Location: Blocker 220 and Zoom Dr. Li An is the Solon & Martha Dixon Endowed Professor at the College of Forestry, Wildlife and Environment and the Director of the Center for Human-Earth System Science (Center URL) at Auburn University. He received his B.S. degree from Peking University (Economic Geography), China, M.S. degree from Chinese Academy […]
As AI and our understanding of it continues to evolve, how do you determine when it’s worth using in the academic environment? In this discussion-based, undergraduate-focused workshop, you’ll explore some of the issues with using AI in academic coursework including hallucinations, bias, acceptable use, citability, and plagiarism.AI tools used in this session are freely available […]
To use AI or to not use AI – that is the topic of this discussion-based workshop. AI is becoming increasingly hard to ignore and its use comes with many consequences, both positive and negative. This workshop aims to present a holistic view of AI and challenge participants to consider how much or how little […]
As AI and our understanding of it continues to evolve, how do you determine when it’s worth using in the academic environment? In this discussion-based, undergraduate-focused workshop, you’ll explore some of the issues with using AI in academic coursework including hallucinations, bias, acceptable use, citability, and plagiarism. AI tools used in this session are freely […]
JungHyun Han is a professor at Korea University, where he directs the Superintelligence Research Center. His research interests lie in computer graphics and virtual/augmented realities. Location: Blocker 220 and Zoom Augmented Reality Applications for Air Conditioner and Construction Industries In this talk, Professor Han presents two AR applications: a mobile AR system for visualizing airflow […]
Location: Rudder 302 Time: 8:30 am – 4:30 pm We are excited to invite you to our one-day Scientific Machine Learning Workshop, where you’ll have the opportunity to delve into the latest advancements and applications of AI, machine learning, and data science in scientific research. This workshop is designed for students, researchers, and faculty, offering […]
Dr. Sriraam Natarajan is a Professor and the Director of the Center for ML at the Department of Computer Science at the University of Texas, Dallas. His research interests include Artificial Intelligence, with an emphasis on Machine Learning, Statistical Relational Learning and AI, Reinforcement Learning, Graphical Models, and Biomedical Applications. He has won several awards, including […]
Dr. Kim is an Assistant Professor in the Department of Construction Science (COSC) at Texas A&M University (TAMU), where he earned his Ph.D. in COSC. Prior to returning to TAMU, he served as an Assistant Professor in the Department of Civil Engineering at the University of Dayton from 2022 to 2024. His research focuses on […]
Register Now Registration deadline is May 9th About the Workshop Discover the power of interdisciplinary collaboration at the upcoming Research in Artificial Intelligence for Science and Engineering (RAISE) workshop, supported by the Texas A&M Institute of Data Science (TAMIDS). This initiative brings together experts in foundational AI research—spanning machine learning, computer vision, large language models, […]
Location: Texas A&M University, Blocker Building, Room 220 & 102 This free five-day summer school is designed to introduce graduate students to the fundamentals of Physics-Informed Neural Networks (PINNs) and Scientific Machine Learning (SciML). The first three days will focus on foundational concepts in PINNs, structured into morning theory sessions followed by afternoon hands-on tutorial […]
Shobhit Jain is a tenured Assistant Professor of Applied Mathematics at Delft University of Technology. He earned his undergraduate degree in Mechanical Engineering from IIT Roorkee, his MS degrees in Mechanical Engineering and Applied Mathematics from TU Delft, and his doctoral degree from ETH Zurich. Shobhit has had industrial stints at several engineering firms, gathering […]
This free workshop is designed for students and educators interested in building a strong foundation in machine learning.
