TrAC Seminar Series – Krishna Garikipati

Detail Date: December 11, 2024 Time: 11:00 AM - 12:00 PM CST Location: 2019 Morrill Hall or https://iastate.zoom.us/j/95263587232?pwd=K1BVcURvWExFb3pUT000NlRwdFZsZz09 Title: Fokker-Planck-Inverse Reinforcement Learning: A physics-constrained approach to Markov Decision Process models of cell dynamics Abstract Inverse Reinforcement Learning (IRL) is a compelling technique for revealing the rationale underlying the behavior of autonomous agents.  IRL seeks to estimate […]

TrAC Seminar Series – Ashis Banerjee

Detail Date: January 28, 2025 Time: 1:00 - 2:00 PM CST Location: https://iastate.zoom.us/j/92613276601?pwd=FOstCb1ZxfzUlSbCtn0B8TN9ahvJFl.1 Title: A Foray into Topological Learning from an Engineering Perspective Abstract Topological learning (TL), referring to a synergy of computational topology and machine learning, has recently emerged as an effective pattern recognition framework for noisy, high-dimensional problems. The recognition happens by first […]

Mastering PyTorch

Master PyTorch, an open-source deep learning framework for AI. This course covers everything from the Tensors computations, custom architectures, and advanced functions in PyTorch. It also covers how to debug PyTorch codes to gain confidence in debugging codes. The course is packed with plenty of hands-on activities, homework, and instructor consulting to make learning PyTorch […]

Deep Reinforcement Learning

In this course, “Reinforcement Learning”, you will learn about various reinforcement learning (RL) algorithms, a branch of machine learning and AI. This course covers everything you need to know about RL, including an overview of the basic concepts of RL, value-based methods, policy-based methods, and actor-critic algorithms. You will also learn how to leverage these […]

TrAC Seminar Series – Ying Li

Detail Date: February 25, 2025 Time: 1:00 PM - 2:00 PM CT Location: https://iastate.zoom.us/j/92613276601?pwd=FOstCb1ZxfzUlSbCtn0B8TN9ahvJFl.1 Title: Machine Learning-accelerated Molecular Design of Innovative Polymers: Shifting from Thomas Edison to Iron Man Abstract […]

Interpretability in AI

In this course, “Interpretability in AI”, you will learn about various interpretable and explainable machine learning algorithms, a branch of machine learning and AI. This course covers everything you need to know about interpretability, including an overview of basic concepts of interpretability, interpretable models, model-agnostic methods, and example-based explanations. You will also learn how to […]

Parallelism in Deep Learning

In this course, “Parallelism in Deep Learning,” you will learn about the need for parallelism in deep learning and how to use different methods of parallelism in deep learning. You will also learn about leveraging data parallelism and model parallelism workflows for your AI models on HPC infrastructures. In this course, you will engage in […]

TrAC Seminar Series – Lindsey Raymond

Detail Date: March 4, 2025 Time: 1:00 PM - 2:00 PM CT Location: https://iastate.zoom.us/j/92613276601?pwd=FOstCb1ZxfzUlSbCtn0B8TN9ahvJFl.1 Title: Generative AI at Work Abstract We study the staggered introduction of a generative AI-based conversational assistant using data from 5,172 customer support agents. Access to AI assistance increases worker productivity, as measured by issues resolved per hour, by 15\% on […]

Inaugural Distinguished TrAC Lecture – Subbarao Kambhampati

2055 Hoover Hall 528 BISSELL RD, Ames, Iowa, United States

Detail Date: March 25, 2025 Time: 1:00 PM - 2:00 PM CT Location: 2055 Hoover Hall, Iowa State University (Zoom link is also provided for the audience external to ISU) Title: From LLMs to LRMs: The Jagged Quest to Tease Planning and Reasoning from Humanity’s Digital Footprints Abstract Large Language Models, auto-regressively trained on the […]

End-to-End Natural Language Processing

In this course, “End-to-End Natural Language Processing”, you will learn about text data and how to process textual data using state-of-the-art AI tools. This course covers everything you need to know about natural language processing and various tasks. You will also learn about leveraging large language models for NLP, how to perform Prompt Engineering and […]

3D Vision – NeRFs and INRs

In this course, “3D Vision – NeRFs and INRs”, you will learn about the basics of 3D Vision and how to use state-of-the-art 3D vision algorithms such as Neural Radiance Fields, Gaussian Splats, and Implicit Neural Representations. In this course, you will engage in hands-on activities, homework, and instructor consulting to make learning 3D Vision […]

TrAC Seminar Series – Jundi Liu

Detail Date: April 1, 2025 Time: 1:00 PM - 2:00 PM CT Location: 2004 Black Engineering or https://iastate.zoom.us/j/92613276601?pwd=FOstCb1ZxfzUlSbCtn0B8TN9ahvJFl.1 Title: Towards Human-centered and Trust-aware Autonomous Systems Abstract Over the past decade, autonomous systems have transformed how people work and live. Yet, despite their growing market penetration, user acceptance and effective interaction remain challenging. Trust is a […]