Brian Hsu

According to our database, Brian Hsu authored at least 12 papers between 2013 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

BioAlchemy: Distilling Biological Literature into Reasoning-Ready Reinforcement Learning Training Data.

Brian Hsu, Ozan Gökdemir, Carlo Siebenschuh, Bruce D. Parrello, Neil Getty, Thomas S. Brettin, Rick L. Stevens, Ian T. Foster, Nicholas Chia, Arvind Ramanathan

CoRR, April, 2026

PRISM: Protocol Refinement through Intelligent Simulation Modeling.

Brian Hsu, Priyanka Setty, Rory Butler, Ryan Lewis, Casey Stone, Rebecca Weinberg, Thomas S. Brettin, Rick L. Stevens, Ian T. Foster, Arvind Ramanathan

CoRR, January, 2026

2025

HiPerRAG: High-Performance Retrieval Augmented Generation for Scientific Insights.

Ozan Gökdemir, Carlo Siebenschuh, Alexander Brace, Azton Wells, Brian Hsu, Kyle Hippe, Priyanka Vasanthakumari, Aswathy Ajith, J. Gregory Pauloski, Varuni Katti Sastry, Sam Foreman, Huihuo Zheng, Heng Ma, Bharat Kale, Nicholas Chia, Thomas Gibbs, Michael E. Papka, Thomas S. Brettin, Francis J. Alexander, Anima Anandkumar, Ian T. Foster, Rick Stevens, Venkatram Vishwanath, Arvind Ramanathan

CoRR, May, 2025

HiPerRAG: High-Performance Retrieval Augmented Generation for Scientific Insights.

Ozan Gökdemir, Carlo Siebenschuh, Alexander Brace, Azton Wells, Brian Hsu, Kyle Hippe, Priyanka Setty, Aswathy Ajith, J. Gregory Pauloski, Varuni Sastry, Sam Foreman, Huihuo Zheng, Heng Ma, Bharat Kale, Nicholas Chia, Thomas Gibbs, Michael E. Papka, Thomas S. Brettin, Francis J. Alexander, Anima Anandkumar, Ian T. Foster, Rick Stevens, Venkatram Vishwanath, Arvind Ramanathan

Proceedings of the Platform for Advanced Scientific Computing Conference, 2025

2024

From Models to Systems: A Comprehensive Fairness Framework for Compositional Recommender Systems.

Brian Hsu, Cyrus DiCiccio, Natesh Sivasubramoniapillai, Hongseok Namkoong

CoRR, 2024

From Models to Systems: A Comprehensive Framework for AI System Fairness in Compositional Recommender Systems.

Brian Hsu, Cyrus DiCiccio, Natesh S. Pillai, Hongseok Namkoong

Proceedings of the Workshop on Algorithmic Fairness Through the Lens of Metrics and Evaluation, 2024

2023

An Operational Perspective to Fairness Interventions: Where and How to Intervene.

Brian Hsu, Xiaotong Chen, Ying Han, Hongseok Namkoong, Kinjal Basu

CoRR, 2023

Detection and Mitigation of Algorithmic Bias via Predictive Parity.

Cyrus DiCiccio, Brian Hsu, YinYin Yu, Preetam Nandy, Kinjal Basu

Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, 2023

Disentangling and Operationalizing AI Fairness at LinkedIn.

Joaquin Quiñonero Candela, Yuwen Wu, Brian Hsu, Sakshi Jain, Jennifer Ramos, Jon Adams, Robert Hallman, Kinjal Basu

Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, 2023

2022

Pushing the limits of fairness impossibility: Who's the fairest of them all?

Brian Hsu, Rahul Mazumder, Preetam Nandy, Kinjal Basu

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2020

Implementing a More Challenging Parsons Problem Interface for Teaching Computer Science.

Nathaniel Weinman, Brian Hsu, Alexia Camacho

Proceedings of the 51st ACM Technical Symposium on Computer Science Education, 2020

2013

A tactile vision substitution system for the study of active sensing.

Brian Hsu, Cheng-Han Hsieh, Sung-Nien Yu, Ehud Ahissar, Amos Arieli, Yael Zilbershtain-Kra

Proceedings of the 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2013