Welcome to Centre for Advanced Studies

Developed Prototype

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Innovative Works

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Research Seminar

Centre for Advanced Studies is an in-campus research driven institute established by Dr. A.P.J Abdul Kalam Technical University Lucknow to impart state of the art education to post graduate students and to facilitate quality research work in the emerging areas of Engineering and Technology.

The Institute targets impactful research and innovations in the broad areas of Computer Science and Engineering, Mechatronics, Nanotechnology, Manufacturing Technology and Automation, and Energy Science and Technology.

The Institute is well equipped with state-of-the-art laboratories like Machine Learning Lab installed with Nvidia GPUs, Cybercity Lab for working on cyber security threats in a smart city environment, Google Developers Codelabs established by Google, IoT Lab, Linux Lab, Sensors drives and control Lab, 3D printing Lab with the facilities of Fused Deposition Modeling and Multi Jet printing, Industrial Automation Lab for facilitate complete automation, Industrial robotic center, Design and simulation center, Tribology Lab, Materials Chemistry and Synthesis Laboratory, Micro and Nano Characterization facility, Nano fabrication facility, Device testing facility, Electrochemical Energy Storage Lab, Battery testing facility, Photovoltaics and solar energy lab, and embedded system lab. These facilities provide for research and innovations in interdisciplinary areas of Engineering and Technology to the interested faculty and students of the University promoting growth and progress of the Institute through collaboration by offering training, internships, short term courses, and research projects.

Rewards: The Institute recognises meritorious students with a gold medal for Best M.Tech. Dissertation in each department and a cash prize for research publication in an SCI indexed journal every academic year.

Financial support: Expenses incurred by the students while attending conference, workshop, short-term course, certification course, Memberships, etc are reimbursed subject to production of bills as per the rules of the Institute/ University.

Collaboration: The Institute has MoUs with universities of international importance providing research opportunities through collaboration and exposure to the students with the research communities.

Funded research projects: The Institute offers opportunities to the students to work on challenging problems of funded research projects under supportive faculties.

Publications: The students are motivated to publish high quality research articles in impactful journals that are SCI/ Scopus indexed and top conferences, which is still a far fetched goal in other PG institutes in the country.

Research careers: The capability of the students is enhanced multifold to facilitate research careers with industrial labs or admission in reputed institutes for higher studies.

Access to E- resources: The central library provides electronic resources such as e-journals, e-databases, e-books through online subscriptions to Elsevier Science Direct, Springer Nature, John Wiley, Taylor & Francis, and more.

Sr. No.	Patent Title	Name of Inventors
1	“A System and Method for Machine Learning Based Automatic Detection of Abnormality from Cardiac Sound” Application number: 201911033584 Dated. 21.08.2019, Status: Applied and under examination.	M.K.Dutta, Anjali Yadav, Abhishek Kaushal
2	Multi-Mode Real-time Object Detector and Obstacle Aware Assistive System for Visually Impaired Person (VIP), Application number: 201911047766, Dated: 22.11.2019, Status: Applied and under examination.	M.K. Dutta, Rakesh Chandra Joshi, Saumya Yadav
3	Artificial Intelligence based System and Method for Multi-Class Classification of Heart Diseases, Allotted Application number 201911047767 Dated: 22.11.2019, Status: Applied and under examination.	M.K. Dutta, Shivansh Dubey, Raghuvendra Pratap Tripathi, Anjali Yadav
4	Automatic Detection of Lungs Disease using Machine Learning from Respiratory Sound, Allotted Application number: 202011009043, Dated. 03.03.2020, Status: Applied and under examination	Neeraj Baghel, M.K. Dutta
5	Artificial intelligence based COVID-19 screening tool based on analysis of X-ray images, Application no. 202011024438 dated. 10.06.2020, Status: Applied and under examination.	Rakesh Chandra Joshi Saumya Yadav M.K.Dutta, Vinay Kumar Pathak, M.L.Bhatt Anit Parihar Hardeep Singh Malhotra
6	“System and method for sanitizing currency note(s)” Application number: 202011035026 Dated. 14.08.2020, Status: Published with no. E-12/948/2020/DEL and under examination.	Anuj Kumar Sharma, Mahip Singh
7	“The rapid multipurpose Disinfector” Application number: 202011037517 Dated. 31.08.2020, Status: Applied and under examination	Anuj Kumar Sharma, Mahip Singh
8	“Oxygen monitoring & control, Multi-Functional convertible Robot for hospitals”. Filed and waiting for application number	Mahip Singh, Anuj Kumar Sharma, Amit Rai Dixit
9	“ITPI- steel and mining waste management: intelligent technology and process management for steel industry and mining waste”. Application number: 202011047142 Dated. 29.10.2020, Status: Applied and under examination	Navneet Kumar, Anuj Kumar Sharma, Brijesh Singh, Yatender Chaturvedi , Sanjeev Kumar Sharma, Rakesh Kumar Yadav
10	“OIL REMEDIATION COMPOSITE AND METHOD FOR SYNTHESIS THEREOF”. Application No- 202211030925 Dated.30.05.2022,Status:App lied and under examination	Dr Saurabh Mishra, Ujjawal Singh, Dr Anuj Kumar Sharma

Sr. No.	Title of Project	Funding Agency	Name of PI/ Co-PI	Amount ₹ Lakh / Duration
1	Design and Development of Artificial Intelligence based Screening Tool for Automatic Diagnosis of Osteoporosis in Women	Biomedical Device and Technology Development (BDTD), Department of Science and Technology, DST Gov. of India.	Prof. M.K. Dutta Role: Principal Investigator Collaborator: King George Medical University (KGMU), Lucknow.	74 Lakhs 3 years (Sanctioned, Fund release under Process)	Click here to view More
2	Intelligent Stethoscope: A low cost device based on body auscultation for Early Medical diagnosis of Heart, Lung and Prenatal health	TDT Division, Biomedical Device and Technology Development (BDTD), Department of Science and Technology, Gov. of India	Prof. M.K. Dutta (PI)	34.45 2 years	Click here to view More
3	Assistive device to impart perceptual ability to visually-impaired using intelligent scene captioning	SEED Division, Technology Interventions for Disabled and Elderly Programme, Department of Science and Technology, Gov. of India	Prof. M.K. Dutta (PI)	39.25 3 years	Click here to view More
4	Development of thermal sensors for measuring the tool tip temperature its online monitoring	AKTU Under “Visvesvaraya Research Promotion Scheme (VRPS)”	Dr. Anuj Kumar Sharma (PI) Dr. Rabesh Kumar Singh (Co-PI)	5.0 2 years	Click here to view More
5	Design and fabrication of human hand inspired soft robotic hand for differently-abled persons	Collaborative Research and Innovation Program (CRIP) under AKTU, Lucknow and TEQIP-III, MHRD, Govt. of India	Dr. Anuj Kumar Sharma (PI) Dr. Rabesh Kumar Singh (Co-PI)	3.0 1 years	Click here to view More
6	Computational fluid dynamics CFD analysis for designing of ore transportation through pipelines	Collaborative Research and Innovation Program (CRIP) under AKTU, Lucknow and TEQIP-III, MHRD, Govt. of India	Dr. Anuj Kumar Sharma (Co-PI)	3.0 1 years	Click here to view More
7	Development of Novel Method for Synthesizing Metal Oxide/Carbon nanocomposites for Energy Storage and Related Applications	Collaborative Research and Innovation Program (CRIP) under AKTU, Lucknow and TEQIP-III, MHRD, Govt. of India	Dr. Piyush Jaiswal (PI)	3.0 1 years	Click here to view More
8	Near net shape generation of nano-composite parts via stir casting and 3D printing approach	Collaborative Research and Innovation Program (CRIP) under AKTU, Lucknow and TEQIP-III, MHRD, Govt. of India	Dr. Rabesh Kumar Singh (Co-PI)	3.0 1 years	Click here to view More
9	Development of sustainable hybrid nano-lubricant with improved tribological properties for green machining	SERB (statutory body of DST Govt. of India	PI Dr. Anuj Kumar Sharma Co-PI Prof. J. Ramkumar IIT Kanpur	18.30 3 years	Click here to view More

