Happiness is when what you think, what you say, and what you do are in harmony.
-- Mahatma Gandhi

  Homepage of Prof. Mausam  
Professor, Jai Gupta Chair
Department of Computer Science and Engineering
Room 402, School of IT Building
Indian Institute of Technology Delhi
Hauz Khas, New Delhi, 110016, India
Email: mausam AT cse DOT iitd DOT ac DOT in,
Phone : +91-11-2659-6076 (O)
School of Artificial Intelligence (ScAI)
Indian Institute of Technology Delhi
Hauz Khas, New Delhi, 110016, India
Email: hodscai AT admin DOT iitd DOT ac DOT in
Affiliate Faculty
Department of Computer Science and Engineering
University of Washington
Seattle, Washington, 98195, U.S.A.
Email: mausam AT cs DOT washington DOT edu
Phone : +1-206-979-7038 (C)
Picture of Mausam

I am looking for technically strong and ambitious PhD students interested in artificial intelligence (neuro-symbolic machine learning, intelligent information systems, natural language processing, and NLP for robotics). Please contact me if you are one of them. I am also interested in industry related problems that can be solved using NLP techniques. Contact me if you think you have an interesting problem. I am not looking for winter/summer interns or students for short-term (less than a year) projects. Please do not contact me with such requests. I am unable to respond to them personally.

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, and two best paper awards. 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 and a B.Tech. from IIT Delhi in 2001.

In Mar'21 I gave bites to a Times of India article on natural language processing.
Proud to be a program co-chair of AAAI 2021 with Kevin Leyton-Brown.
ArnetMiner believes that I am the 65th most influential AI scholar and 71st most influential NLP scholar for the decade 2009-2019. Not sure I deserve to be in this list of greats, but happy to receive the honor, nonetheless!
In Oct'20 I was one of the panelists for Doordarshan program on AI and roadmap.
In Oct'20 I was one of the panelists for a Rajya Sabha TV program on AI for social empowerment.
In Mar'20 I gave bites to a Mail Today article on AI education in India.
Starting Jan'20, I taught an NPTEL (public) undergraduate course on artificial intelligence. It reruns starting Jan'21.
In Jan'20 I was one of the panelists for a Rajya Sabha TV program on regulating AI.
In Oct'19 I was one of the panelists for a Rajya Sabha TV program on AI.
In Jun'19 I gave bites to an Economics Times article on AI and India.
In Jun'19 I was one of the panelists for a DD Science program on AI in Hindi.
In Feb'19, I received the Jai Gupta Chair fellowship by IIT Delhi.
In Feb'19 I was interviewed by Factor Daily. The transcript of the interview.
In Oct'18 I was honored to participate in a Niti Aayog panel on AI in front of esteemed audience comprising the PM, council of ministers, heads of PSUs and senior bureaucrats in the Govt of India.
In Oct'18 I was interviewed as one of the experts for a Lok Sabha TV program on AI (in Hindi).
In Sep'18 I was interviewed as one of the experts for Rajya Sabha TV features on AI: the video in English and the video in Hindi.
In Aug'18 I gave bites to an India Today article on the future of AI.
In Jan'18 I recorded a public talk on Artificial Intelligence: Past, Present and Future and a Student Q&A session for Living Science.
In Jun'17 I was a Program co-chair for the 27th International Conference on Automated Planning and Scheduling in Pittsburgh.
In Jul'16 I was invited to deliver a talk in the Early Career Spotlight Track at IJCAI'16 in New York.
In Jul'16 our STARAI'16 paper titled Contextual Symmetries in Probabilistic Graphical Models received the best paper award.
In Jun'16 I was elected as a councilor to AAAI Executive Council for a three year term.
In Apr'16 I was awarded a Young Faculty Research Fellowship under the Visvesvaraya PhD scheme for Electronics & IT by Govt. of India.
In Apr'16 I was interviewed by ML India. The transcript of the interview.
In Jan'15 at AAAI'15, I was awarded the AAAI Senior status, a distinction in the field of artificial intelligence.
In Jan'15 I was awarded a Teaching Excellence Award for my Spring 2014's AI course.
In Sep'14 I appeared on NDTV Profit to defend Artificial Intelligence at a debate show titled, The Contrarian.
In Nov'13 at HCOMP, our paper titled Crowdsourcing Multi-Label Classification for Taxonomy Creation received the best paper award.
In Oct'13 I joined as a faculty member at IIT Delhi after a six year research faculty stint at University of Washington, Seattle.
In Jul'12 Andrey Kolobov and I released a monograph titled Planning with Markov Decision Processes: An AI Perspective.
In Sep'08 I was awarded an honorable mention for the 2008 ICAPS best disseration award.
In Oct'07 I joined University of Washington as a Research Assistant Professor.
In Aug'07 I completed my PhD thesis on stochastic planning with concurrent, durative actions.

