Computer Science and Engineering Program

Computer Science Engineering (CSE) is an academic program that integrates the field of Computer Engineering and Computer Science. It is one of the most sought after courses amongst engineering students. The course contains a plethora of topics but emphasizes the basics of computer programming and networking. It is a course that deals with design, implementation, and management of information systems of both software & hardware processes. A computer scientist specializes in theory of computation and design of computational systems.

M.Tech. Computer Science and Engineering

M.Tech in Computer Science and Engineering is one of the first programs offered at Centre for Advanced Studies. The vision of the program is to be recognised globally as centre of excellence for postgraduate studies as well as research and development with an aim to create professionals that can match the demand of the present IT industry by developing experts with a focus on enhancing their technical capabilities, research profile, and soft skills The department of Computer Science and Engineering promotes research and innovations in the areas of Artificial Intelligence/ Machine Learning/ Deep learning/ Cyber Security/ and ICT. The curriculum is a mixture of the conventional and revolutionary concepts and is updated regularly to keep up with the increasing demands and the trends of the research laboratories and organizations. The program is AICTE approved and currently offers 18 seats per academic year with specialization of
1. Machine Learning
The programme introduces the foundation and working of machine learning and Artificial intelligent systems. It enhances the students’ knowledge on design, development and testing of various machine learning algorithms and systems using industry standard tools. It is structured in such a way that the students will be able to build intelligent systems and evaluate machine learning algorithms for domain specific applications.
2. Cyber Security
Cyber Security programme offers an advanced study on Cybersecurity methodologies and their applications in real-world scenarios. The students are exposed to the advanced tools and technologies used to secure web communication, management of cyber threats and more.
3. ICT (Information and Communication Technologies)
This programme explores how information and communication technologies may be managed, and how they may serve the purposes of management. The aim of the programme is to develop critical and reflective awareness in relation to the state-of-the-art in the value and use of Information and Communication Technologies (ICTs) in business organizations. The course helps to meet the increasing need for professionals who would be able to respond to the convergence between computers and communication. Course introduces rigorous mathematical concepts in linear systems and signals theory.


1. Opportunity to study in a Government research driven institute having world class infrastructure including
 • 5 petaflops supercomputing faculty facility with DGX servers, the world's best quality Artificial Intelligence lab
 • Google Developers Code lab, sponsored by Google and is first of its kind in the country
 • Cybercity Simulator lab equipped with state of the art tools and equipment for smart city environments
 • Internet of Things lab
2. Highly qualified and experienced faculty
3. Focus on cutting edge research on a rich variety of topics like Artificial Intelligence, Machine Learning, Data Analytics, Cyber security, and many more core/ interdisciplinary areas
4. Industry oriented hands on training in the world class research labs
5. Recognition for meritorious students who perform exceptional in academic and research work
6. Opportunity to work in DST funded research projects in cutting edge technology
7. Conference travel support to present research work in National and International conferences
8. Access to e-resources is available through digital library
9. Regular updates in curriculum to keep up with the increasing demands of the focus research areas
10. Choice based specialisation in Artificial Intelligence, Cyber security, ICT

Labs and Equipments

1. Artificial Intelligence Lab

An Artificial Intelligence (AI) Lab with high-performance Graphics Processing Units (GPU) server is set up at Centre for Advanced Studies, Dr.A.P.J.Abdul Kalam Technical University, Lucknow, for enabling academic & research institutions for high-class research, course/project work, job-oriented hands-on training in the area of artificial intelligence with a focus on deep learning, machine learning, data science and analytics. This artificial intelligence lab is one of the few state-of-the-art labs in India and first in Uttar Pradesh, having this massive computing facility. It is 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 major objective of development of this lab is to enable the Institute to offer the very best education, training and research facility in Artificial Intelligence powered by GPUs for AI with focus on deep learning, machine learning, data science and analytics. 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 increases in performance for scientific, data analytics, engineering, consumer, and enterprise applications.
Objective of the AI Lab:
1. Identify innovative research directions in Artificial Intelligence, Deep Learning, Machine Learning, and Big Data analytics.
2. Encouraging students to publish research articles, patents and starting their start-ups in the campus/university.
3. Integrating and reasoning with information from disparate data sources by training students, developers, data scientists, and researchers.
4. Designing and implementing distributed systems for information exploitation, collaboration and decision making.
5. Data-intensive agent-based tools providing quality education and practical skills to the students and faculty.
6. Assist in the development of partnerships with Industry regarding Internships, Summer Jobs, Publications and students’ placements.
7. Establish, refine and implement strategies to take the idea in to students and faculty fraternity.