Sr. No.	Student Innovations	Research Team	Research Outcomes (Publications/ Patents)
1	Title: Intelligent Stethoscope: A low-cost device based on body auscultation for early medical diagnosis of heart, lung and prenatal health Description: Artificial Intelligence based automatic intelligent stethoscope is developed to diagnose cardiac, pulmonary and prenatal disorders to minimize human intervention. The proposed model is ported into small... computing devices to make a stand-alone diagnostic tool that may be of help in remote primary health care centers. The proposed method is non-invasive, efficient, robust, and has low time complexity making it suitable for real-time applications.	Neeraj Baghel Junior Research Fellow Anjali Yadav Junior Research Fellow Juwairiya Siraj Khan Junior Research Fellow Mentor : Prof. M.K.Dutta	Patents from the project: (A) “A System and Method for Machine Learning Based Automatic Detection of Abnormality from Cardiac Sound” Application number: 201911033584 Dated. 21.08.2019, Status: Applied and under Examination (B) “Artificial Intelligence based System and Method for Multi-Class Classification of Heart Diseases”, Allotted Application number 201911047767 Dated: 22.11.2019, Status: Applied and under Examination (C) “Automatic Detection of Lungs Disease using Machine Learning from Respiratory Sound” Application number: 202011009043 Dated. 03.03.2020, Status: Applied and under Examination Publications from the project: ... 1) Anjali Yadav, Anushikha Singh, Malay Kishore Dutta & Carlos M. Travieso “Machine Learning Based Classification of Cardiac Diseases from PCG recorded Heart Sounds” Neural Computing and Applications, Springer Verlag Publishers, DOI - 10.1007/s00521-019-04547-5, December 2020, SCI indexed Impact Factor – 4.774. 2) Neeraj Baghel, Malay Kishore Dutta & Radim Burget, “Automatic Diagnosis of Multiple Cardiac Diseases from PCG Signals using Convolutional Neural Network”  Computer Methods and Programs in Biomedicine, Volume 197, doi.org/10.1016/j.cmpb.2020.105750, Elsevier Publishers, 2020, SCI indexed, Impact Factor – 3.632. 3) Neeraj Baghel, Radim Burget, M.K.Dutta “1D-FHRNet: Automatic Diagnosis of Fetal Acidosis from Fetal Heart Rate Signals”, Detection in Children using Deep Neural Network” Biomedical Signal Processing and Control, Elsevier Publisher, Accepted and in Press. SCI indexed Impact Factor – 3.317	Click here to view More pdf
2	Title:Assistive device to impart perceptual ability to visually-impaired using intelligent scene captioning Description: An artificial intelligence-based fully automatic assistive technology is developed to recognize different objects, obstacles, read text articles, and auditory inputs are provided to the user in real time, which gives better understanding to the visually impaired person about their surroundings. A deep-learning model is trained with multiple images of objects that are highly relevant to the visually impaired person.	Rakesh Chandra Joshi Research Scholar Saumya Yadav Junior Research Fellow Abha Upadhyay Junior Research Fellow Anushka Chaurasia Junior Research Fellow Mentor : Prof. M.K.Dutta	Patents from the project: Multi-Mode Real-Time Object Detector and Obstacle Aware Assistive System for Visually Impaired Person (VIP)” Application No.- 201911047766, Dated - 22.11.2019, Status : Applied and Under Examination “Automatic Detection of Lungs Disease using Machine Learning from Respiratory Sound” Application number: 202011009043 Dated. 03.03.2020, Status: Applied and under Examination Publications from the project: 1) Joshi, R.C.; Yadav, S.; Dutta, M.K.; Travieso-Gonzalez, C.M. Efficient Multi-Object Detection and Smart Navigation Using Artificial Intelligence for Visually Impaired People. Entropy 2020, 22, 941. ; https://doi.org/10.3390/e22090941, SCI indexed Impact Factor -2.494 ... 2) Yadav, R. C. Joshi, M. K. Dutta, Martin Kiac, Pavel Sikora, “Fusion of Object Recognition and Obstacle Detection approach for Assisting Visually Challenged Person” 2020 43rd International Conference on Telecommunications and Signal Processing (TSP), July 7-9, 2020, Milan, Italy. DOI: 10.1109/TSP49548.2020.9163434 3) R. C. Joshi, S. Yadav and M. K. Dutta, "YOLO-v3 Based Currency Detection and Recognition System for Visually Impaired Persons," 2020 International Conference on Contemporary Computing and Applications (IC3A), Lucknow, India, 2020. DOI: 10.1109/IC3A48958.2020.233314 4) D. Dahiya, H. Gupta and M. K. Dutta, "A Deep Learning based Real Time Assistive Framework for Visually Impaired," 2020 International Conference on Contemporary Computing and Applications (IC3A), Lucknow, India, 2020. DOI: 10.1109/IWOBI47054.2019.9114475 5) Lalita Jaiswar, Anjali Yadav, Malay Kishore Dutta, Carlos Travieso-González, Luis Esteban-Hernández, “Transfer Learning based Computer Vision Technology for Assisting Visually Impaired for detection of Common Places” 3rd International Conference on Applications of Intelligent Systems 2020 (APPIS 2020) Las Palmas de Gran Canaria, Spain, ACM Digital Library. DOI: 10.1145/3378184.3378215 6) Saumya Yadav, R. C. Joshi, M. K. Dutta, R. Burget. “Artificial Intelligence based Robust and Real-time Assistance for Visually Impaired People”- Assistive Technology (The Official Journal of RESNA), Taylor & Francis Publishers- Submitted and under review	Click here to view More pdf
3	Title:Artificial Intelligence Based Automatic Identifying Problem in Spinal Cord Using Gait Patterns Description: Artificial Intelligence –based “Automatic Identifying Problem in Spinal Cord Using Gait Patterns” to early detection of problem-... related to the spinal cord.The Detection is based on Gait Cycle(Walking on Gait Sensors) that can use to predict different problem related to the spinal cord which is physical discomfort occurring anywhere on the spine or back ranging from mild to disabling.	Chandrasen Pandey M.Tech CSE (2019-21) Neeraj Baghel Junior Research Fellow Mentor : Prof. M.K.Dutta	Publications from the project: Chandrasen Pandey, Neeraj Baghel, Malay Kishore Dutta and Carlos M Travieso-Gonzalez”Automatic Diagnoses of Back Pain Using Gait Patterns”International Work Conference on BioInspired Intelligence,October 21-23,2020-Universidad de Costa Rica (UCR) and Tecnologico de Costa Rica(TEC),COSTA RICA..	Click here to view More pdf
4	Title:Artificial Intelligence Based Automatic Diagnosis of Chlorosis in Vigna Mungo Plant Description: Artificial Intelligence –based method for automatic diagnosis of chlorosis in vigna mungo plant is possible using this method. The detection is based on a leaf pattern that can use to predict different problem related to the vigna mungo plant which is necessary for proper growth of the plant. The method uses machine learning and deep... learning for identifying the severity of chlorosis in vigna mungo plant. The method can be integrated with drones to surveillance the large cultivated fields in real-time.	Chandrasen Pandey M.Tech CSE (2019-21) Manoj Kaushik M.Tech CSE (2019-21) Rakesh Chandra Joshi Research Scholar Neeraj Baghel Junior Research Fellow Mentor : Prof. M.K.Dutta	Publications from the project: 1) Pandey, C., Baghel, N., Dutta, M.K. et al. Machine learning approach for automatic diagnosis of Chlorosis in Vigna mungo leaves. Multimed Tools Appl 80, 13407–13427 (2021). https://doi.org/10.1007/s11042-020-10309-62021,SCI indexed Impact Factor -2.51 2) Rakesh Chandra Joshi, Manoj Kaushik, Malay Kishore Dutta,Ashish Srivastava, Nandlal Choudhary,VirLeafNet: Automatic analysis and viral disease diagnosis using deep-learning in Vigna mungo plant,Ecological Informatics,Volume 61,2021,101197,ISSN 1574-9541,https://doi.org/10.1016/j.ecoinf.2020.101197.2021, SCI indexed Impact Factor -2.30	Click here to view More pdf
5	Title:Dense convolutional Neural Network based Multiclass plant Disease Detection and Classification Description: A deep-learning-based approach is presented for the plant disease detection and classification from leave images captured in various resolutions.... Dense convolutional neural network architecture is trained on a large plant leaves image dataset from multiple countries. Images have several inter-class and intra-class variations with complex and challenging conditions that have been addressed in this dense neural network The processing time to process a single plant leaf image is 0.016s with significant accuracy which signifies its real-time performance.	Vaibhav Tiwari M.Tech CSE (2019-21) Rakesh Chandra Joshi Research Scholar Mentor : Prof. M.K.Dutta	Publications from the project: 1) Vaibhav Tiwari, Rakesh Chandra Joshi, and Malay Kishore Dutta. "Dense convolutional neural networks based multiclass plant disease detection and classification using leaf images." Ecological Informatics 63(2021):101289.DOI:10.1016/j.ecoinf.2021.101289SCI indexed Impact Factor – 2.51.	Click here to view More pdf
6	Title:Truth Identification from EEG Signal by using Convolution neural network: Lie Detection Description: AI lie detector is developed that can analyse the brain signals of a person and detect if a person is telling the truth or lying. Deep learning has... been used to train and test the system with 14 channel 1D EEG signal data to make it efficient and robust for real-time implementation. The system developed will be highly effective in criminal investigations and other applications.Currently polygraph technique is used for truth identification which relies on physiological reactions of a person that can be controlled and hence the method is not so effective. To overcome this our model uses live recorded brain signals which cannot be altered.	Neeraj Baghel Junior Research Fellow Divyanshu Singh M.Tech CSE (2019-21) Mentor : Prof. M.K.Dutta	Publications from the project: 1) N. Baghel, D. Singh, M. K. Dutta, R. Burget and V. Myska, "Truth Identification from EEG Signal by using Convolution neural network: Lie Detection," 2020 43rd International Conference on Telecommunications and Signal Processing (TSP), 2020, pp. 550-553, doi: 10.1109/TSP49548.2020.9163497.	Click here to view More pdf
7	Title:Identification of Disease using Deep Learning and Evaluation of Bacteriosis in Peach Leaf Description: Artificial Intelligence based method is developed to help in timely identification of disease and evaluation of bacteriosis in peach leaf which will reduce the use of pesticide and minimize loss of peach crops. The method can be integrate... with UAV device and remain connected within the same local area network (LAN) to use as a diagnostic model or early warning tool and help the farmer to keep eye on peach field without being present there in person.	Saumya Yadav Junior Research Fellow Neha Sengar M.Tech CSE (2019-21) Akriti Singh M.Tech CSE (2019-21) Mentor : Prof. M.K.Dutta	Publications from the project: Saumya Yadav, Neha Sengar, Akriti Singh, Anushikha Singh & Malay Kishore Dutta, “Identification of Disease using Deep Learning and Evaluation of Bacteriosis in Peach Leaf”, Ecological Informatics, Elsevier Publishers, DOI - 10.1016/j.ecoinf.2021.101247, February 2021, SCI indexed Impact Factor – 2.51.	Click here to view More pdf
