About Me š
I am a PhD student at Harvard under the mentorship of Dr. Flavio du Pin Calmon and Dr. Hima Lakkaraju and am supported by the NSF Graduate Student Research Fellowship.
I am broadly interested in fair, interpretable, and trustworthy machine learning, and my current projects apply information theoretic tools to problems in fairness and representation learning. Although I love digging into theory, I am an engineer by training and hope to use my research to design actionable solutions for society.
Outside of the lab, you can find me playing jazz guitar šø, volleyball š (Iām a middle blocker!), or playing board games with my friends.
Publications āļø
Multi-Group Proportional Representation
NeurIPS 2024
Operationalizing the Blueprint for an AI Bill of Rights: Recommendations for Practitioners, Researchers, and Policy Makers
Under Review.
Interpreting CLIP with Sparse Linear Concept Embeddings (SpLiCE šŖ¢)
Usha Bhalla*,
NeurIPS 2024
Fair Machine Unlearning: Mitigating Disparities during Data Deletion
AISTATS 2024
Integrated single-cell multiomic analysis of HIV latency reversal reveals novel regulators of viral reactivation
Ashokkumar Manickam, Jackson J Peterson, Yuriko Harigaya, David M Murdoch, David M Margolis,
bioRxiv
Integrated single-cell multiomic profiling of HIV latency reversal
Ashokkumar Manickam, Jackson J Peterson, Wei Mei, David M Murdoch, David M Margolis,
Journal of Virus Eradication, 2022
Distributionally Robust Group Backwards Compatibility
Martin Bertran, Natalia Martinez,
NeurIPS DistShift Workshop, 2021
Multitask Learning for Citation Purpose Classification
NAACL 2nd Workshop on Scholarly Document Processing, 2021
Detecting Motion in a Room Using a Dynamic Metasurface Antenna
IEEE Access, 2020
aoesterling [at] g [dot] harvard [dot] edu
google scholar
curriculum vitae