Artificial Intelligence Summer School

(AISS 2022)

This three days summer school will be held at Indraprastha Institute of Information Technology, Delhi. Advancements in Artificial Intelligence are rapidly bringing new areas and techniques into prominence, each of which has potential to change the way we do things as well offer new solutions and insights to problems that confront us. This summer school will focus on developments in two specific topics of artificial intelligence (AI) – Explainable AI, and Neuro-symbolic AI. Explainable artificial intelligence (XAI) aims to answer the questions How? and Why? about AI systems. It has significant use cases in addressing the ethical and legal concerns. In essence, XAI research is a necessity for trustworthy AI. As a result, explainability in AI has experienced a recent surge in attention. Neuro-symbolic AI combines traditional symbolic AI approaches with modern deep learning techniques. Such models have capability to outperform state-of-the-art deep learning models in complex domains, using significantly less training data, yet achieving high accuracy. In addition there will be many talks and discussions which will be decided according to the participants' interests.


Dr. Chirag Agarwal

Adobe Research (Explainable AI)

Prof. V. Raghava Mutharaju

IIIT Delhi (Neuro-symbolic AI)

  • Dr. Chirag Agarwal, Adobe Research (Explainable AI): Dr. Chirag is a Research Scientist at Adobe and a Research Fellow at Harvard University working on developing trustworthy machine learning that go beyond training models for specific downstream tasks and ensure they satisfy other desirable properties, such as explainability, fairness, and robustness. He is one of the co-founders of the Trustworthy ML Initiative, a forum and seminar series related to Trustworthy ML, and an active member of the MLC research group that focuses on democratizing research by supporting open collaboration in machine learning (ML) research. He earned a Ph.D. in Electrical and Computer Engineering from University of Illinois at Chicago, USA, in 2020.
  • Prof. V. Raghava Mutharaju, IIIT Delhi (Neuro-symbolic AI): Dr. Raghava is an Assistant Professor at the Computer Science and Engineering department of IIIT-Delhi, India and leads the Knowledgeable Computing and Reasoning (KRaCR; pronounced as cracker) Lab. He has worked in Industry research labs such as GE Research, IBM Research, Bell Labs, and Xerox Research. His research interest is in Semantic Web and in general in Knowledge Representation and Reasoning. This includes knowledge graphs, ontology modeling, reasoning, querying, and its applications. He got his Ph.D. in Computer Science and Engineering from Wright State University, Dayton, OH, USA, in 2016.

Keynote Speakers

Prof. Mausam

IIT Delhi

Dr. Gautam Shroff


  • Prof. Mausam, IIT Delhi: Prof. Mausam is the founding head of School of Artificial Intelligence, along with being a Professor of Computer Science at IIT Delhi. He is also an affiliate professor at University of Washington, Seattle. With a twenty year research experience in artificial intelligence, he has, over time, contributed to many research areas such as large scale information extraction over the Web, AI approaches for optimizing crowdsourced workflows, and probabilistic planning algorithms. More recently, his research is exploring neuro-symbolic machine learning, computer vision for radiology, NLP for robotics, multilingual NLP, and several threads in intelligent information systems that include information extraction, knowledge base completion, question answering, summarization and dialogue systems. He has over 100 archival papers to his credit, along with a book, two best paper awards, and one test of time award. Mausam was awarded the AAAI Senior Member status in 2015 for his long-term participation in AAAI and distinction in the field of artificial intelligence. He has had the privilege of being a program chair for two top conferences, AAAI 2021, and ICAPS 2017. He was ranked the 56th most influential NLP scholar and 64th most influential AI scholar by ArnetMiner AI2000 Ranking. He received his PhD from University of Washington in 2007.
  • Dr. Gautam Shroff: Dr. Gautam Shroff is a Senior Vice President in TCS and heads TCS Research. He has published over 125 research papers in the areas of computational mathematics, parallel computation, distributed systems, software architecture, software engineering, big data, information fusion, virtual reality as well as artificial intelligence including machine learning, deep learning, and natural language processing. He has written two books “Enterprise Cloud Computing” published by Cambridge University Press, UK, in October 2010, and “The Intelligent Web”, published by Oxford University Press, UK, in 2013. He is a TCS Fellow as well as a Fellow of the Indian National Academy of Engineering. Prior to joining TCS in 1998, Dr. Shroff had been on the faculty of the California Institute of Technology, Pasadena, USA (1990 - 91) and thereafter of the Department of Computer Science and Engineering at Indian Institute of Technology, Delhi, India (1991 - 1997). He has also held visiting positions at NASA Ames Research Center in Mountain View, CA, and at Argonne National Labs in Chicago. He completed his B.Tech degree in Electrical Engineering from IIT Kanpur in 1985, and Ph.D in Computer Science from Rensselaer Polytechnic Institute Troy, NY in 1990.


The summer school is open to Researchers, Postdocs, Ph.D. students, Faculty, Industrial practitioners, M.Tech. students. B.Tech. students will also be selected.


Registration fee: The registration is free of cost.

Registration procedure: To attend the event you will need to necessarily register. Please register by filling up this form. There are only a limited number of places available in the summer school. Therefore, after registration if for any reason you decide not to attend the school, you will have to cancel your registration well in advance so that your place is offered to a wait-listed candidate.

Registration Deadline extented till August 15th, 2022

Call for Submission

Call for Research talks and Posters: The summer school will include short research talks and posters, in addition to the lectures and keynote talks. The research talks intend to provide a platform to researchers to discuss their recent and ongoing work and exchange new ideas related to artificial intelligence, machine learning, and related areas, with fellow researchers and potential collaborators. A speaker will have up to 20 minutes to give the talk that will include the discussion and interaction with the audience. Research talks may include ongoing or recently published work in the theory, design, implementation, analysis, or empirical evaluation and measurement of relevant algorithms and applications. Given a limited number of slots available for the research talks, work and ideas can also be presented as a poster at AISS 2022, for which the arrangements will be made, including the printing of the poster.

To present a research talk we invite an extended abstract of not more than a single page in a one column format. Typically, a submission should include a short abstract and some details of the work. A submission should be in ACM one column format using the template available here. There will be no formal published proceedings, however, the submitted short abstracts will be made available on the website of AISS 2022.

Research talks abstract submission deadline: July 31st, 2022 Extended till August 15, 2022

Research talks abstract submission procedure: Please send your submission to


To be updated.


To be updated.


Okhla Industrial Estate, Phase III
(Near Govind Puri Metro Station)
New Delhi, India - 110020

Supported by

AI Elsevier