8	Title:Automated System for Face-mask Detection using Convolutional Neural Network Description:An automated artificial intelligence based tool is developed for face mask detection using deep learning algorithm that is capable of detecting people wearing face-masks in video-stream in real-time in Covid-19 pandemic to avoid spreading virus.... The method can be integrate with camera device and remain connected within the same local area network (LAN) to use tool in health care and public areas to keep eye on peoples without being present there in person.	Saumya Yadav Junior Research Fellow Neha Sengar M.Tech CSE (2019-21) Akriti Singh M.Tech CSE (2019-21) Mentor : Prof. M.K.Dutta	Publications from the project: 1) Neha Sengar, Akriti Singh, Saumya Yadav & Malay Kishore Dutta, “Automated System for Face-mask Detection using Convolutional Neural Network”, 7th International Conference on Mathematics and Computing, Springer Publishers, March 2021, Indian Institute of Engineering Science and Technology, India	Click here to view More pdf
9	Title:Application of Machine Learning in Risk Prediction of Type 2 Diabetes Mellitus (T2DM) using Anthropometric, Biochemical, and Genetic Parameters Description:Artificial Intelligence based method is developed for prediction of ...undiagnosed type 2 diabetes mellitus in north Indian population at early stage that can significantly reduce national healthcare expenditure, particularly in the area of diabetes and its complications. Research revealed that anthropometric parameters, biochemical parameters, and gene type parameters have prominent presence on the top-10 key factors for T2DM.	Saumya Yadav Junior Research Fellow Neha Sengar M.Tech CSE (2019-21) Mentor : Prof. M.K.Dutta	Publications from the project: 1) Neha Sengar, Saumya Yadav Atar Singh Kushwah, Pushpank Vats, Monisha Banerjee & Malay Kishore Dutta, “Application of Machine Learning in Risk Prediction of Type 2 Diabetes Mellitus (T2DM) using Anthropometric, Biochemical, and Genetic Parameters”, Journal of Ambient Intelligence & Humanized Computing (AIHC), Springer Nature Publishers, (Under Revision).	Click here to view More pdf
10	Title:Cytokine Gene Variants and Socio-Demographic Characteristics as Predictors of Cervical Cancer: A Machine Learning Approach Description:A machine learning-based approach for the risk prediction of cervical cancer. Different risk factors adopting demographic details and cytokine genes were analysed on collected dataset.... Various statistical parameters are used for the evaluation on different machine-learning approaches. The risk factor analysed in this study can be taken as a biomarker in developing a cervical cancer diagnosis system.	Rakesh Chandra Joshi Junior Research Fellow Manoj Kaushik M.Tech CSE (2019-21) Mentor : Prof. M.K.Dutta	Publications from the project: 1) Manoj Kaushik, Rakesh Chandra Joshi, Atar Singh Kushwah, Maneesh Kumar Gupta, Monisha Banerjee, Radim Burget, and Malay Kishore Dutta, “Cytokine Gene Variants and Socio-Demographic Characteristics as Predictors of Cervical Cancer: A Machine Learning Approach” Computers in Biology and Medicine, Available online 8 June 2021, 104559, https://doi.org/10.1016/j.compbiomed.2021.104559, SCI indexed Impact Factor – 3.434.	Click here to view More pdf
11	Title:A Deep Learning Approach for Epilepsy Seizure Detection using EEG Signals Description:A deep learning model that is fast, effective and non-invasive in the diagnosis of epilepsy seizure using Electroencephalogram (EEG) signals. The system contains a robust pre-processing module to... automatic removal of artifacts from the EEG signals and an epilepsy	Manoj Kaushik M.Tech CSE (2019-21) Divyanshu Singh M.Tech CSE (2019-21) Mentor : Prof. M.K.Dutta	Publications from the project: 1) Manoj Kaushik, Divyanshu Singh, Malay Kishore Dutta, Carlos M. Travieso González “A Deep Learning Approach for Epilepsy Seizure Detection using EEG Signals” International Work Conference on Bioinspired Intelligence, October 21-23, 2020 - Universidad de Costa Rica (UCR) and Tecnológico de Costa Rica (TEC), COSTA RICA.	Click here to view More pdf
12	Title:Heart Anomaly Classification using Convolutional Neural Network Description:An effective deep learning-based automatic approach for heart anomaly detection has been proposed to ease the process of heart anomaly detection.... It is capable of taking heart sounds recorded through smart phones as an input. The heart sounds are pre- processed (framing, artifact removal and de-noising), then converted into a Mel-spectrogram i.e. visual approach for representing the heart signal over time at different frequencies.	Shikha Rani M.Tech CSE (2019-21) Mentor : Prof. M.K.Dutta	Publications from the project: Shikha Rani & Malay Kishore Dutta, “Heart Anomaly Classification using Convolutional Neural Network”, International Conference on Data Science and Applications (ICDSA 2021),school of mobile computing and communication, Jadavpur university, Kolkata, India	Click here to view More pdf
13	Title:SLINet: Dysphasia Detection in Children using Deep Neural Network Description:A robust Deep learning framework to diagnose specific language impairment (dysphasia) in children at early stage so that it can be treated timely. A rigorous analysis based on different age-group is conducted. Approach is gender, age and expert-independent.	Manoj Kaushik M.Tech CSE (2019-21) Neeraj Baghel Junior Research Fellow Mentor : Prof. M.K.Dutta	Publications from the project: Shikha Rani & Malay Kishore Dutta, “Heart Anomaly Classification using Convolutional Neural Network”, International Conference on Data Science and Applications (ICDSA 2021),school of mobile computing and communication, Jadavpur university, Kolkata, India	Click here to view More pdf
14	Title:Machine Learning based Malware Analysis in Android and Windows Platforms Description:An Artificial Intelligence based method is developed for Android and Windows based Malware Detection and Classification. An efficient host-server based... malicious app detection system is developed where on-device feature extraction can be performed for the app to be analyzed, without the need for rooting the device. The extracted features are sent over to remote server where machine learning is applied for malware analysis and detection. At server-end, static features such as permissions, app components, etc. have been used to train classifiers for Android malware detection and classification. Discriminatory features were used to train the machine learning based classifiers for real time identification of the Malware.	Anam Fatima M.Tech CSE (2017-19) Areeba Irshad M.Tech CSE (2017-19) Mentor : Prof. M.K.Dutta	Publications from the project: 1) Anam Fatima, Saurabh Kumar and Malay Kishore Dutta, "Android Malware Detection Using Genetic Algorithm based Optimized Feature Selection and Machine Learning" at 2019 42nd International Conference on Telecommunications and Signal Processing, Budapest, Hungary, 2019, IEEE Xplore Digital Library, pp. 220-223, doi: 10.1109/TSP.2019.8769039. ... 2) Areeba Irshad, Ritesh Maurya, Malay Kishore Dutta, Radim Burget , Vaclav Uher, “ Feature Optimization for Run Time Analysis of Malware in Windows Operating System using Machine Learning Approach” 42nd International Conference on Telecommunications and Signal Processing- 2019 (TSP – 2019) - Budapest, Hungary, 2019, PP. 255-260, IEEE Xplore Digital Library, DOI: 10.1109/TSP.2019.8768808. 3) Anam Fatima, Ritesh Maurya, Malay Kishore Dutta, Radim Burget, Jan Masek, "Host-Server based Malware Detection System for Android Platforms Using Machine Learning" at 5th International Conference on Computational Intelligence and Communication Technology (CICT-2019), India. Paper presented and published as part of Springer Book Series on "Advances in Intelligent Systems and Computing" vol 1086. Springer, Singapore. doi: https://doi.org/10.1007/978-981-15-1275-9_17.	Click here to view More pdf
15	Title:EMF radiations effect on brain: An artificial intelligence based study Description:An automatic image processing–based approach is used where geometric features extracted from the segmented... brain region has been analyzed for identifying the effect of EMF radiation on the morphology of a brain, using drosophila as a specimen. Genetic algorithm–based evolutionary feature selection algorithm has been used to select an optimal set of geometrical features, which, when fed to the machine learning classifiers, result in their optimal performance.	Ritesh Maurya Research Scholar (CSE) Mentor : Prof. M.K.Dutta	Publications from the project: Ritesh Maurya., Neha Singh, Tanu Jindal, Vinay Kumar Pathak, M. K. Dutta, Machine learning–based identification of radiofrequency electromagnetic radiation (RF-EMR) effect on brain morphology: a preliminary study. Med Biol Eng Comput 58, 1751–1765 (2020). https://doi.org/10.1007/s11517-020-02198-6	Click here to view More pdf
16	Title:Artificial Intelligence based Diagnosis of Auto-Immune Disease using Capsule Neural Network Description:Manual analysis of the indirect-immunofluorescence (IIF)... human epithelial cell Type-2 (HEp-2) cell image for the diagnosis of an auto-immune disease is a subjective and time-consuming process, and it is also prone to human-errors. The present work proposes an automatic capsule neural network (CapsNet) based framework for HEp-2 cell image classification to compensate for the deficiencies present in the prominent convolution neural network (CNN) based frameworks.	Ritesh Maurya Research Scholar (CSE) Mentor : Prof. M.K.Dutta	Publications from the project: Maurya, R., Pathak, V.K. & Dutta, M.K. Computer-aided diagnosis of auto-immune disease using capsule neural network. Multimed Tools Appl (2021). https://doi.org/10.1007/s11042-021-10534-7	Click here to view More pdf
17	Title:Deep Learning-based COVID-19 automatic diagnostic framework using Chest X-ray images Description:A robust deep learning-based system is proposed to detect the COVID-19... using chest X-ray images. Infected patient's chest X-ray images reveal numerous opacities (denser, confluent, and more profuse) in comparison to healthy lungs images which are used by a deep learning algorithm to generate a model to facilitate an accurate diagnostics for multi-class classification (COVID vs. normal vs. bacterial pneumonia vs. viral pneumonia) and binary classification (COVID-19 vs. non-COVID). X-ray images have been used for training and model performance assessment from several hospitals of India and abroad. The proposed model performs rapid disease detection in 0.137 s per image in a system equipped with a GPU and can reduce the workload of radiologists by classifying thousands of images on a single click to generate a probabilistic report in real-time.	Rakesh Chandra Joshi Research Scholar (CSE) Saumya Yadav Junior Research Fellow Mentor : Prof. M.K.Dutta	Publications from the project: 1) Rakesh Chandra Joshi, Saumya Yadav, Vinay Kumar Pathak, Hardeep Singh Malhotra, Harsh Vardhan Singh Khokhar, Anit Parihar, Neera Kohli, D. Himanshu, Ravindra K. Garg, Madan Lal Brahma Bhatt, Raj Kumar, Naresh Pal Singh, Vijay Sardana, Radim Burget, Cesare Alippi, Carlos M. TraviesoGonzalez, Malay Kishore Dutta, A deep learningbased COVID-19 automatic diagnostic framework using chest X-ray images,... Biocybernetics and Biomedical Engineering, Volume 41, Issue 1, 2021, Pages 239-254, https://doi.org/10.1016/j.bbe.2021.01.002. 2)Rakesh Chandra Joshi, Malay Kishore Dutta and Carlos M. Travieso-González, “Artificial Intelligence based Multi-sensor COVID-19 Screening Framework” International Work Conference on Bioinspired Intelligence, 2020 (IWOBI-2020), UCR & TEC, Costa Rica – Publisher : Springer Nature	Click here to view More pdf

