Summer Seminar Series

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Seminar Recordings

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Picture of Unnat Jain

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Unnat Jain

Presenting July 10, 2020 @ 11:00 am MDT
Venue: Zoom Video Call - Subscribe to our Mailing List to receive the link via email
Title: Collaborative Embodied Agents . Click here for more info.

Unnat is a Ph.D. student in Computer Science at UIUC working with Alex Schwing and Svetlana Lazebnik. Within computer vision and machine learning, he is currently looking into developing communicative embodied agents and interpreting their communication. He spent summers at Allen Institute for AI and Facebook AI Research as a research intern.

Previously, he completed his MS in Computer Science at UIUC with the best thesis award and featured in the Siebel Scholars Class of 2018. Prior to joining Illinois, Unnat graduated with the Director’s Gold Medal from the Indian Institute of Technology, Kanpur. He was also awarded the Cadence Gold Medal for the best research thesis across all engineering departments. Learn more about Unnat at https://unnat.github.io/.


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Shruti Rijhwani

Presenting July 2, 2020 @ 3:00 pm MDT
Venue: Zoom Video Call - Subscribe to our Mailing List to receive the link via email
Title: Entity Linking for Low-Resource Languages . Click here for more info.

Shruti Rijhwani is a PhD student at Carnegie Mellon University. Her primary research interest is multilingual natural language processing, with a focus on low-resource and endangered languages. Her research is supported by a Bloomberg Data Science Ph.D. Fellowship. Much of her published work focuses on improving named entity recognition and entity linking for low-resource languages and domains.


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Sambaran Bandyopadhyay

Presenting June 26, 2020 @ 12:00 pm MDT
Venue: Zoom Video Call - Subscribe to our Mailing List to receive the link via email
Title: Graph Representation Learning in the Presence of Outliers. Click here for more info.

Sambaran Bandyopadhyay is an Advisory Research Engineer at IBM Research, India. He is also a final year PhD student at the department of Computer Science and Automation at Indian Institute of Science, Bangalore. Sambaran has published his research works in top tier AI conferences such as AAAI, IJCAI, KDD, WSDM, ICAPS, ECAI etc. and also has 8 patents filed to USPTO. He has been a member of the technical program committee of several AI conferences such as NeurIPS, ICML, AAAI, ECML-PKDD, etc.


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Ayan Mukhopadhyay

Presenting June 19, 2020 @ 11:30 am MDT
Venue: Zoom Video Call - Subscribe to our Mailing List to receive the link via email
Title: Robust Incident Forecasting and Response. Click here for more info.

Ayan Mukhopadhyay is a Post-Doctoral Research Fellow at the Stanford Intelligent Systems Lab at Stanford University, USA. His research interests include multi-agent systems, robust machine learning and decision-making under uncertainty. He was awarded the 2019 CARS post-doctoral fellowship by the Center of Automotive Research at Stanford (CARS). Before joining Stanford, he finished his PhD at Vanderbilt University’s Computational Economics Research Lab. His doctoral thesis was nominated for the Victor Lesser Distinguished Dissertation Award 2020. His work on urban emergency response management has been covered in the Government Technology Magazine, Financial Times, multiple global smart city summits, and received a best paper award at ICLR’s AI for Social Good Workshop.


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Arpita Biswas

Presenting June 12, 2020 @ 11:30 am MDT
Venue: Zoom Video Call - Subscribe to our Mailing List to receive the link via email
Title: Two-Sided Fairness Guarantees for Recommendation Systems (arXiv). Click here for more info.

Arpita Biswas is a Google Ph.D. Fellow at the Department of Computer Science and Automation, Indian Institute of Science. Her broad areas of interest include Game Theory, Optimization, and Machine Learning. She is presently looking at problems in Computational Social Choice Theory and Fairness in Machine Learning. Prior to her Ph.D., she worked as a Research Engineer at Xerox Research Centre India. Her work spans several research spaces such as multi-agent learning, incentive mechanisms, facility location, planning and scheduling, etc. Thus far, she has worked on problems arising from real-world scenarios like online crowd-sourcing, resource allocation, dynamic pricing in transportation, and ride-sharing. More details about her can be obtained at https://sites.google.com/view/arpitabiswas/.


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Eunice Jun

Presenting May 29, 2020 @ 12:00 pm MDT
Venue: Zoom Video Call - Subscribe to our Mailing List to receive the link via email
Title: Tea: A High-level Language and Runtime System for Automating Statistical Analysis. Click here for more info.

Eunice Jun is a PhD student in the Paul G. Allen School of Computer Science & Engineering at the University of Washington. Her research focuses on developing new tools and methods for conducting valid and reproducible statistical analyses. She hopes to make conducting valid data analyses easy (and fun) for end-users. She incorporates methods and techniques from human-computer interaction, programming languages, software engineering, and data science. Her work has been supported by a UW CSE Wilma Bradley Fellowship and an NSF Graduate Research Fellowship.


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Anirbit Mukherjee

Presenting May 21, 2020 @ 12:00 pm MDT
Venue: Zoom Video Call - Subscribe to our Mailing List to receive the link via email
Title: Understanding training of depth 2 nets under minimal distributional assumptions and data poisoning attacks. Click here for more info.

Anirbit, is a (final) year Ph.D. student in applied mathematics at the Johns Hopkins University advised by Prof. Amitabh Basu. He specializes in deep-learning theory and has been awarded 2 fellowships from JHU for this research, "Walter L.Robb Fellowship" and the inaugural "Mathematical Institute for Data Science Fellowship." Earlier, he was a researcher in Quantum Field Theory, while doing his undergrad in physics at the Chennai Mathematical Institute (CMI) and masters in theoretical physics at the Tata Institute of Fundamental Research (TIFR). For more details, you can visit his website.


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Nitish Gupta

Presenting May 14, 2020 @ 12:00 pm MDT
Venue: Zoom Video Call - Subscribe to our Mailing List to receive the link via email
Title: Neural Module Networks for Reasoning over Text. Click here for more info.

Nitish is a senior PhD student in Computer Science at the University of Pennsylvania pursuing research in NLP. He is advised by Prof. Dan Roth and co-advised by Prof. Sameer Singh, UCI. Nitish's research focuses on developing structured models for grounded language understanding, primarily in the context of making machines understand and answer questions against text. He is particularly interested in models that perform reasoning by understanding the compositional nature of language, and are able to provide a formal semantic parse and an explanation about their predictions. For more details you can visit https://nitishgupta.github.io/.