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Chibuike E. Ugwu

Ph.D. Candidate in Computer Science

Washington State University, Pullman, WA, USA

(Last Update: May 2026)

About Me

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 Diane Cook. My general research interests are in Artificial Intelligence (AI) and Machine Learning (ML), with a main focus on developing robust, safe, and trustworthy ML algorithms with theoretical guarantees for deployment in critical real-world challenges within safety-sensitive domains (e.g., healthcare).

My current research focuses on:

  • Building trustworthy Large Language Model (LLM) hallucination control policies for safety-sensitive applications.
  • Advancing Conformal Prediction-based uncertainty quantification with theoretical guarantees to facilitate effective human–ML collaboration (e.g., Clinician-in-the-Loop Uncertainty-aware predictive systems and beyond).
  • Developing uncertainty-aware energy management methods for wearable Internet of Things (IoT) devices for mobile health applications and beyond.

Projects

Overview of research on uncertainty quantification, trustworthy LLMs, RLHF, and wearable IoT
  • I develop conformal prediction methods for safety-sensitive healthcare tasks, producing intervals and regions with formal coverage guarantees. Representative work includes clinician-in-the-loop UTI detection from smart-home sensors (AAAI 2026), calibrated cognitive-health regions from smartwatch data (ACM HEALTH), and Adaptive Prediction Regions for multi-target regression.

  • I build hallucination control policies for trustworthy LLMs in safety-sensitive settings—detecting unsupported claims, quantifying uncertainty, verifying against evidence, and abstaining when confidence is low so systems defer to human experts when needed.

  • I develop uncertainty-aware RLHF for clinician-facing forecasting from continuous sensor data, combining behavioral markers, clinician prompts, a fine-tuned LLM, and conformal prediction. Expert feedback on reliability and usability guides updates toward accurate, actionable, expert-aligned clinical AI.

  • I design uncertainty-aware energy management for wearable health IoT under limited battery and uncertain harvesting, using calibrated conformal forecasts to allocate energy while preserving sensing and inference.
    Highlighted papers: IJCAI 2025 · DAC 2025

Latest News

  • April, 2026 — I am super excited to receive three amazing awards:
  • 2026 — I am thrilled to share that my papers were accepted:
    1. AAAI 2026 - Clinician-in-the-Loop Smart Home System to Detect Urinary Tract Infection Flare-Ups via Uncertainty-Aware Decision Support
    2. ACM HEALTH - Conformalized Uncertainty Regions for Machine Learning-Based Multiple Cognitive Health Measures from Smartwatch Sensor Data
    3. ACM TODAES - Trading Off Performance and Sustainability in Internet of Things: An Uncertainty-Aware Hierarchical Energy Management Approach
  • 2025 — Received the Mahmoud M. Dillsi Graduate Fellowship; papers accepted at IJCAI 2025, DAC 2025, and ACM TECS (ERGo).
  • May 2025 — Successfully passed my Ph.D. Preliminary Exam. Now a Ph.D. candidate!
  • 2024 — Outstanding Graduate Teaching Assistant in EECS (VCEA); Nakahara Tsuyoshi and Mary Fellowship.

Select Publications

Clinician-in-the-Loop Smart Home System to Detect Urinary Tract Infection Flare-Ups via Uncertainty-Aware Decision Support C. E. Ugwu, R. Fritz, D. J. Cook, J. Doppa AAAI Conference on Artificial Intelligence (AAAI), 2026

Conformalized Uncertainty Regions for Machine Learning-Based Multiple Cognitive Health Measures from Smartwatch Sensor Data C. E. Ugwu, Y. Yan, D. J. Cook, M. Schmitter-Edgecombe, J. Doppa ACM Transactions on Computing for Healthcare, 2026

Trading Off Performance and Sustainability in Internet of Things: An Uncertainty-Aware Hierarchical Energy Management Approach C. E. Ugwu*, D. Hussein*, G. Bhat, J. Doppa ACM Transactions on Design Automation of Electronic Systems (TODAES), 2026 · (* equal contribution) (to appear)

Sustainable Wearables for Health Applications and Beyond via Uncertainty-Aware Energy Management C. E. Ugwu*, D. Hussein*, G. Bhat, J. Doppa International Joint Conference on Artificial Intelligence (IJCAI), 2025 · (* equal contribution)

Uncertainty-Aware Energy Management for Wearable IoT Devices with Conformal Prediction C. E. Ugwu*, D. Hussein*, G. Bhat, J. Doppa ACM/IEEE Design Automation Conference (DAC), 2025 · (* equal contribution)

ERGo: Energy-Efficient Hybrid Graph Neural Network Training on Heterogeneous Processing-In-Memory Architecture P. Dhingra, C. E. Ugwu, J. Doppa, P. P. Pande ACM Transactions on Embedded Computing Systems (TECS), 2025

Sensitivity and robustness of randomization test and F-test in some experimental designs A. V. Oladugba, C. E. Ugwu, U. C. Onwuamaeze Quality and Reliability Engineering International, 2023

Professional Appointments

Research Assistant (Aug 2022 – Present)

EECS Department, Washington State University · Pullman, WA

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

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