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Chibuike E. Ugwu

Ph.D. Candidate in Computer Science

Washington State University, Pullman, WA, USA

About Me

I am a final-year Ph.D. candidate in Computer Science at Washington State University, advised by Professors Jana Doppa and Diane Cook. I am currently an AI & Informatics Research Intern at Mayo Clinic. My research is in Artificial Intelligence and Machine Learning, with a main focus on developing robust, safe, and trustworthy ML algorithms with theoretical guarantees for deployment in healthcare and other safety-sensitive applications. My work emphasizes uncertainty quantification and conformal prediction to enable reliable decision-making in critical real-world settings.

My current research focuses on:

  • Building trustworthy machine learning algorithms for safety-sensitive applications.
  • Reliable LLM hallucination control policies
  • Uncertainty-aware human–AI collaboration for safe decision support
  • Trustworthy AI for medical imaging

Interests

  • Trustworthy AI
  • Large Language Models
  • AI safety
  • AI in Healthcare

Professional Experience

Mayo Clinic logo

AI Research Intern (Sept. 2026 – Dec. 2026)

Mayo Clinic, AI & Informatics · Rochester, MN, USA

Washington State University logo

Research Assistant (Aug 2022 – Present)

Washington State University, EECS Department

Washington State University logo

Teaching Assistant and Guest Lecturer (Aug 2022 – Dec 2024)

Washington State University, EECS Department

Latest News

Select Publications

Clinician-in-the-Loop Smart Home System to Detect Urinary Tract Infection Flare-Ups via Uncertainty-Aware Decision Support Chibuike E. Ugwu, Roschelle Fritz, Diane J. Cook, Jana Doppa AAAI Conference on Artificial Intelligence (AAAI), 2026
Clinician-in-the-loop UTI detection with conformal-calibrated intervals
Conformalized Uncertainty Regions for Machine Learning-Based Multiple Cognitive Health Measures from Smartwatch Sensor Data Chibuike E. Ugwu, Yan Yan, Diane J. Cook, Maureen Schmitter-Edgecombe, Jana Doppa ACM Transactions on Computing for Healthcare, 2026
Conformalized uncertainty regions for cognitive health measures
Trading Off Performance and Sustainability in Internet of Things: An Uncertainty-Aware Hierarchical Energy Management Approach Chibuike E. Ugwu*, Dina Hussein*, Ganapati Bhat, Jana Doppa ACM Transactions on Design Automation of Electronic Systems (TODAES), 2026 · (* equal contribution)
Trading off performance and sustainability in IoT energy management
Sustainable Wearables for Health Applications and Beyond via Uncertainty-Aware Energy Management Chibuike E. Ugwu*, Dina Hussein*, Ganapati Bhat, Jana Doppa International Joint Conference on Artificial Intelligence (IJCAI), 2025 · (* equal contribution)
Sustainable wearables via uncertainty-aware energy management
Uncertainty-Aware Energy Management for Wearable IoT Devices with Conformal Prediction Chibuike E. Ugwu*, Dina Hussein*, Ganapati Bhat, Jana Doppa ACM/IEEE Design Automation Conference (DAC), 2025 · (* equal contribution)
Uncertainty-aware energy management for wearable IoT devices
ERGo: Energy-Efficient Hybrid Graph Neural Network Training on Heterogeneous Processing-In-Memory Architecture Pratyush Dhingra, Chibuike E. Ugwu, Jana Doppa, Partha Pratim Pande ACM Transactions on Embedded Computing Systems (TECS), 2025
ERGo energy-efficient GNN training overview
Sensitivity and robustness of randomization test and F-test in some experimental designs Abimibola Victoria Oladugba, Chibuike E. Ugwu, Uchenna Charity Onwuamaeze Quality and Reliability Engineering International, 2023

Professional Appointments

Mayo Clinic logo

AI Research Intern (Sept. 2026 – Dec. 2026)

Mayo Clinic, AI & Informatics · Rochester, MN, USA

Conducting machine learning and artificial intelligence research for healthcare applications.

Washington State University logo

Research Assistant (Aug 2022 – Present)

EECS Department, Washington State University · Pullman, WA

Developing novel algorithms and theory for robust and trustworthy machine learning.

Washington State University logo

Teaching Assistant and Guest Lecturer (Aug 2022 – Dec 2024)

EECS Department, Washington State University · Pullman, WA
CptS 223 — Advanced Data Structures C/C++ Fall 2022, Fall 2023, Fall 2024
CptS 315 — Introduction to Data Mining Spring 2023, Spring 2024

Professional Services and Outreach Activities

Conference Activities

  1. AAAI Conference on Artificial Intelligence (AAAI) 2026
  2. Annual Conference on Neural Information Processing Systems (NeurIPS) 2025
  3. International Joint Conference on Artificial Intelligence (IJCAI) 2025

Program Committee Member

  1. International Conference on Machine Learning (ICML) 2026
  2. International Conference on Uncertainty in Artificial Intelligence (UAI) 2026
  3. International Conference on Learning Representations (ICLR) 2026
  4. Association for the Advancement of Artificial Intelligence (AAAI) 2026
  5. AAAI Conference on Artificial Intelligence, AI for Social Impact Track (AISI) 2026
  6. AAAI Conference on Artificial Intelligence, AI for Innovative Applications (IAAI) 2026
  7. International Conference of Machine Learning (ICML) 2025
  8. Association for the Advancement of Artificial Intelligence (AAAI) 2025
  9. AAAI Conference on Artificial Intelligence, AI for Social Impact Track (AISI) 2025
  10. AAAI Conference on Artificial Intelligence, AI for Social Impact Track (AISI) 2024

Volunteer and Outreach Activities

  1. Volunteer for AAAI Conference on Artificial Intelligence (AAAI), 2026
  2. Volunteer for International Joint Conference on Artificial Intelligence (IJCAI), 2025
  3. Mentor and Judge for Digital AgAthon (AgAID Institute), 2025
  4. Instructor for WSU Summer Programming Camp for Middle Schoolers, 2025
  5. Judge for Showcase for Undergraduate Research and Creative Activities (SURCA), 2026
  6. Judge for ACM Club's CrimsonCode Hackathon, 2026