School of Electrical Engineering and Computer Science faculty members are presenting their research at prestigious conferences this year in areas such as design automation, embedded systems, high-performance computing, machine learning, and data science.
Several faculty members recently presented their work at the 39th Annual Conference on Neural Information Processing Systems (NeurIPS 2025), which brings together researchers from wide-ranging fields of study, including in artificial intelligence and machine learning as well as from neuroscience, life sciences, natural sciences, and social sciences. With growing worldwide interest in AI research and development, the conference, held in San Diego and in Mexico City in December, had more than 26,000 attendees.
Papers presented at NeurIPS 2025 included:
- Learning Reconfigurable Representations for Multimodal Federated Learning with Missing Data (Nghia Hoang)
- ROOT: Rethinking Offline Optimization as Distributional Translation via Probabilistic Bridge (The Hung Tran and Nghia Hoang)
- Enhancing Safety in Reinforcement Learning with Human Feedback via Rectified Policy Optimization (Honghao Wei)
- Online Optimization for Offline Safe Reinforcement Learning (Yassine Chemingui and Jana Doppa)
School of EECS researchers also recently presented at the Association for the Advancement of Artificial Intelligence (AAAI) conference in Singapore. This premier conference promotes research in artificial intelligence and brings together researchers, scientists, students, and engineers in AI disciplines for scientific exchange. Out of 29,000 submissions received for this year’s conference, less than 18% were accepted for publication.
At the event, Honghao Wei has been selected as an AAAI New Faculty Highlights. Meanwhile, Azza Fadhel and Jana Doppa are organizing a workshop on “AI to Accelerate Science and Engineering (AI for Agriculture and Forestry Sciences Theme).” Azza Fadhel, Nghia Hoang, and Jana Doppa are also giving a tutorial on “Blackbox Optimization from Offline Datasets: Foundations to Recent Advances.” Jana Doppa is chairing the AAAI Senior Members Track as well as giving invited talks at the “Collaborative and Trustworthy AI” workshop and “Singapore AI Week.”
Papers presented at AAAI:
- ForeSWE: Forecasting Snow-Water Equivalent with an Uncertainty-Aware Attention Model (Krishu Thapa, Nghia Hoang, and Ananth Kalyanaraman)
- Nanoporous Materials Discovery via Search Bias-Guided Surrogate Modeling (Azza Fadhel, Yassine Chemingui, Nghia Hoang, and Jana Doppa)
- Cost-Sensitive Conformal Training with Provably Controllable Learning Bounds (Xuesong Jia, Yuanjie Shi, and Yan Yan)
- Provably Minimum-Length Conformal Prediction Sets for Ordinal Classification (Zijian Zhang, Xinyu Chen, Yuanjie Shi, and Yan Yan)
- Discovery of Feasible 3D Printing Configurations for Metal Alloys via AI-Driven Adaptive Experimental Design (Azza Fadhel and Jana Doppa)
- Clinician-in-the-Loop Smart Home System to Detect Urinary Tract Infection Flare-Ups via Uncertainty-Aware Decision Support (Chibuike Ugwu, Diane Cook, and Jana Doppa)
“These are perhaps the most selective and sought after venues to publish peer-reviewed research and AI and ML, and so to have a strong presence in the technical programs of these conferences reflects on the cutting-edge quality of research conducted by our faculty and students in EECS,” said Ananth Kalyanaraman, director of the School of Electrical Engineering and computer Science. “The research works presented address foundational challenges in the development and use of AI in various important scientific and engineering applications.”