Sr. No.	Date	Research Group Name	Research Seminar Topic	Research Seminar Presented by	Abstract
1	6th January 2021	AI research Group	Deep Learning Based Framework for Microscopic Cell Images Classification using Multi-Level Ensemble	Ritesh Maurya (Research Scholar, Computer Science and Engineering,CAS)	Abstract pdf
2	13th January 2021	AI research Group	Deep Machine Learning in Time Series: Cardiac and Pulmonary Signals analysis using CNN models	Neeraj Baghel, (Junior Research Fellow, Centre for Advanced Studies, Lucknow)	Abstract pdf
3	22nd January 2021	AI research Group	Deep Learning in Medical Imaging: Automated Detection of COVID-19 from Chest X-Rays using deep convolutional neural network	Saumya Yadav, (Junior Research Fellow, Centre for Advanced Studies, Lucknow)	Abstract pdf
4	27th January 2021	AI research Group	Deep Learning in Computer Vision with Sensors: Application in Assistance for Visually Impaired People	Rakesh Chandra Joshi, (Research Scholar, Computer Science and Engineering,CAS)	Abstract pdf
5	3rd February 2021	AI research Group	Cost Function Optimization Strategies in Deep Neural Network	Kumud Patel, (Research Scholar, Computer Science and Engineering,CAS)	Abstract pdf
6	10th February 2021	AI research Group	Network Optimization for Deep Learning Models	Chavi Bajpai, (Research Scholar, Computer Science and Engineering,CAS)	Abstract pdf
7	17th February 2021	AI research Group	Brain - computer interaction using Artificial Intelligence	Juwairiya Siraj Khan, (Junior Research Fellow, Computer Science and Engineering,CAS)	Abstract pdf
8	16th April 2021	Mechatronics research Group	Robotic Fish: Design and swimming mechanism	Mithilesh Kumar Koiri, (Research Scholar, Mechatronic,CAS)	Abstract pdf
9	30th November 2021	AI research Group	Deep Generative Models in Deep Learning	Chetana Singh, (Research Scholar, CSE,CAS)	Abstract pdf
10	3rd December 2021	AI research Group	Ensemble Learning based Classification in Artificial Intelligence and its Applications	Karnika Dwivedi, (Research Scholar, CSE,CAS)	Abstract pdf
11	18th January 2022	AI research Group	Explainable AI in Healthcare	Vinay Priy Mishra, (Research Scholar, CSE,CAS)	Abstract pdf
12	22th January 2022	Mechatronics research Group	Corrosion Prevention of Steel using Arbi Leaves	Vinit Kumar Jha,(M.Tech (Final Year), CAS)	Abstract pdf
13	07th September 2022	AI research Group	Deep Learning based Sound Generation with different Approaches and Challenges	Chetna singh,(Research Scholar, CSE,CAS)	Abstract pdf

