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Author Information
Anca Dragan (UC Berkeley)
Karen Levy (Cornell University)
Himabindu Lakkaraju (Harvard)
Hima Lakkaraju is an Assistant Professor at Harvard University focusing on explainability, fairness, and robustness of machine learning models. She has also been working with various domain experts in criminal justice and healthcare to understand the real world implications of explainable and fair ML. Hima has recently been named one of the 35 innovators under 35 by MIT Tech Review, and has received best paper awards at SIAM International Conference on Data Mining (SDM) and INFORMS. She has given invited workshop talks at ICML, NeurIPS, AAAI, and CVPR, and her research has also been covered by various popular media outlets including the New York Times, MIT Tech Review, TIME, and Forbes. For more information, please visit: https://himalakkaraju.github.io/
Ariel Rosenfeld (Bar-Ilan University)
Maithra Raghu (Google Brain)
Irene Y Chen (MIT)
Irene is a PhD student at MIT focusing on applications on health care and fairness. She did her undergrad at Harvard where I studied applied math and computational engineering. Before starting at MIT, she worked for two years at Dropbox as a data scientist and machine learning engineer.
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2021 : B-Pref: Benchmarking Preference-Based Reinforcement Learning »
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2021 Spotlight: Pragmatic Image Compression for Human-in-the-Loop Decision-Making »
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2021 : Poster: The Many Roles that Causal Reasoning Plays in Reasoning about Fairness in Machine Learning »
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2022 : Time-Efficient Reward Learning via Visually Assisted Cluster Ranking »
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2022 : Optimal Behavior Prior: Data-Efficient Human Models for Improved Human-AI Collaboration »
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2022 : Aligning Robot Representations with Humans »
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2022 : A Human-Centric Take on Model Monitoring »
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2022 Workshop: 5th Robot Learning Workshop: Trustworthy Robotics »
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2022 : Anca Dragan: Learning human preferences from language »
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2022 Poster: First Contact: Unsupervised Human-Machine Co-Adaptation via Mutual Information Maximization »
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2022 Poster: Uni[MASK]: Unified Inference in Sequential Decision Problems »
Micah Carroll · Orr Paradise · Jessy Lin · Raluca Georgescu · Mingfei Sun · David Bignell · Stephanie Milani · Katja Hofmann · Matthew Hausknecht · Anca Dragan · Sam Devlin -
2022 Poster: Learning to Reason with Neural Networks: Generalization, Unseen Data and Boolean Measures »
Emmanuel Abbe · Samy Bengio · Elisabetta Cornacchia · Jon Kleinberg · Aryo Lotfi · Maithra Raghu · Chiyuan Zhang -
2022 : Invited talk (Dr Hima Lakkaraju) - "A Brief History of Explainable AI: From Simple Rules to Large Pretrained Models" »
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2021 : Q/A Session »
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2021 : [IT3] Towards Reliable and Robust Model Explanations »
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2021 : The Many Roles that Causal Reasoning Plays in Reasoning about Fairness in Machine Learning »
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2021 : Invited Talk: Towards Reliable and Robust Model Explanations »
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2021 : BASALT: A MineRL Competition on Solving Human-Judged Task + Q&A »
Rohin Shah · Cody Wild · Steven Wang · Neel Alex · Brandon Houghton · William Guss · Sharada Mohanty · Stephanie Milani · Nicholay Topin · Pieter Abbeel · Stuart Russell · Anca Dragan -
2021 Poster: Pragmatic Image Compression for Human-in-the-Loop Decision-Making »
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2021 Poster: Do Vision Transformers See Like Convolutional Neural Networks? »
