I heard that IIT Madras has a new BTech program in Artificial Intelligence and Data Analytics. Is it true? Can I know more about the department, the curriculum, and the facilities?

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Wed, 27 Mar 2024 07:20:48 +0000
Departments

IIT Madras is all set to welcome its 18th department - the Department of Data Science and Artificial Intelligence (DSAI), formerly known as the Wadhwani School of Artificial Intelligence. It is one of the first departments to offer a BTech program in Artificial Intelligence and Data Analytics (AIDA) from the older IITs. The department will commence its operations in 2024 after completing all administrative procedures.

Program, Curriculum, and Courses

The DSAI department at IIT Madras will stand out as the best place to build a strong foundation in the field of Artificial Intelligence. It is currently poised to offer the following programs:

B.Tech in Artificial Intelligence and Data Analytics (AIDA)

M.Tech in Data Science and AI

Joint MSc with the University of Birmingham

I2MP in Data Science

Interdisciplinary Dual Degree in Data Science

M.S & Ph.D

Considering the expanding scope of Data Science and AI, there are a large number of courses that will be included in the curriculum, covering every aspect of the field. These courses provide strong mathematical and foundational training, with a focus on important areas emphasizing machine learning, deep learning, and reinforcement learning, alongside their applications in various domains.

The curriculum is highly flexible —as all undergraduate curricula at IIT Madras are—supported by a large basket of electives and various options for minor programs. Some key core courses in the curriculum include:

Machine Learning | Data Curation and Visualization
Artificial Intelligence | language Technologies
Deep Learning | Mathematical Modelling and Simulation

Several necessary lab courses will also be covered such as the Machine Learning Lab, Artificial Intelligence Lab, Machine Learning Operations Lab, and the Deep Learning Lab.

The curriculum will feature strong interdisciplinary elements, integrating several application courses, including Data Science for Physics, Chemistry, and Biology. Additionally, multiple elective courses are to be included to address key and emerging applications of Data Analytics & AI.

Scope to learn Mathematics: The curriculum is designed to encompass courses that cater to mathematical foundations and theoretical aspects. At the same time, there will be a significant emphasis on essential domains and applications. Students with an aptitude for mathematics will find the course appealing due to an increased focus on the theoretical aspects.

Research, Facilities, and Industrial Collaborations

The department is already home to some well-funded centers such as the Robert Bosch Centre for Data Science and Artificial Intelligence (RBCDSAI), the Centre for Integrative Biology and Systems Medicine (IBSE), and the Centre for Responsible AI (CeRAI). The department is expected to have significant funding from the Artificial Intelligence and Data Science industry with excellent infrastructure. There will be a dedicated space for the department, with state-of-the-art facilities for computational labs, including high-end GPU systems.

The students of the department will be encouraged to involve themselves and be a part of the ongoing research in data science & AI. The AI club at CFI takes up projects spanning various domains, with an opportunity for students from any branch to learn and apply AI. The scope for research in DSAI at IITM is very broad and encompasses several key theoretical areas and important domain areas such as healthcare, smart cities, transportation, manufacturing, finance, etc.

Google Research, Apple, Meta, Walmart, Pfizer, Saint Gobain Research, Hindustan Unilever Limited, Dassault Aviation, Tiger Analytics, MaxLinear, IIS, etc. are some of the organizations that have collaborated with the department for R&D. The list of companies in the future is expected to increase, providing students excellent opportunities to indulge themselves in research activities.

Why is there a different department for AI and CS? Which is better for BTech students?

Over the years, the broad area of computer science has expanded in many different directions. At IIT Madras, the research areas for the CSE department span vast domains like computer systems (including VLSI), theoretical computer science, and human-computer interactions. The explosive rise of research and job opportunities in AI and Data Science in the last decade has made it obvious that there should be a dedicated department for this field with its own vision and team.

While a few may overlap, most of the courses offered by the two departments will be different. Students who study these courses might apply for different jobs and research opportunities.

Students applying to either department should consider their core interest areas. Both departments offer very interesting courses that open up research opportunities and are gateways to lucrative jobs. We expect students from these departments to be equally impactful in their careers after graduation.

Who are some of the top Professors in the Department of DSAI at IIT Madras?