S.No.	Date/ Time	Title of Talk	Speaker
1	Friday May 1, 2020 3 to 5 PM	Intellectual Property Rights	Prof. J Ramkumar (IIT Kanpur)	Click here to view More
2	Friday May 1, 2020 3 to 5 PM	Analysis and Modeling of Coronavirus spread data	Mr. Jatin Chaudhary (CISCO Bangalore)	Click here to view More
3	Saturday May 2, 2020 3 to 5 PM	Biped locomotion	Prof. Ashish Dutta (IIT Kanpur)	Click here to view More
4	Saturday May 2, 2020 3 to 5 PM	Entrepreneurship Development Program	Mr. T. S. Rajput (NSIC, A Govt of India Enterprise)	Click here to view More
5	Friday May 8, 2020 2 to 4 PM	Waste to Wealth	Dr. Nanda Gopal Sahoo (Kumaun University Nainital)	Click here to view More
6	Friday May 8, 2020 2 to 4 PM	Patenting for Engineers and Researchers	Dr. Girish Kunte (TeKIP Bangalore)	Click here to view More
7	Saturday May 9, 2020 2 to 4 PM	Social media-based epidemic intelligence	Dr. Aditya Joshi (CSIRO Sydney)	Click here to view More
8	Saturday May 9, 2020 2 to 4 PM	Robotics2Rural	Prof. S K Saha (IIT Delhi)	Click here to view More
9	Friday May 15, 2020 2:30 to 3:30 PM	Audio and Acoustic Signal Processing: The quest for High Fidelity Continues	Prof. Karlheinz Brandenburg (Ilmenau Germany)	Click here to view More
10	Saturday May 16, 2020 10:30 to 11:30 AM	Complex Networks	Prof. Ljiljana Trajkovic (Simon Fraser University Canada)	Click here to view More
11	Friday May 22, 2020 4 to 5 PM	Hydrogen Storage & Lithium Ion Battery: Contributer towards Energy Sustainability	Dr. Rupesh Rohan (IRMRA Thane)	Click here to view More
12	Saturday May 23, 2020 9 to 10 AM	Understanding Viruses in the Corona pandemic era	Dr. Pooja Saxena (Medicago R&D Inc. Canada)	Click here to view More
13	Saturday May 30, 2020 3:30 to 5 PM	Recent trends in automotive engines	Prof. V Ganesan (IIT Madras)	Click here to view More
14	Tuesday June 9, 2020 2:30 to 3:30 PM	Deep Learning in Medical Image Analysis – Challenges and Applications	Prof. Dorit Merhof (Aachen University Germany)	Click here to view More
15	Saturday June 13, 2020 3 to 4 PM	Resistive Switching technology for next-generation applications	Dr. Amitesh Kumar (NIT Patna)	Click here to view More
16	Saturday June 20, 2020 2:30 to 3:30 PM	Secrets of Successful Project Teams: Managing bias in project organizations for efficient decision-making	Mr. Mithun Mridha (Altran France) and Prof. Katarzyna Grzesik-Harz (SUMAS Switzerland)	Click here to view More

