Abdul-Hakeem Omotayo

Fair, Scalable, Responsible and Trustworthy AI Systems Researcher at the University of California, Davis


Hi! My preferred name is Hakeem.

I completed my undergraduate degree in Mathematics at the University of Lagos while focusing on developing novel aerodynamic systems. Then, I went on to pursue an M.S. in Mathematics at New Mexico State University, Las Cruces working under the guidance of Prof. Ernest Barany and Prof. Abdessattar Abdelkefi where I explored the role of nonlinear freeplay in airfoil dynamics. Following that, I began my journey toward a Ph.D. in Statistics at the University of California, Davis where I am fortunate to be working in Prof. Fushing Hsieh’s group on time series, statistical computer vision and AI ethics.

My substantive interest lies in improving machine learning algorithms & methods for various use cases such as debiasing large language models, double-bind problems (low data domain & compute), statistical vision and developing strategies for evaluating these algorithms and methods for concerns that revolve around ethics, fairness, accountability, and trustworthiness. I am passionate about how we can improve the capabilities of AI systems while reducing their unique capacity to propagate harm.

Some research questions I am currently pursuing are:

  1. How do we lean on mathematical, statistical and computing theories and methods to develop theoretical frameworks for evaluating fairness, equity, justice, and accountability in AI systems?
  2. How should AI experts foster and contribute to policy development, implementation, and monitoring of the safety, transparency, and trustworthiness of AI systems deployed in areas like policing, healthcare, agriculture, finance, customer service, and autonomous robots?
  3. How do we evaluate representations and bias, consent, privacy, data handling, data quality, and other ethical issues in datasets collection and usage?
  4. How do we sustainably move values, concepts, and principles enshrined in AI systems and research to meaningful, pragmatic commitments that are action-guiding and measurable?
  5. What are the methods AI experts and government stakeholders can use in approximating the socio-economic impact of AI systems during development and before deployment?

In the past, I have interned (X2) with Microsoft AI Platform in the Azure Cognitive Service Language Pillars Team. I was lucky to be mentored by Amita Gajewar and managed by Priyanka Kulkarni. I have also been blessed to have been mentored by Dr. Susanna Ricco as a recipient of Google CS Research Mentorship Program and Dr. Zhipeng Lou as a recipient of J.P. Morgan’s Quantitative Research Mentorship Program.

This summer, I am a returning intern with Microsoft AI Platform in the Visual Document Intelligence team.

In addition, I am currently an AI researcher at Masakhane and Roya where I contribute solutions to how we can improve Africa’s footprint by developing AI systems to cater to the needs of the continent. I am also working on how this participatory approach can be extended to people of historically marginalized communities across the world. As the sporadic growth of integrating AI systems into our daily lives continues, these communities are at risk of various harms.

In my spare time, I mentor students from disadvantaged backgrounds on how to navigate school, research, internships, and life in general.