At present I am working on the following projects:
  • Neuro-Symbolic AI: Neural models have become the model of choice for almost all machine learning applications, such as NLP, computer vision, and speech. However, previous generation (symbolic) models, based on logic or probabilistic representations can combine with neural models to achieve further progress. In this research, we explore the value(s) of symbolic constraints, intermediate representations, and algorithms offer in a neural setting. We develop LIFT, which shows that a symbolic inference algorithm can help train a neural model faster. In our NeurIPS'19 paper, we demonstrate how (and why) to use symbolic constraints while training a neural model for several NLP applications. Our recent ICLR paper trains neural models for constrained satisfaction problems like Sudoku.

  • Neural Models for Probabilistic Planning: Neural models for reinforcement learning problems have achieve tremendous recent success. In this project, we study whether they can also be helpful for (Relational) Markov Decision Processes (MDPs) that are expressed in a declarative logic-based representation such as RDDL. We have written a series of papers on this topic and are excited at reviving research thread of Relational MDPs using modern neural models. In our first paper (NeurIPS'18), we show that neural models trained on a few instances of a domain can be effectively transferred to a new instance of the same domain of the same size. We extend this to transfer across problem sizes in a restricted setting and in a full blown RMDP setting (ICML'20).

  • Open Information Extraction: We hope to overcome the "knowledge-acquisition bottleneck" by automatically extracting information from natural language text in a domain-independent manner. We work on improving the quality of Open IE extractors by pushing their precision and recall. We recently released the code for IMoJIE and Open IE 6, neural Open IE extractors, with state of the art results. Our previous Open IE extractor (Open IE 5) is publicly released with over 5,000 downloads. Other progress on this work includes a better handling of compound noun expressions, numerical facts and lists of facts in a sentence. We also release an evaluation framework and dataset for better evaluation of Open IE systems (paper). I wrote short survey on the vast literature on Open IE.

  • Inference over Knowledge-Bases: Knowledge-bases are always incomplete! We develop novel inference algorithms for the task of knowledge-base completion. Our joint matrix-tensor factorization model mitigates the issues with matrix factorization for this task. Our type-sensitive model adds unsupervised typing to tensor factorization to obtain state of the art results on several datasets. We also release the code that implements these and many other models. More recent work proposes TimePlex, a KB completion model for Temporal Knowledge Bases. It also proposes new evaluation protocols for this important task.

  • Task-oriented Dialog Systems: We study end-to-end trainable dialog systems, which are targeted towards a certain goal, such as answering customer questions. Often, these require interaction with knowledge sources, such as a knowledge-base. In BossNet (code), we show an effective way to disentangle language and knowledge when training such systems end-to-end. CDNet improves upon by adding a constrained KB-distillation layer, leading to a much better identification of appropriate entities for an utterance. An extension of RL enables training dialog systems even in absence of KB-query annotation.

  • Machine Learning for Medical Imaging: An IITD-AIIMS partnership studies computer vision over histopathological images of duodenal biopsies for Celiac disease prediction. The goal is to build a medically-explainable AI system that collaborates with physicians for best predictions.

In my personal time, I can be found listening to, playing, or singing hindustani classical music. I have got the fortune of accompanying several famed vocalists on harmonium, including Pt. Vidyadhar Vyas, Vidushi Sunanda Patnaik, Us. Mashkoor Ali Khan, Smt. Bharathi Prathap, and my dear wife, Shashwati Mandal. In my previous life, I performed with a Seattle light Indian music band called Pratidhwani (my last show was Kashish in December 2012). Even before that, I was involved with Seattle's local cricket tournament where I tried my fingers at off-spinning. World cinema and cooking were my other favorite pastimes.