S. No.	Name of Lab/ Equipment	Description/ Applications
1	Nvidia DGX 2 server(two petaFlops system) An Artificial Intelligence (AI) Lab with high-performance Graphics Processing Units (GPU) server	This artificial intelligence lab is one of the few state-of-the-art labs in India and first in Uttar Pradesh, equipped with NVIDIA-DGX-2 which is the world’s first 2 petaflops system, packing the power of 16 of the world’s most advanced GPUs and accelerating the newest deep learning model types that were previously untrainable. With ground-breaking GPU scale, models can be trained 4X bigger on a single node. In comparison with legacy x86 architectures, DGX-2’s ability to train ResNet-50 would require the equivalent of 300 servers with dual Intel Xeon Gold CPUs. The Artificial Intelligence Lab can also help to train students, developers, data scientists, and researchers to use deep learning and accelerated computing to solve real-world problems across a wide range of domains. With access to GPU-accelerated workstations in the cloud, researchers and students will learn how to train, optimize, and deploy neural networks using the latest deep learning tools, frameworks, and SDKs. They can also learn how to assess, parallelize, optimize, and deploy GPU-accelerated computing applications. GPU computing leverages the parallel processing capabilities of GPU accelerators and enabling software to deliver dramatic increase in performance for scientific, data analytics, engineering, consumer, and enterprise applications.
2	BET Measurement System	The equipment is useful for determining the surface area of materials. Potential application includes all those areas where the high surface area of materials is a necessity.
3	Industrial Robotic Center	An advanced state of the art Industrial Robotic Center is established in the institute by KUKA India Private Limited (A German Company). The robotic center has three robotic cells, Material handling Cell, MIG welding Cell, Bare robotic cell. The KUKA robots facility is used to understand and train basic concepts of robot programming, motion planning, and programming methodology of robotic systems, performing research-oriented specific tasks including pick and place job. MIG welding cell is the Bare robot which students mainly use to learn, implement and test their new ideas, methods, and techniques using robotic systems. The purpose of Bare robotic cell is to use the arm for the testing and analysis of the systems developed by the students. The robotic manipulator can be customized as per the systems designed and developed by the students.
4	Industrial Automation Lab	Industrial Automation Lab offers manufacturing automation on Flexible Manufacturing Systems (FMS) including material storing and dispatching equipment AS/RS, machining stations CNC lathe, CNC milling, CNC grinding, material handling equipment such as 4 axis and 6 Axis Robot, loading /unloading automated guided vehicle(AGV), Assembly Station and Visual Inspection Setup. This Lab provides in-depth coverage of Computer Integrated Manufacturing and Industrial Automation. It provides hands-on study particularly in the areas of computer Aided Manufacturing (CAM), Computer Numerical Control (CNC) and manufacturing automation. It has tool dynamometer (Kistler company) and minimum quantity lubrication setup along with Temperature Data Acquisition system. The speciality of this Lab is that the CNC machines installed here can be individually utilized for research purpose.
5	3D Printing Lab	A method of manufacturing is known as ‘Additive manufacturing’, due to the fact that instead of removing material to create a part, the process adds material in successive patterns to create the desired shape. 3D Printing uses software that slices the 3D model into layers (0.01mm thick or less in most cases). Each layer is then traced onto the build plate by the printer, once the pattern is completed, the build plate is lowered and the next layer is added on top of the previous one. Main areas of use are: Prototyping, Specialized parts – aerospace, military, biomedical engineering, dental, Hobbies and home use, Future applications– medical (body parts), buildings and cars. The entire 3D printing technology can be divided into 3 steps – (a) 3D Design (b) Slicing (c) 3D Printing. Two types of printers are available in our center. These 3D printers work on the principal of fused material deposition and filament-based polymers deposition to shape an object, layer-by-layer.
6	Design and Simulation Center	This lab consists of 18 high end specifications computer systems (32 GB high speed RAM, 4 GB dedicated Graphics card and high-performance multicore Intel processor) with latest design and simulation software like SolidWorks, ANSYS, and MATLAB etc., which enables the students to simulate various complex designs. This lab is integrated with 3D printing lab so as to design and develop the prototypes for testing. Using the facility and MATLAB, the students can develop innovative solutions to challenging research problems. A few application areas are Antenna Design and Placement, Autonomous Sensor Development, Avionics and Flight Control, Electric Motors, Electronics Reliability, E-Motor NVH and Active Sound Design for EV, Gas Turbines, Hypersonics, PCBs, ICs and IC Packages, Power Electronics, Rotating Machinery, Vehicle Chassis, Wind Turbine Design.
7	Sensor Drives & Control Lab	This is a fundamental lab for students from different backgrounds to make them understand the working and usage of different types of sensors, controllers and drives. Students are taught about the working principle, sensors usability in embedded systems, actuators usability in automation and embedded systems. They are also trained to develop their own sensors/ actuation system, according to the project requirements. Starting from semiconductor, Diode, transistors, Logic Gate, the students are trained to program different microcontrollers using different high level language like- C++, Python, Matlab etc. so that they can have the capacity and competence to develop different smart system of their own for the service and benefit of human society.
8	Pin on disc tribometer	A pin on disc tribometer consists of a stationary pin that is normally loaded against a rotating disc. The pin can have any shape to simulate a specific contact, but cylindrical tips are often used to simplify the contact geometry. This Ducom Pin/Ball on Disk Tribometer is a test instrument designed for accurate and repeatable tribological characterization of bulk materials, coatings and lubricants. The Pin/Ball on Disk Tribometer is used to characterize the tribological behavior for almost all material bench-marking and materials development needs. Different types of objectives can be resolved related to analysis of wear characteristics of industrial materials, composites, metallic, ceramic components with different lubricant and varying loads.
9	Human Non-invasive Blood Pressure (NIBP) Monitor	Reliably record and monitor trends in response to interventions on finger arterial pressure, systolic, diastolic, mean arterial, heart rate and interbeat interval. Equipped with Volume Clamp Technology that provides accurate finger pressure measurement and Height Correction unit which can automatically correct movement of the finger cuff relative to the heart, (HCU) Heart Rate Variability HRV (psychophysiology) Biopotentials & GSR (psychophysiology) Record and measure various physiological responses such as biopotential recordings (EOG, ECG, EMG, EEG, GSR). In Cardiovascular studies, ECG signals are recorded to examine heart rate, heart rate variability, and analysis of the waveform morphology, arrhythmia and other similar functions, and sleep studies.
10	Equi-vital Physiological Monitoring System	Comfortable belts for recording physiological data via a compact and unobtrusive sensor belt, leaving the subject free to move naturally. Module can record ECG signal, Acceleration (3 axis), Respiration, Skin Temperature, SPO2 and GSR. The system should provide real time data recording with online and offline analysis. Provide Noise and movement artifactcillary pack. It is used to record and measure various physiological responses such as EOG, ECG, EMG, EEG and Galvanic Skin Response (GSR).
11	Marker less Motion capture system (2-D Gait Analysis System) with Force plate	It contains 16 * 2 feet stable three layered platform. The software provides parameters like velocity, cadence, step length, step width, stance and swing percent, toe in/out angle, instantaneous. Centre of Pressure (COP), Centre of Mass, Foot angle, direction of progression, Left to Right Ratios path efficiency, total pressure, footfall COP, and [COP-COMe] etc. There is also a facility for multiple protocols like walking, standing, running and jumping. It can also be used for comparing variables between the left and right footfalls to evaluate symmetry, track changes overtime to quantify patient progress, and provide metrics and complete reports. Video synchronization of 2 or more cameras with replay capabilities and a push-button switch for marking events, is also available. It is used in research and study of Cerebral Palsy, Stroke, Parkinson’s Disease, Multiple Sclerosis, Alzheimer’s Disease, Ataxia, Muscular Dystrophy, Neuropathy Concussion, Fall Risk, Osteoarthritis, Motor Impairments, Sensory Impairments, Knee and Hip Replacement, Injury Rehabilitation, Amputation, Brace fitting and tuning, Prosthetic limb optimization, Equines Gait (Toe-Walking), Spine Bifida.
12	EMOTIV EPOC+ 14 Channel Mobile EEG	EMOTIV EPOC+ 14 channel EEG provides access to professional grade brain data. Access high-quality raw EEG data, conduct research leveraging our detections for mental commands, analyse performance metrics or facial expressions. The EPOC+ measures both EEG and 9-axis motion data. Data is transmitted wirelessly through Bluetooth. It is a 5-channel wireless EEG device covering frontal, temporal and parietal and occipital locations around the brain. It utilizes proprietary polymer sensors that are hydrophilic they pull moisture from the air and skin. EMOTIV EPOC+ 14 channel mobile EEG is designed for scalable and contextual human brain research and advanced brain-computer interface applications.
13	Auditory brainstem response (ABR) audiometry system	Auditory brainstem response (ABR) audiometry is a neurologic test of auditory brainstem function in response to auditory (click) stimuli, which is the most common application of auditory evoked responses. ABR audiometry refers to an evoked potential generated by a brief click or tone pip transmitted from an acoustic transducer in the form of an insert earphone or headphone. The elicited waveform response is measured by surface electrodes typically placed at the vertex of the scalp and ear lobes. It features high performance amplifiers specifically designed to obtain high quality evoked potentials signals. With 14 bit averages, the BERAGRAPH can measure an objective auditory threshold with accuracy greater than 5 db and distinguish end cochlear deafness from retrocochlear deafness. The auditory stimulator gives burst, login and click stimulation presented either in condensation, refraction or alternating from 0 db to 120 db. The masking intensity can be controlled automatically with the stimulating intensity while maintaining the same programmed difference.
14	Delsys Wireless EMG System	Freely record and measure electrical activity produced by muscles, using wireless EMG sensors. Wireless EMG is useful for a wide range of applications within exercise physiology like track & field and gymnastics, studying motor control for patient rehabilitation or muscle performance, activity, and fatigue in elite athletes, measure electrical muscle activity.
15	FLIR E5 Thermal Imaging Camera	This is a real-time working 10,800 (120 × 90) pixel infrared resolution, focus-free camera. Provides thermal images along with accurate temperature measurements. The FLIR E5 is a powerful thermal imaging tool for troubleshooting electrical, mechanical, and building problems. Find hidden issues quickly, easily, and safely–without the need for direct contact with equipment.
16	SENSEnuts	SENSEnuts uniquely offers full technology stack with application layer, wireless network & cloud connectivity protocols for rapid IoT prototyping and also end to end vertical applications. It is Microcontroller with integrated 802.15.4 transceiver and variety of sensors like Environment, Meteorological, Air & water quality etc. It also has features like modular design having Gateways, Radios & sensors devices. It is easy to use because of C based programming, exhaustive set of “easy to use” APIs, flexible MAC protocol implementation, live data Interface with MATLAB etc. It has many advanced features to offer like energy efficient individual StreetLight Controllers which enable remote On/Off switching, dimming control, User configurable time scheduling & grouping schemes, Current/power consumption tracking of luminaire, Alerts for outage & malfunction, connectivity to Local or Cloud Server for data access and management and interfaces for Sensors like Motion detection, Pollution, light etc.
17	Material Chemistry & Synthesis Laboratory	The laboratory is equipped with all the basic and modern infrastructural facilities like fume hood, spot extractors, magnetic stirrers, ultrasonic processor, hot air ovens, distilled water setup, microwave, vacuum furnace, for enabling academic and research activities. The preparation of a variety of nanomaterials for gas-sensing, materials for battery and super capacitors, can be achieved here.
18	Field Emission Scanning Electron Microscope (FE-SEM) with EDAX module	The equipment is highly useful for viewing the shape, size, texture and elemental composition of materials at micro and nano scale those that cannot be observed by the unaided eye. One of the most important characterization technique for studying, the morphology of materials at the micro/nano scale, EDAX is used for determining the elemental composition of the materials.
19	Electrochemical Workstation	This instrument is used for carrying out electrochemical energy storage, heavy metal ion detection, and catalysis related researches. Application areas include battery, supercapacitors, corrosion, etc.
20	Impedance Analyser	Useful for studying the electrical impedance in materials. Characterization of fuel cells, photovoltaic cells, batteries and other electrochemical devices.
21	Voyager Cyber city Simulator Hardware Modules For Cyber Simulator(smart TV LED,Dell Power Edge R230 with 19.5 screen Dell optiplex 7050with 19.5 screen)	Cyber city simulator at Centre for Advanced studies is the facility for automated modelling and monitoring of cyber security threats at smart city environments. It displays status for cyber security threats on roads, power station, airport, metro rail, automobiles etc. It has state of the art tools and equipment for smart city projection. The objectives of this lab are to design and create attack plan methodologies, to understand social engineering aspects used for attacks, to get an insight into enterprise security trend, to use latest techniques to hack into systems and networks, to conduct regular audits and penetration test in your company, to support legal team with Digital forensic evidence, to support compliance roadmaps based on standards for your organization, to support Internal Audit teams for IT security compliance.
22	Solar Simulator	Solar simulator is a device for simulating natural sunlight in laboratory conditions. Used for the preparation and testing of solar cells and modules.
23	Hp z238 Microtower Workstations in Google Developers Code	This lab is constructed with an objective to replicate coding experience at Google. The specifications of the installed computers are i5 processor, 8GB RAM, and virtualisation technology enabled, Windows 10 operating system, good internet speed, and double monitors. The lab also comprises separate discussion areas for groups to interact, clear doubts and network among themselves. Google Developers Code Lab is the result of collaboration between the Centre for Advanced Studies and Google Asia Pacific Pvt. Ltd. This lab is sponsored by Google and is first of its kind in the country. As a result of the collaboration, Google organises numerous courses with well-defined curriculum, expected learning outcomes, and guidelines for lab exercises, using the lab facility for the students, faculty and staff of the University. The lab also facilitates learning through development of advanced technologies, friendly environment for discussions among peers, networking among the research groups of the University.

