Nikhil Behari

I am a Research Fellow at the Harvard School of Engineering and Applied Sciences in the Center for Research on Computation and Society advised by Prof. Milind Tambe, and a Research Affiliate at the MIT Media Lab in the Camera Culture Group led by Prof. Ramesh Raskar.

My research interests include 3D scene representation, reinforcement learning techniques, and optimization for decision-making under uncertainty, especially applied to human and planetary health. Currently, at Harvard, I am collaborating with researchers at Google Research and DeepMind on enhancing the generalizability of models for complex resource allocation problems. Previously, at the MIT Media Lab, I researched topics in automated imaging system design and scene representation using non-standard cues.

I received my Bachelor of Arts in Computer Science and Statistics from Harvard College in 2022. I was previously an intern at the NASA Langley Research Center with Dr. Corey Ippolito, and at the CMU Future Interfaces Group with Prof. Chris Harrison. I also previously co-organized the KDD Workshop on Data-Drive Humanitarian Mapping, and am currently a Non-Resident Tutor for Harvard's Mather House.

Email  /  Google Scholar  /  Github

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DISeR: Designing Imaging Systems with Reinforcement Learning
Tzofi Klinghoffer*, Kushagra Tiwary*, Nikhil Behari, Bhavya Agrawalla, Ramesh Raskar
In International Conference on Computer Vision (ICCV), October 2023
project page / paper
Find Rhinos without Finding Rhinos
Lucia Gordon, Nikhil Behari, Samuel Collier, Elizabeth Bondi-Kelly, Jackson A. Killian, Catherine Ressijac, Peter Boucher, Andrew Davies, Milind Tambe
In International Joint Conference on Artificial Intelligence (IJCAI) AI for Good, August 2023
ORCA: Glossy Objects as Radiance Field Cameras
Kushagra Tiwary*, Akshat Dave*, Nikhil Behari, Tzofi Klinghoffer, Ashok Veeraraghavan, Ramesh Raskar
In Computer Vision and Pattern Recognition Conference (CVPR), June 2023
project page / paper / mit news article
Data-driven Humanitarian Mapping and Policymaking: Toward Planetary-Scale Resilience, Equity, and Sustainability
Snehalkumar ‘Neil’ Gaikwad, Shankar Iyer, Dalton Lunga, Takahiro Yabe, Xiaofan Liang, Bhavani Ananthabhotla, Nikhil Behari, Sreelekha Guggilam, Guanghua Chi
In Knowledge Discovery and Data Mining (KDD), August 2022
workshop page / paper
A Framework for Rapid Active Learning in Resource-Constrained Environmental Sensing Domains
Nikhil Behari
Senior Thesis, Harvard College, May 2022
Micronutrient Deficiency Prediction via Publicly Available Satellite Imagery
Elizabeth Bondi, Haipeng Chen, Christopher Golden, Nikhil Behari, Milind Tambe
In Innovative Applications of Artificial Intelligence (IAAI-22), February 2022
journal article / paper
Using Public Data to Predict Demand for Mobile Health Clinics
Haipeng Chen, Susobhan Ghosh, Gregory Fan, Nikhil Behari, Arpita Biswas, Mollie Williams, Nancy E. Oriol, Milind Tambe
In Innovative Applications of Artificial Intelligence (IAAI-22), February 2022
Contextual Segmentation of Fire Spotting Regions Through Satellite-Augmented Autonomous Modular Sensor Imagery
Nikhil Behari, Henry Holbrook, Paris Garrett, Corey Ippolito, Chester Dolph
In American Institute of Aeronautics and Astronautics (AIAA) Scitech, January 2022
Improving Aircraft Trajectory Classification
Henry Holbrook, Paris Garrett, Nikhil Behari, Chester Dolph, Christopher Morris, George Szatkowski
In American Institute of Aeronautics and Astronautics (AIAA) Scitech, January 2022
Representative Travel Time Mapping: Highlighting Transportation-Based Citywide Inequities in Hospital Access
Nikhil Behari
In Knowledge Discovery and Data Mining (KDD) Workshop on Data-driven Humanitarian Mapping, August 2021
Satellite-Based Food Market Detection for Micronutrient Deficiency Prediction
Nikhil Behari, Elizabeth Bondi, Christopher D. Golden, Hervet J. Randriamady, Milind Tambe
In AAAI Workshop on Health Intelligence (W3PHIAI-21), February 2021
Changing Allegiance: Insider Threat and Inadvertent Leaks
Kathleen Carley, Geoffrey Morgan, Nikhil Behari, Neal Altman, Andrew Moore
In International Sunbelt Social Network Conference, April 2016