Brandon Fain

Brandon Fain is an Assistant Professor of the Practice in the Department of Computer Science at Duke University's Trinity College of Arts & Sciences, where he has served since 2020 after previously holding an Assistant Research Professor position from 2019-2020. His academic home is firmly within computer science, with a focus on bridging theoretical computer science with practical, socially conscious applications. He teaches core algorithms and machine learning courses while maintaining an active research program that intersects computer science, economics, and ethics.

Dr. Fain received his educational training at Duke University, where he earned:

• Ph.D. in Computer Science (2019), with thesis "Algorithms for Public Decision Making" (winner of outstanding dissertation award)
• M.S. in Computer Science (2018)
• B.A. in Physics with double major in Mathematics and minor in Computer Science from Transylvania University (2014, Summa Cum Laude)

Dr. Fain's research focuses on developing algorithms that address fairness, ethics, and human compatibility in artificial intelligence systems. His work spans algorithmic fairness in multi-objective reinforcement learning, fair resource allocation, and ethical considerations in AI development. He approaches these challenges through the lens of computational economics, algorithmic game theory, and multi-agent systems, seeking to build AI that better aligns with human values and societal needs. His research is deeply motivated by a desire to create more humane algorithmic systems that can respond to complex human preferences in rigorous and equitable ways.

Analysis of Dr. Fain's publication record reveals a consistent focus on fairness in computational systems, with particular emphasis on multi-objective decision making and ethical considerations in AI. His recent work shows increasing sophistication in handling nonlinear preferences and uncertainty in reinforcement learning contexts. A notable trend is his growing interest in the intersection of algorithmic fairness with political and social applications, as evidenced by his work on gerrymandering detection and participatory budgeting. His publications consistently appear in top venues for AI, algorithms, and computational social choice.

Dr. Fain has received multiple teaching honors including:

• Top 5% Course Evaluations in Trinity College (Fall 2019)
• Dean's Award for Excellence in Teaching
• Certificate in College Teaching
• Preparing Future Faculty Fellowship
• Outstanding Ph.D. dissertation award (2019)

Dr. Fain is deeply committed to undergraduate research mentorship, having guided numerous students to publish in top computer science venues. His CS+ Summer Undergraduate Projects program provides Duke undergraduates with immersive research experiences. His current grant portfolio includes significant NSF funding:

• NSF INCLUDES Alliance: The Alliance for Identity-Inclusive Computing Education (2021-2027)
• CUE: Collaborative Research: Effective Peer Teaching Across Computing Pathways (2020-2023)

These grants reflect his commitment to broadening participation in computing and improving computer science education.

Dr. Fain directs the CS+ Summer Undergraduate Projects in Computer Science program, which provides Duke undergraduates with intensive research experiences in teams of 3-4 students mentored by faculty and graduate students. He also actively collaborates with colleagues through programs like Data+ and Code+, creating a vibrant ecosystem for undergraduate research in computer science at Duke.