Seed Grant Proposals Due February 23
AI Bridge Summit @ Texas A&M
A one-week training and team-formation summit and linked seed grant initiative to catalyze interdisciplinary teams, translate advanced AI into novel solutions, and support seed projects for future extramural funding.
MISSION
To bridge foundational and use-inspired AI research across Texas A&M by pairing AI method experts with domain researchers in structured ideation via a unique, linked tutorial-seed grant initiative to catalyze interdisciplinary teams, translate advanced AI into novel solutions, and support seed projects for future extramural funding
GOALS
Over the summit week, the program demystifies modern AI, including large language models and agents, vision and vision-language models, reinforcement learning and post-training, and AI for Science & Engineering, while pairing method builders with domain PIs to co-define problems, needs, and approaches for future research collaborations. The immediate goal is seed readiness for the linked seed grant. Over the following year, the aim is to translate these projects into proposals for extramural funding and accelerate Texas A&M University’s leadership in cutting-edge, use-inspired AI research.
AI BRIDGE SUMMIT
The summit paired tutorial training, spotlight presentations, poster sessions, and structured matchmaking to catalyze interdisciplinary teaming and measurable progress toward novel research proposals.
The summit was open to all members of the Texas A&M University System—including Ph.D. students, postdoctoral researchers, research engineers and scientists, and faculty across domains—with different topics presented each day, allowing participants to choose which days most align with their goals
Each day of the workshop covered a different aspect of AI research, allowing Texas A&M researchers to gain insight in the latest AI methodologies, technologies, and innovations.
Day 1 — Foundations of Machine Learning, Supervised Learning, Unsupervised Learning, Data Selection
- Shuiwang Ji, Professor and Truchard Family Endowed Chair, Computer Science & Engineering [YouTube Video]
- Nate Veldt, Assistant Professor, Computer Science & Engineering [YouTube Video] [Presentation PDF]
- Victoria Crawford, Assistant Professor, Computer Science & Engineering [YouTube Video] [Presentation PDF]
Day 2 — Large Language Models (LLMs)
- Yu Zhang, Assistant Professor, Computer Science & Engineering [YouTube Video] [Presentation PDF]
- Kuan-Hao Huang, Assistant Professor, Computer Science & Engineering [YouTube Video] [Presentation PDF]
Day 3 — Computer Vision and Vision Language Models (VLMs), 3D Reconstruction, Generation, and Language Models
- Cheng Zhang, Assistant Professor, Computer Science & Engineering [YouTube Video] [Presentation PDF]
- Zhiwen Fan, Assistant Professor, Electrical & Computer Engineering [YouTube Video]
Day 4 — Reinforcement Learning, Post-Training, Reasoning, and Language Agents
- Dileep Kalathil, Associate Professor, Electrical & Computer Engineering [YouTube Video] [Presentation PDF]
- Tianbao Yang, Professor, Computer Science & Engineering [YouTube Video]
Day 5 — Physics-informed machine learning, AI for life science, Bayesian Learning and Uncertainty Quantification
- Xiaofeng Qian, Associate Professor, Materials Science & Engineering [YouTube Video]
- Xiner Li, Senior AI Scientist, Genentech [YouTube Video]
- Anirban Bhattacharya, Professor, Statistics [YouTube Video]
Use-Inspired Spotlight
- Day One – Henry Ruiz
- Day One – Qian Yuan
- Day One – Seung Won Yoon
- Day Two – Andrej Svyantek
- Day Two – Paula Shireman
- Day Three – Yalong Pi
- Day Three – Adeolu Adekunle
- Day Three – Ximeng Tao
- Day Four – Muhammad Hasnain
- Day Four – Beju Rao
- Day Four – Andrej Svyantek
- Day Five – Xiaowei Chen
- Day Five – Yuxuan Cosmi Lin
AI BRIDGE RESEARCH SEED GRANT
📅 Deadline is February 23
Read the Call for Proposals
The program will provide small awards ($20,000) to interdisciplinary teams pursuing novel and innovative one-year research projects with potential for external funding.
Applicants do NOT need to participate in the linked summit training session to submit a proposal.
Grant Proposal Eligibility: The call is open to faculty members from Texas A&M University (including Galveston and other branch campuses) and its Texas A&M University System partner research state agencies (i.e., Texas A&M AgriLife Research and Texas Engineering Experiment Station) who are eligible to act as principal investigators for external funding.
AI BRIDGE RESEARCH SEED GRANT
Proposal Deadline is February 23, 2026, 11:59 PM CST
ORGANIZERS
Drew Casey
Associate Director, Texas A&M Institute of Data Science
Shuiwang Ji
Professor and Truchard Family Endowed Chair, Computer Science & Engineering
Nick Duffield
Director, Texas A&M Institute of Data Science
Bani K. Mallick
Distinguished Professor and Regents Professor, Statistics
Henry Fadamiro
Professor and Associate Vice President for Research, Strategic Initiatives, Texas A&M University Division of Research
Sharmila Pathikonda
Associate Vice Chancellor for Research, Director for Research Development, Texas A&M University System
Financial support for the AI Bridge Program is provided by the Texas A&M University Division of Research, Texas A&M Institute of Data Science, Texas A&M AgriLife Research, Texas A&M University System Office of Research, Texas A&M Engineering Experiment Station (TEES), and the Texas A&M University College of Arts and Sciences.
The Research in Artificial Intelligence for Science and Engineering Initiative (RAISE) is partnering to provide expertise and guidance in support of the AI Bridge Program.