1. Balaraman Ravindran: Currently, the head of the Department of DSAI and previously for the Robert Bosch Centre for Data Science & Artificial Intelligence (RBDSAI) and Centre for Responsible AI (CeRAI) at IIT Madras, Professor B. Ravindran is a leading Reinforcement Learning researcher and is among the top three Machine Learning experts in India. His research in the field has made a significant impact internationally and has laid the foundation for the ongoing works in the department at IIT Madras.

With over twenty years of expertise in AI and ML, specializing particularly in RL, he has published around 100 papers and journals and has been quoted in top publications such as MIT Technology Review, Harvard Business Review, and Forbes India. He is also known for establishing one of the most active deep learning groups in the country, resulting in several citations of their work. His lectures on NPTEL are highly popular among students and are known for their effective presentation. He is a recipient of numerous prestigious awards and has been serving on the Board of Studies at various colleges and universities in India.

Currently, his research interests are centered on learning from and through interactions and span the areas of geometric deep learning and reinforcement learning.

To know more about him, visit here.

2 .Raghunathan Rengaswamy: Professor Raghunathan Rengaswamy is an esteemed researcher who is renowned for his contributions in various fields within Process control and Chemical Engineering. His journey includes serving as an Assistant professor at IIT Bombay, and various other universities such as Clarkson University and Texas Tech University, where he co-directed the Process Control and Optimization Consortium (PCOC).

Professor Rengaswamy’s research interests span Fault Detection and Diagnosis (FDD), the development of Sensor Placement (SP) algorithms for FDD, Fuel Cells, and computational microfluidics. His work in computational microfluidics led to the establishment of SysEng LLC, a startup in the U.S. Furthermore, his collaboration with Professor Shankar Narasimhan from the Department of Chemical Engineering at IIT Madras resulted in the co-founding of Gyan Data Pvt. Ltd (GDPL), a high-technology service and product development company situated in the IIT Madras Research Park.

He has over 215 publications in various notable journals. A series of review articles on condition monitoring and fault detection and diagnosis, co-authored by Professor Rengaswamy, has amassed over 1400 citations, with a significant impact on the academic community. Currently working in the Department of DSAI, his focus includes Reinforcement Learning, Big Data Process Analytics, Machine Learning, and Big Data.

3. Arun Tangirala: With expertise spanning diverse domains of Process Systems Engineering and Applied Data Science, Dr. Arun K Tangirala has served as a professor in the Department of Chemical Engineering at IIT Madras since 2004. Prof. Tangirala has held esteemed Visiting Professorship positions at leading international institutions, including the University of Delaware, Technical University of Munich, and Tsinghua University. He has made substantial contributions to various fields, including engineering, biology, and climate sciences.

Throughout his illustrious career, he has not only excelled in teaching fundamental and advanced courses on process control, system identification, wavelet transforms, random processes, and fuel cell systems but has also been a recipient of prestigious teaching and research awards. Moreover, he has authored a comprehensive text, “Principles of System Identification,” which has become a standard reference worldwide for building data-driven models.

Prof. Tangirala is also the Editor-in-Chief of the Institution of Engineers India Journal: Series E and an Associate Editor for both the ASME Journal of Dynamical Systems, Measurements, and Control and the Control Engineering Practice Journal. In his current role as a professor in the Department of DSAI, he has made a significant impact on academia with a portfolio comprising over 80 publications. His research focuses on the intersection of Data Science and various domains such as process control and monitoring, system identification, and applied signal processing.

4. Karthik Raman: Professor Karthik Raman is a distinguished researcher with a detailed background in computational biology and systems sciences. Currently serving as a Professor in the Department of DS and AI, and previously in the Department of Biotechnology, IIT Madras, he has been a vital force in various roles since 2015. Proficient in computational modeling and simulation of biological systems, his expertise extends to microbiome systems biology, in silico metabolic engineering, and the design principles of biological networks.

He has represented IIT Madras in global forums, contributed to open-source drug discovery hackathons, and delivered impactful lectures at industries, engaging in national and international outreach activities. His academic contributions include over 50 publications across more than 35 esteemed journals. Prof. Raman is also dedicated to mentoring students, particularly in DNA computing. He co-founded and directs qBiome Research Private Limited, emphasizing his commitment to interdisciplinary research and its practical applications.

Currently immersed in the field of Data Science and Artificial Intelligence, Professor Raman is active in striking a fine balance between computational biology and AI.

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