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2020 : Keynote: Anca Dragan »
Anca Dragan -
2020 : Mini-panel discussion 3 - Prioritizing Real World RL Challenges »
Chelsea Finn · Thomas Dietterich · Angela Schoellig · Anca Dragan · Anusha Nagabandi · Doina Precup -
2020 Workshop: Machine Learning for Health (ML4H): Advancing Healthcare for All »
Stephanie Hyland · Allen Schmaltz · Charles Onu · Ehi Nosakhare · Emily Alsentzer · Irene Y Chen · Matthew McDermott · Subhrajit Roy · Benjamin Akera · Dani Kiyasseh · Fabian Falck · Griffin Adams · Ioana Bica · Oliver J Bear Don't Walk IV · Suproteem Sarkar · Stephen Pfohl · Andrew Beam · Brett Beaulieu-Jones · Danielle Belgrave · Tristan Naumann -
2020 Poster: Incorporating Interpretable Output Constraints in Bayesian Neural Networks »
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2020 Spotlight: Incorporating Interpretable Output Constraints in Bayesian Neural Networks »
Wanqian Yang · Lars Lorch · Moritz Graule · Himabindu Lakkaraju · Finale Doshi-Velez -
2020 : Q&A for invited speaker, Anca Dragan »
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2020 : Getting human-robot interaction strategies to emerge from first principles »
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2020 Poster: AvE: Assistance via Empowerment »
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2020 Tutorial: (Track2) Explaining Machine Learning Predictions: State-of-the-art, Challenges, and Opportunities Q&A »
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2020 Poster: Reward-rational (implicit) choice: A unifying formalism for reward learning »
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2020 Poster: Preference learning along multiple criteria: A game-theoretic perspective »
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2020 Poster: Beyond Individualized Recourse: Interpretable and Interactive Summaries of Actionable Recourses »
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2020 Tutorial: (Track2) Explaining Machine Learning Predictions: State-of-the-art, Challenges, and Opportunities »
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2019 : Coffee Break and Poster Session »
Rameswar Panda · Prasanna Sattigeri · Kush Varshney · Karthikeyan Natesan Ramamurthy · Harvineet Singh · Vishwali Mhasawade · Shalmali Joshi · Laleh Seyyed-Kalantari · Matthew McDermott · Gal Yona · James Atwood · Hansa Srinivasan · Yonatan Halpern · D. Sculley · Behrouz Babaki · Margarida Carvalho · Josie Williams · Narges Razavian · Haoran Zhang · Amy Lu · Irene Y Chen · Xiaojie Mao · Angela Zhou · Nathan Kallus -
2019 Workshop: Machine Learning for Autonomous Driving »
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2019 Workshop: Fair ML in Healthcare »
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2019 : Poster Session I »
Shuangjia Zheng · Arnav Kapur · Umar Asif · Eyal Rozenberg · Cyprien Gilet · Oleksii Sidorov · Yogesh Kumar · Tom Van Steenkiste · William Boag · David Ouyang · Paul Jaeger · Sheng Liu · Aparna Balagopalan · Deepta Rajan · Marta Skreta · Nikhil Pattisapu · Jann Goschenhofer · Viraj Prabhu · Di Jin · Laura-Jayne Gardiner · Irene Li · sriram kumar · Qiyuan Hu · Mehul Motani · Justin Lovelace · Usman Roshan · Lucy Lu Wang · Ilya Valmianski · Hyeonwoo Lee · Sunil Mallya · Elias Chaibub Neto · Jonas Kemp · Marie Charpignon · Amber Nigam · Wei-Hung Weng · Sabri Boughorbel · Alexis Bellot · Lovedeep Gondara · Haoran Zhang · Taha Bahadori · John Zech · Rulin Shao · Edward Choi · Laleh Seyyed-Kalantari · Emily Aiken · Ioana Bica · Yiqiu Shen · Kieran Chin-Cheong · Subhrajit Roy · Ioana Baldini · So Yeon Min · Dirk Deschrijver · Pekka Marttinen · Damian Pascual Ortiz · Supriya Nagesh · Niklas Rindtorff · Andriy Mulyar · Katharina Hoebel · Martha Shaka · Pierre Machart · Leon Gatys · Nathan Ng · Matthias Hüser · Devin Taylor · Dennis Barbour · Natalia Martinez · Clara McCreery · Benjamin Eyre · Vivek Natarajan · Ren Yi · Ruibin Ma · Chirag Nagpal · Nan Du · Chufan Gao · Anup Tuladhar · Sam Shleifer · Jason Ren · Pouria Mashouri · Ming Yang Lu · Farideh Bagherzadeh-Khiabani · Olivia Choudhury · Maithra Raghu · Scott Fleming · Mika Jain · GUO YANG · Alena Harley · Stephen Pfohl · Elisabeth Rumetshofer · Alex Fedorov · Saloni Dash · Jacob Pfau · Sabina Tomkins · Colin Targonski · Michael Brudno · Xinyu Li · Yiyang Yu · Nisarg Patel -
