I am a Ph.D. candidate in Computer Science at Washington State University, where I am fortunate to be advised by professors Jana Doppa and Yan Yan . My general research interests are in Machine Learning (ML) and Artificial Intelligence (AI), with a main focus on developing robust, safe, and trustworthy deep learning algorithms and theoretical frameworks for addressing critical real-world challenges within safety-sensitive domains. My current work focuses on:

• Building trustworthy Large Language Model (LLM) hallucination control policies.
• Adapting calibration-based uncertainty quantification methods, like Conformal Prediction, to facilitate effective and secure human-ML collaboration.
• Developing uncertainty-aware energy management methods for wearable Internet of Things (IoT) devices.

• Ph.D., Computer Science
  Washington State University (2022 - present)
• M.Sc., Computer Science
  Washington State University (2022 - 2025)
• B.Sc., Statistics (First Class Honors)
  University of Nigeria (2014 - 2018)

• July, 2025 - Great News! 🎉 Our paper, "ERGo: Energy-Efficient Hybrid Graph Neural Network Training on Heterogeneous Processing-In-Memory Architecture," has been accepted to the International Conference on Compilers, Architecture, and Synthesis for Embedded Systems, Embedded Systems Week (ESWEEK 2025)!
• May, 2025 - Successfully passed my PhD Preliminary Exam 🎉. Now a PhD Candidate!
• April, 2025 - Great News! 🎉 Our paper, "Sustainable Wearables for Health Applications and Beyond via Uncertainty-Aware Energy Management," has been accepted to the 34th International Joint Conference on Artificial Intelligence (IJCAI 2025)!
• Feb., 2025 - Exciting News! 🎉 Our paper, "Uncertainty-Aware Energy Management for Wearable IoT Devices with Conformal Prediction," has been accepted to the 62nd ACM/IEEE Design Automation Conference (DAC 2025)!
• Nov., 2024 - Passed my Ph.D. Qualifying Examination! Excited for the next phase of my research!
• April, 2024 - 🏅 Outstanding Graduate Teaching Assistant in EECS Award, VCEA.