Google Developers Code Lab

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 organizes 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, adding academic value to the Institute and the University.
Google Developers Code Lab is constructed with an objective to replicate coding experience at Google. The specifications of the installed computers are i5 processor, 8GB RAM, virtualization 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.
Objectives of the Lab
•To organize short term courses, workshops and trainings offered by Google to the students, faculty, and staff of the University.
•To educate about recent products and services offered by Google to the research community of the University.
•To train and provide hands-on experience on Google developer tools and technologies.
•To expose the students, faculty and staff of the University with the Google communities for interactions and collaboration.
•To advance knowledge of the faculty of the University impacting education of the students with latest developments in technology.

Cyber city simulator Lab

Cyber city simulator at Centre for Advanced studies is the facility for automated modeling 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.
Objectives of the Lab
• Design and create attack plan methodologies
• Understand social engineering aspects used for attacks
• Get an insight into enterprise security trend
• Use latest techniques to hack into systems and networks
• Conduct regular audits and penetration test in your company
• Support legal team with Digital forensic evidence
• Support compliance roadmaps based on standards for your organization
• Support Internal Audit teams for IT security compliance

Research Areas
• Ethical Hacking Methodology
• Hacking Networks & Systems
• Web Application Security
• Denial of Services
• Social Engineering
• IoT Basics
• A few case studies
• Introduction to CyberCity
• IoT Security Challenges
• IoT Authentication & Authorization
• IoT Data Integrity & Standards
• Emerging IoT Technologies & Trends
• Data Security & Cryptography
• IoT Communication Protocol Vulnerabilities
• IoT Vulnerabilities & Attacks
• IoT Exploitation Framework
• An approach towards IoT security
• Introduction to IoT Security Framework & Benchmarks

Internet of Things (IoT) Lab

The IoT Lab is based on SENSEnuts technology that 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 Self-healing multi-hop network, easy to install and faster deployment It gives affordable solution for WSN concept testing and learning. 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.
Objectives and Applications:
An ideal platform for research projects. It has many advanced features to offer like energy efficient individual Street Light 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 finally interfaces for Sensors like Motion detection, Pollution, light etc.

Artificial Intelligence in Biomedical Lab

The Artificial Intelligence in Biomedical Laboratory focuses on development intelligent AI devices and expert systems to analyze diverse biomedical signals and data towards establishing mathematical relation with various diseases and disorders. Signal processing and analysis using both traditional machine learning and deep learning methods are intended at provide individualized biomarkers for precision diagnosis and predictive modelling. Machine learning is also in wearable device analytics to aid clinicians in the treatment of mobility disorders, as well as improving the health outcomes using A for individuals suffering from diseases and efforts are also going on to improve measures of clinical outcomes to justify therapeutic interventions. The main goal of the lab is to develop artificial intelligence techniques to assist clinical decision making, avoid medical errors and ultimately improve patient health. Some key directions of interest include: Wearables and system development, Clinical outcomes research, Diagnostic Assistance, Clinical Event Forecasting, Patient-centric Information Retrieval Human Computation, and many more.
Research Areas
a) Marker less Motion capture system (2-D Gait Analysis System) with Force plate
b) Human Non-invasive Blood Pressure (NIBP) Monitor
c) Equi-vital Physiological Monitoring System
d) Auditory brainstem response (ABR) audiometry system
e) Electronic Stethoscope for PCG signal
f) EMOTIV EPOC+ 14 Channel Mobile EEG
g) EMOTIV 32 Channel EEG cap
h) Delsys Wireless EMG System
Faculty Details
Prof. M. K. Dutta