S. No.	Name of the Faculty / Email- ID	Area of Specialization	Research Problems
1	Prof. M. K. Dutta mkd@cas.res.in	Machine Learning and Deep learning, Deep Learning in Biological and Medical Applications, Computer Vision & Pattern Recognition, Bio-Medical Signal Processing, Multimedia Signal Processing, Audio Signal processing	1. Development of deep learning architectures and their optimisation. 2. Applications of Machine Learning / Deep Learning in Biological and Medical Applications 3. AI based Computer vision systems. 4. Biomedical Signal analysis using AI: Heart Sounds/Lung Sounds/ ECG /EEG /EMG 5. Time series analysis using AI 6. AI based assistive devices for Navigation for Visually Impaired People
2	Dr. Anuj Kumar Sharma anujksharma@cas.res.in	Soft robotics, Bio Inspired robotics, Metal cutting operations, Electrical discharge machining, Machining tribology, MQL Machining, Nano-cutting fluids, Thermocouples for machining	1. Generation of machined surface with improved surface quality using mono/hybrid nanoparticle based cutting fluids in Turning operation 2. Generation of machined surface with improved surface quality using mono/hybrid nanoparticle based cutting fluids in Milling operation 3. Metallic additive manufacturing using robotic manipulator 4. Design and development of robotic fish for data collection in a water body 5. Development of Bio inspired sensors for robot navigation and communication.
3	Dr. Rabesh Kumar Singh rabeshkumarsingh@cas.res.in	Additive Manufacturing, Metal cutting operations, Die-sink EDM Tribology of machining, Machining with MQL Nano-cutting fluids, Sensors for measurement of Temperature and Cutting forces in metal removal processes, Cutting speed controller for turning operation	1. To investigate the effect of MQL parameters (shape, size and distribution) on machining performance: A experimental and modelling approach 2. Investigation on the effect of different unit cells and infill structures on 3D printed parts 3. Thermal modelling of geometry of single track deposition in metal arc additive manufacturing systems 4. Development of a hybrid approach for 3D printed parts using friction stir welding and milling operation
4	Dr. Saurabh Mishra saurabhm@cas.res.in	Nanotechnology in Oil Industry	1. Fabrication of nano-porous structures for saving environment from oil spill 2. Application of nanotechnology in enhanced oil recovery 3. Utilization of digital techniques like artificial intelligence (AI), machine learning (ML), & deep learning (DL) in oil spill detection and monitoring 4. Application of digital platform in oil exploration and production problems
5	Dr. Vrinda Yadav vrinda@cas.res.in	Machine Learning and Deep Learning, Applications of Machine Learning / Deep Learning in Software Engineering, Applications of Software Engineering in Machine Learning	1. Summarizing source code for comprehension and maintenance using AI 2. AI assisted code search 3. Generating commit messages for source code changes automatically 4. Deep learning based code smell detection
6	Dr. Gopal Ji gopalji@cas.res.in	Corrosion Prevention of Metals using waste materials, Metal Matrix composites and Thin Film coatings, Wear prevention of metals, Bio-Sensors	1. Use of waste natural materials in corrosion prevention of metals 2. Thin film produced by floating film transfer method (FFTM) for corrosion prevention 3. Investigation of corrosion and tribological behaviour of various protective coatings/polymer composites 4. Image based corrosion detection using machine learning principles 5. Biosensors for technical applications
7	Dr. Arun Kumar drarun@cas.res.in	Cloud Computing, Applications of Machine Learning / Deep Learning, Cybersecurity, Network Security, IOT	1. User authentication in the blockchain using Machine Learning Techniques 2. ML/AI based Security models for cloud computing and the Internet of Things 3. Network attacks and anomaly detection using deep learning 4. Memory forensics using deep learning
8	Dr. A.V. Ullas avullas@cas.res.in	Polymer Composites	1. Development of light-weight materials for construction applications 2. Development of energy/shock absorbing materials for defence applications 3. Preparation and characterization of antimicrobial films for food packaging 4. Preparation and characterization of self-healing polymer materials
9	Dr. Anamika Jain anamika@cas.res.in	Machine Learning/ Deep Learning, Biometrics, Behavioral Biometrics, Image Processing & Pattern Recognition, Watermarking	1. One-shot Verification method for offline signatures 2. Verification of the signature without being trained on forged samples 3. Deep analysis of deep, shallow and traditional features of signature images 4. End-to-End Multimodal biometric authentication
10	Dr. Biswajit Mandal biswajit@cas.res.in	Electrochemical Energy Storage and Ion Sensing	1. Development of bio-mass derived carbon materials for electrochemical energy storage application 2. Development of metal oxide hybrids for increasing the energy density of pseudo supercapacitors 3. Synthesis of novel ternary oxides as an alternative to Li-ion batteries 4. Development of cheap electrochemical sensors for Arsenic (As (III)) detection in ground water
11	Dr. Pushpendra Singh Rathore pushpendra@cas.res.in	Thermal Energy Storage	1. Synthesis and Characterization of thermal Energy Storage materials 2. Design, Development and analysis of energy efficient building envelope 3. Integration of Thermal Energy Storage Systems in HVAC 4. Development of Solar Thermal Desalination system for water purification
12	Dr. Jitendra Kumar jitendra.kumar@cas.res.in	Motion planning of biped robot on uneven terrain, Humanoid robots kinematics and dynamics, Dynamics of multibody systems, Machines and mechanisms, Intelligent application of robotic system to solve industrial problem, Machine learning	1. Learning-based energy optimal motion planning of a 34-DOF humanoid robot on uneven ground 2. Motion planning of humanoid robots in a microgravity environment 3. Energy optimal path generation of redundant robotic manipulators in unstructured environments 4. Energy optimal gait synthesis of biped robots on different types of uneven terrain 5. To study the bilaterally symmetric body plan of walking robots (biped, quadrupeds, etc) and its influence on learning-based energy optimal gait planning of these robots
13	Dr. Chandresh Kumar Rastogi chandresh@cas.res.in	Nanomaterials synthesis and characterization	1. Synthesis and characterization of fluorescent nanomaterials for light emitting diodes and display applications 2. Development of nearinfrared activated nanomaterials for anti-counterfeiting applications 3. Development of fluorescent materials for temperature sensing applications 4. Preparation and characterization of nanomaterials for energy storage devices
14	Dr. Gyan Prakash Maurya gyan@cas.res.in	Electrocatalysis and photo-electrocatalysis	1. Kinetics analysis of electrocatalyst for oxygen evolution reaction (OER) and Hydrogen evolution reaction (HER) for hydrogen production via electrochemical water splitting reaction with the help of the Impedance analysis 2. Effect of the surface states present at the semiconductor catalyst surface for photoelectrochemical (PEC) water splitting with the help of impedance analysis and density functional theory (DFT) calculations 3. Li ion battery modelling for Solid electrolyte interface (SEI) layer 4. Activity enhancement of Supercapacitor material via various physicochemical methods 5. Electrocatalysis for Carbon dioxide (CO₂) reduction for useful fuels like ethanol and methanol 6. Corrosion protection by electrochemical machining

