Hello, I'm Victor.
CS Ph.D. Candidate at Brown University
I work at the intersection of AI evaluation, human–AI interaction, and algorithmic accountability. I develop methods and tools to understand how large language models and autonomous agents behave in practice, and study how people interpret and rely on these systems. My goal is to ground AI evaluation in real-world use and community needs, helping build systems that people can meaningfully assess and hold accountable.
Affiliated with the Center for Tech Responsibility (CNTR) and Data Science Institute (DSI), advised by Prof. Suresh Venkatasubramanian. I am also a member of the RISE Lab, working with Prof. C. Malik Boykin.
Previously, I was a Data Scientist at SeqHub Analytics and a research assistant with The Mozilla OAT Project. I obtained my undergraduate degree in Computer Science from the University of Ibadan.
Beyond research, I love traveling, and I make videos on YouTube.
News & Updates
- September 2026 Our paper, "The AI Observatory: A Public Measure of Real-World AI Use", is accepted to NeurIPS Evaluations and Datasets Track 2026! Check out the media coverage in The Washington Post and MIT Technology Review.
- July 2026 We have two papers accepted to AIES 2026: MonitrLLM: A Community-Centered Evaluation Infrastructure for Large Language Models and Designing for Doubt: The Case for Informed Abstention in Autonomous Agents.
- July 2026 I gave a guest lecture, Grounded LLM Evaluations, at Bryant University for MSDS 640: Data Science and AI Capstone.
- May 2026 Our paper "What Benchmarks Don't Measure: The Case for Evaluating Abstention Competence in Autonomous Agents" won the Best Paper Award at the RLEval Workshop at ACM CAIS.
- April 2026 Multi-lingual Functional Evaluation for Large Language Models accepted to ACL Findings. See you in San Diego!
- April 2026 More Is Not Better: Visual Uncertainty Cues and the Fragility of Trust Calibration in LLM-Assisted Decision Making accepted to Computers in Human Behavior: Artificial Humans Journal.
- Dec 2025 Beyond Static Leaderboards: A Roadmap to Naturalistic, Functional Evaluation of LLMs accepted to the Second Workshop on Language Models for Underserved Communities (LM4UC) at AAAI 2026.
- Sep 2025 "Testing LLMs in a sandbox isn't responsible. Focusing on community uses and needs is." accpeted as an opinion abstract at the Workshop on Socially Responsible Language Modelling Research at COLM 2025.
- July 2025 Excited to be one of the keynote speakers at the inaugural Technical AI Governance Workshop at ICML.
- May 2025 Serving as one of the Social Chairs for FAccT 2025.
- April 2025 I am giving an invited talk at the Ohio Data Ethics Working Group on the landscape of AI Audit Tools.
- Jan 2025 Towards AI Accountability Infrastructure: Gaps and Opportunities in AI Audit Tooling is accepted to CHI'25. See you in Japan!
- April 2024 We got a Distinguished Paper Award at the 2nd IEEE Conference on Secure and Trustworthy Machine Learning for our paper on the AI Auditing landscape.
- March 2024 I will be presenting our paper "Towards AI Accountability Infrastructure: Gaps and Opportunities in AI Audit Tooling" at the NorthEast HCI meeting.
- Dec 2023 Our Paper "SoK: AI Auditing: The Broken Bus on the Road to AI Accountability" has been accepted to the 2nd IEEE Conference on Secure and Trustworthy Machine Learning! Camera-ready and more details on the way.
- Oct 2023 I gave a talk at the inaugural research mentorship series of the Society of Petroleum Engineers, University of Ibadan Chapter. See Slides here.
- Mar 2023 I co-facilitated a panel session on Navigating the Open-Source Algorithm Audit tooling landscape with Abeba Birhane at Mozfest, 2023.
- Mar 2023 I officially accepted Brown's PhD offer to start in the fall.