2019 : Spotlight Paper Talks »
Arnav Kapur · Maithra Raghu · Xinyu Li -
2019 Workshop: Machine Learning for Health (ML4H): What makes machine learning in medicine different? »
Andrew Beam · Tristan Naumann · Brett Beaulieu-Jones · Irene Y Chen · Madalina Fiterau · Samuel Finlayson · Emily Alsentzer · Adrian Dalca · Matthew McDermott -
2019 Poster: Transfusion: Understanding Transfer Learning for Medical Imaging »
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2019 Poster: On the Utility of Learning about Humans for Human-AI Coordination »
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2018 : Anca Dragan »
Anca Dragan -
2018 : Poster Session I »
Aniruddh Raghu · Daniel Jarrett · Kathleen Lewis · Elias Chaibub Neto · Nicholas Mastronarde · Shazia Akbar · Chun-Hung Chao · Henghui Zhu · Seth Stafford · Luna Zhang · Jen-Tang Lu · Changhee Lee · Adityanarayanan Radhakrishnan · Fabian Falck · Liyue Shen · Daniel Neil · Yusuf Roohani · Aparna Balagopalan · Brett Marinelli · Hagai Rossman · Sven Giesselbach · Jose Javier Gonzalez Ortiz · Edward De Brouwer · Byung-Hoon Kim · Rafid Mahmood · Tzu Ming Hsu · Antonio Ribeiro · Rumi Chunara · Agni Orfanoudaki · Kristen Severson · Mingjie Mai · Sonali Parbhoo · Albert Haque · Viraj Prabhu · Di Jin · Alena Harley · Geoffroy Dubourg-Felonneau · Xiaodan Hu · Maithra Raghu · Jonathan Warrell · Nelson Johansen · Wenyuan Li · Marko Järvenpää · Satya Narayan Shukla · Sarah Tan · Vincent Fortuin · Beau Norgeot · Yi-Te Hsu · Joel H Saltz · Veronica Tozzo · Andrew Miller · Guillaume Ausset · Azin Asgarian · Francesco Paolo Casale · Antoine Neuraz · Bhanu Pratap Singh Rawat · Turgay Ayer · Xinyu Li · Mehul Motani · Nathaniel Braman · Laetitia M Shao · Adrian Dalca · Hyunkwang Lee · Emma Pierson · Sandesh Ghimire · Yuji Kawai · Owen Lahav · Anna Goldenberg · Denny Wu · Pavitra Krishnaswamy · Colin Pawlowski · Arijit Ukil · Yuhui Zhang -
2018 : Opening Remark »
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2018 Workshop: Machine Learning for Health (ML4H): Moving beyond supervised learning in healthcare »
Andrew Beam · Tristan Naumann · Marzyeh Ghassemi · Matthew McDermott · Madalina Fiterau · Irene Y Chen · Brett Beaulieu-Jones · Michael Hughes · Farah Shamout · Corey Chivers · Jaz Kandola · Alexandre Yahi · Samuel Finlayson · Bruno Jedynak · Peter Schulam · Natalia Antropova · Jason Fries · Adrian Dalca · Irene Chen -
2018 Workshop: NIPS Workshop on Machine Learning for Intelligent Transportation Systems 2018 »
Li Erran Li · Anca Dragan · Juan Carlos Niebles · Silvio Savarese -
2018 : Anca Dragan »
Anca Dragan -
2018 Poster: Insights on representational similarity in neural networks with canonical correlation »
Ari Morcos · Maithra Raghu · Samy Bengio -
2018 Poster: Where Do You Think You're Going?: Inferring Beliefs about Dynamics from Behavior »
Sid Reddy · Anca Dragan · Sergey Levine -
2017 : Morning panel discussion »
Jürgen Schmidhuber · Noah Goodman · Anca Dragan · Pushmeet Kohli · Dhruv Batra -
2017 : "Communication via Physical Action" »
Anca Dragan -
2017 Workshop: 2017 NIPS Workshop on Machine Learning for Intelligent Transportation Systems »
Li Erran Li · Anca Dragan · Juan Carlos Niebles · Silvio Savarese -
2017 Workshop: Deep Learning: Bridging Theory and Practice »
Sanjeev Arora · Maithra Raghu · Russ Salakhutdinov · Ludwig Schmidt · Oriol Vinyals -
2017 : Invited talk: Robot Transparency as Optimal Control »
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2017 Poster: SVCCA: Singular Vector Canonical Correlation Analysis for Deep Learning Dynamics and Interpretability »
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2016 : Learning Reliable Objectives »
Anca Dragan -
2016 : Invited Talk: Autonomous Cars that Coordinate with People (Anca Dragan, Berkeley) »
Anca Dragan -
2016 Poster: Exponential expressivity in deep neural networks through transient chaos »
Ben Poole · Subhaneil Lahiri · Maithra Raghu · Jascha Sohl-Dickstein · Surya Ganguli -
2016 Poster: Cooperative Inverse Reinforcement Learning »
Dylan Hadfield-Menell · Stuart J Russell · Pieter Abbeel · Anca Dragan