SU Agent-AI Workshop 2026 - Syracuse University

About the Workshop

SU Agent AI Workshop 2026 brings together students, researchers, practitioners, and industry professionals to explore the latest advances in autonomous and semi-autonomous AI agents. As agent-based systems increasingly shape real-world applications from scientific discovery and decision support to software engineering and robotics this workshop provides a focused forum for sharing ideas, methods, and emerging best practices.

The program will feature five confirmed invited talks delivered by experts from academia and industry. Each talk will provide in-depth perspectives on cutting-edge topics in Agent AI, including agent architectures, reasoning and planning, multi-agent coordination, tool-augmented agents, learning in complex environments, safety, and real-world applications. Participants will gain insights into both foundational research and applied perspectives on building, evaluating, and deploying agent-based AI systems.

The workshop serves as a platform for collaboration and community-building across disciplines. Attendees will have opportunities to engage with speakers, exchange ideas with peers, and discuss open problems and future directions in Agent AI research and development. Whether you are advancing theoretical foundations, developing practical agent systems, or exploring new applications, the SU Agent AI Workshop 2026 offers a valuable platform to learn, connect, and contribute to the evolving landscape of intelligent agents.

Topics of Interest

LLM Agents and Learning of LLM agents
Designing autonomous agents that can reason, plan, and act using modern frameworks and multi-agent systems.
Enabling agents to interact with APIs, databases, and external tools to perform real-world tasks autonomously.
Building systems where multiple AI agents coordinate, communicate, and solve complex problems together.
Open source software of LLM tool use and agents

Schedule

Time	Event
8:00AM – 9:00AM	Coffee and Networking - Sponsored by the IEEE Syracuse Section Meet in the lobby, get registered, enjoy some coffee, and meet your fellow attendees.
9:00AM – 9:10AM	Opening Remarks Professor Alex Jones Chair, Department of Electrical Engineering and Computer Science (EECS) Klaus Schroder Endowed Chair Professor Engineering and Computer Science
9:10AM – 10:00AM	Invited Talk: "From Benchmarks to Environments: Training Agentic Systems for Reliability" Stephanie Vanwagner Vice President, Turing Intelligence Palo Alto, California
10:00AM – 10:50AM	Invited Talk: "Constructing and Evolving Rubrics: Synergizing Synthetic Data with Multi-Agent RL" Professor Haoyu Wang Assistant Professor, Department of Computer Science College of Nanotechnology, Science and Engineering University at Albany, State University of New York
10:50AM - 11:00AM	10 Minutes Break
11:00AM – 11:50AM	Invited Talk: "Human-Aware Reinforcement Learning: Towards Natural Human–Robot Collaboration" Professor Jamison Heard Assistant Professor, Department of Electrical and Microelectronic Engineering Kate Gleason College of Engineering Rochester Institute of Technology
12:00Noon – 12:50PM	Invited Talk: "Recent theoretical advances in diffusion models" Professor Yuchen Wu Assistant Professor, School of Operations Research and Information Engineering Cornell University
12:50PM - 1:00PM	Closing Remarks

Speakers

Professor Alex K. Jones

Klaus Schroder Endowed Professor for Engineering

Chair – Department of Electrical and Computer Science
Syracuse University

Professor Alex K. Jones serves as the Klaus Schroder Endowed Professor for Engineering and Chair of the Department of Electrical Engineering and Computer Science at Syracuse University. With extensive expertise in computer engineering, his research focuses on energy-efficient computing, hardware security, and embedded systems. He has made significant contributions to the field through his work on power-aware computing architectures and system-level design optimization. Professor Jones is dedicated to advancing engineering education and fostering innovation in computing technologies, leading initiatives that bridge academic research with real-world applications.

Stephanie VanWagner

Vice President

Turing Intelligence

As Vice President of Turing Intelligence, she leads Healthcare & Life Sciences and partners with leading pharma, biotech, and frontier labs to build the next generation of responsible, domain-specific AI. Her work focuses on accelerating clinical trials and drug discovery by turning proprietary scientific and clinical data into safe, high-performance intelligence that can be trusted in regulated environments.

Professor Haoyu Wang

Assistant Professor

Department of Computer Science
University at Albany
State University of New York

Haoyu Wang is an Assistant Professor of Computer Science at UAlbany. He received his Ph.D. degree in School of Electrical and Computer Engineering, Purdue University. His research spans Data Mining, Machine Learning, and Natural Language Processing, with a particular focus on democratizing knowledge-centric AI under realistic compute and data constraints for broader accessibility. He has been honored with several awards, including Distinguished Paper Award in AAAI'23, the Bilsland Dissertation Fellowship at Purdue University and he was selected as Future Leaders in Data Science and Artificial Intelligence at the University of Michigan (2024).

Professor Jamison Heard

Assistant Professor

Department of Electrical and Microelectronic Engineering
Kate Gleason College of Engineering
Rochester Institute of Technology

Jamison Heard received the Bachelor of Science degree in electrical engineering from the University of Evansville, Evansville, IN, USA, in 2013 and the Master of Science degree and Ph.D. in electrical engineering from Vanderbilt University, Nashville, TN, USA, in 2016 and 2019, respectively. He is currently researching adaptive human-robot teams, human-aware reinforcement learning, human-robotic interaction, task recognition, and real-time human state assessment.

Professor Yuchen Wu

Assistant Professor

School of Operations Research and Information Engineering
Cornell University

Yuchen Wu is an Assistant Professor in the School of Operations Research and Information Engineering at Cornell University. Prior to Cornell, she was a postdoctoral researcher in the Department of Statistics and Data Science at the Wharton School, University of Pennsylvania. She received her Ph.D. in 2023 from the Department of Statistics at Stanford University, advised by Professor Andrea Montanari. Her research focuses on establishing rigorous foundations for statistical and machine learning methods and developing new algorithms guided by theoretical insights.