Description
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Research & Innovation

Publications by Faculty Members/Students

Conference Proceedings/ Book Chapters

Patents and Intellectual Properties

Student Innovation Gallery

Funded Research Projects by Faculty Members

Student Innovations

RESEARCH GROUP MEETINGS & SEMINARS ORGANIZED BY RESEARCH GROUPS

RESEARCH WEBINAR SERIES

Expert Talks

Prof. Radim Burget

Signal Processing Laboratory. Department of Telecommunications, Brno University of Technology. Brno, Czech Republic, European Union

Prof. Carlos M. Travieso-Gonzalez

Head of Signals and Communications Department Institute for Technological Development and Innovation in Communications (IDeTIC) University of Las Palmas de Gran Canaria (ULPGC), Spain.

Prof. Rossi Setchi

Director of Research Centre in AI, Robotics and Human-Machine Systems (IROHMS) Deputy Head of School, Director of Research, Cardiff School of Engineering, Cardiff University, United Kingdom.

Prof. Sabah A. Jassim

Professor of Mathematics and Computation School of Computing, University of Buckingham,Buckingham MK18 1EG, United Kingdom.

Prof. Hao Ying

IEEE Fellow, Professor, Department of Electrical and Computer Engineering Wayne State University, Detroit, Michigan 48202, USA

Prof. Aleksandar Poleksic

Department of Computer Science University of Northern Iowa, USA

Prof. Cesare Alippi

Professor (Information Processing Systems) Professor with the Politecnico di Milano, Milano, Italy and Università della Svizzera Italiana, Lugano, Switzerland.

Prof. Tarek El-Ghazawi

ECE Professor and Director Institute for Massively Parallel Applications and Computing Technology (IMPACT)The George Washington University, USA

Prof. Jean-Pierre Leburton

ECE Professor and Director Gregory Stillman Professor of Electrical and Computer Engineering,University of Illinois at Urbana-Champaign, USA.

Prof. Dr. Peter Peer

Vice-Dean Faculty of Computer & Information Science Computer Vision Lab University of Ljubljana, Slovenia, European Union.

Prof. Stephen Pistorius

Professor & Associate Head: Medical Physics (Physics & Astronomy) Professor (Radiology) Vice Director & Graduate Chair: Biomedical Engineering Graduate Program University of Manitoba, Canada.

Prof. Viera Rozinajova

Institute of Informatics, Information Systems and Software Engineering (FIIT) Vice-dean - Faculty of Informatics and Information Technologies Slovak University of Technology, Bratislava, European Union

Prof. Pierre Maréchal

Institut de Mathématiques de Toulouse Université Paul Sabatier Toulouse, France.

Prof. Nong Ye

Director, Information and Systems Assurance Laboratory Ira A. Fulton School of Engineering Arizona State University, USA.

Prof. Gordon B. Agnew

Dept. of Electrical and Computer Engineering University of Waterloo, Canada.

Professor Jason Crain

IBM Research United Kingdom & Visiting Professor, University of Oxford United Kingdom

Prof. Sokrates T. Pantelides

University Distinguished Professor of Physics and Engineering William A. and Nancy F. McMinn Professor of Physics and Professor of Electrical Engineering, Vanderbilt University, USA. Distinguished Visiting Scientist, Oak Ridge National Laboratory, USA

Prof. Vaidy Sunderam

Samuel Candler Dobbs Professor of Computer Science Chair, Department of Mathematics and Computer Science, Director, Computational and Life Sciences Strategic Initiative, Emory University, Atlanta, USA.

Prof. Khan M. Iftekharuddin

Associate Dean for Research and Graduate Programs, Director, Vision Lab. Batten College of Engineering and Technology Old Dominion University, USA

Prof. Doan B Hoang

School of Electrical and Data Engineering Faculty of Engineering and Information Technology. University of Technology Sydney, Australia.

Prof. Jont Allen

Dept. of Electrical and Computer Engineering, University of Illinois at Urbana Champaign, USA

Prof. Theda Daniels-Race

M. B. Voorhies Distinguished Professor, School of Electrical Engineering and Computer Science and the LSU Center for Computation and Technology (CCT), Louisiana State University, USA

Prof. Hamid Vakilzadian

Department of ECE, University of Nebraska-Lincoln, USA

Prof. Alan Sprague

Electrical and Computer Engineering University of Alabama at Birmingham, Birmingham, United Kingdom.

Prof. Martin Fabian

Dept. of Electrical engineering Chalmers University of Technology, Gothenburg, Sweden

Prof. Fred Choobineh

Blackman Distinguished Professor of College of Engineering. Dept. of Electrical and Computer Engineering, University of Nebraska-Lincoln, USA.

Prof. Suresh Subramaniam

Professor and Chair Department of Electrical and Computer Engineering George Washington University, Washington DC, USA

Prof. Anna Soffía Hauksdóttir

Professor, Department of Electrical and Computer Engineering Engineering and Physical Sciences University of Iceland Reykjavík, Iceland

Prof. Israel Koren

Dept. of Electrical and Computer Engineering University of Massachusetts, USA

Prof. Jason O'Kane

Director, Center for Computational Robotics, Department of Computer Science and Engineering University of South Carolina, USA.

Prof. Xenofon Koutsoukos

Associate Chair, Department of Electrical Engineering and Computer Science Vanderbilt University, USA.

Prof. Peter Puschner

Institute of Computer Engineering Technische Universitaet Wien Vienna, Austria

Prof. Ilangko Balasingham

Department of Electronic Systems Norwegian University of Science and Technology (NTNU) Trondheim, Norway.

Prof. Raquel Diaz-Sprague

Electrical and Computing Engineering, University of Alabama at Birmingham, Birmingham Alabama 35205, USA

Prof. Gregor Rozinaj

Faculty of Electrical Engineering and Information Technology Institute of Multimedia ICT Slovak University of Technology, Bratislava, Slovakia, European Union.