Prof. M. K. Dutta is a Professor of Computer Science & Engineering in Centre for Advanced Studies. Currently he is also in the Position of Director of Centre for Advanced Studies and Dean PG studies and Research in Dr. A.P.J.Abdul Kalam Technical University, Lucknow, India. His research interest include Machine Learning and Deep learning, Applications of Machine Learning/Deep Learning in Biological and Medical Applications, Image Processing, Computer Vision, Pattern Recognition, Bio-Medical Signal Processing applications, Multimedia Signal Processing and Audio Signal processing. He has strong international cooperation with scientist from USA, UK, Canada, Australia, Spain, Czech Republic, Korea, Costa Rica, Germany, Spain, Republic of Macedonia, Taiwan, China and have co-authored many research articles with them. Professor Dutta has co-authored 295 + indexed research papers in reputed international journals and conferences. He was involved as Principal investigator for 6 funded research projects and also has filed 10 Patents for his inventions. He has guided 5 PhD students (and 6 ongoing) and 21 M.Tech Dissertations. He was Conference Chair of two prestigious IEEE sponsored International conferences and he is in the reviewer panel and editorial panel of many prestigious journals. He has contributed through innovative work for the welfare of the society using the technological interventions which has huge societal benefit. ... Some of his important contribution was use of Artificial intelligence in clinical problems like automatic identification of retinal diseases digital fundus image, Classification of trabecular bone structure of Osteoporotic Patients from X-ray images using Machine Learning. He has also developed methods to identify major cardiac and pulmonary diseases using machine learning applications in body auscultation signals. He has important contributions in Artificial intelligence applications in contemporary biological applications like to identify the presence of cancer causing elements like acrylamide in Carbohydrate content food i.e. potato chips using computer vision and machine learning. His another notable contribution was to identify from fish images the freshness and also if the fish was exposed to toxic substances like pesticides and heavy metals like mercury. Other contribution of Prof Dutta was to find the effect of EMF radiation from mobile phones and cell towers on the human brain using computer vision and machine learning. A significant contribution was for the pandemic COVID-19, in which a machine learning model is designed for the classification of COVID patient and non COVID patients using chest X-ray images. Other philanthropic work Prof Dutta is involved in is to develop an “Assistive device to impart perceptual ability to visually impaired using intelligent scene captioning” in which an assistive device is designed using deep learning to recognize the objects which are highly relevant for visually impaired person.

Funded Projects

Sr. No.

Title of Project

Funding Agency

Name of PI/ Co-PI

Amount ₹ Lakh / Duration



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)

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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)

2 years

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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)

3 years

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Research Problems:
1. Development of deep learning architectures and their optimization.
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

Dr. Vrinda Yadav

Dr. Vrinda Yadav completed Ph.D. in 2019 from IITB-Monash Research Academy, that offers joint Ph.D. between Indian Institute of Technology Bombay and Monash University Australia. Her Ph.D. thesis was on Evolution Traceability of Business Process Models, jointly supervised by Prof. Rushikesh K. Joshi (Department of Computer Science and Engineering, IIT Bombay), and Dr. Chris Ling (Faculty of Information Technology, Monash University). Her Ph.D. was sponsored by Infosys Limited Bangalore. During her Ph.D., she worked at both IIT Bombay as well as Caulfield campus of Monash University, and she also did research as an Intern at Infosys Labs Bangalore. She completed M.Tech. in 2014 from International Institute of Information Technology Bangalore. During her M.Tech., she did research as an Intern at Accenture Technology Labs. She completed her B.Tech. in 2012 in Computer Science and Engineering from University Institute of Engineering and Technology, CSJM University Kanpur
Her research areas includes: Machine Learning and Deep Learning, Applications of Machine Learning /Deep Learning in Software Engineering, Applications of Software Engineering in Machine Learning, MLOps, Blockchain
Research Problems:
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. 4. Deep learning based code smell detection

Dr. Arun Kumar

Dr. Arun Kumar is working as Assistant Professor in Computer Science and Engineering Department of Centre for Advanced Studied Lucknow. He received his M.Tech and PhD in Computer Science from Jawaharlal Nehru University New Delhi, India. He is a reviewer of International refereed journals of repute including IEEE, Inderscience, IGI Global, and various international conferences.
His research areas includes: Cloud Computing, Applications of Machine Learning / Deep Learning, IOT, Wireless network, Multimedia, information security, Cyber Security, etc.
Research Problems:
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

Dr. Anamika Jain

Dr. Anamika Jain is an Assistant Professor in the department of Computer Science and Engineering. She has done her Ph.D. from the Indian Institute of Information Technology Allahabad (IIIT-A) in the Information Technology department. Her thesis deals with the problems in the field of offline signature verification. She published her research work in various SCI/SCIE journals. During her tenure at IIIT-Allahabad, she has served as an active member in IEEE student committees and organized many IEEE workshops, Conferences. She received her M.Tech and B.E. from MANIT Bhopal and NRIIIST Bhopal, Respectively.
Her research areas includes: Deep Leaning, Machine Learning, Image Processing, Biometrics, Watermarking, etc.
Research Problems:
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