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New Courses in Generative AI for Undergraduates, Graduate Students, and PostDocs
Jul. 21, 2023—This fall, there will be opportunities for students and Postdocs to take classes covering the latest advances in generative AI. For undergraduates, as part of the Future of Learning and Generative AI Initiative, undergraduates will be able to register for DS 3891 Introduction to Generative Artificial Intelligence. This course introduces the theory and use of these...
Surgical Informed Consent NLP Research
Dec. 12, 2022—Researchers in the Surgical Ethics Program at VUMC are seeking a data science student to collaborate on a project involving natural language processing. The ultimate goal of this project is to improve patient comprehension of the informed consent process and their surgical care. Interested students should reach out to the PI, Dr. Alexander Langerman, at...
AI Winter Intensive Workshop: Jan 3-6
Nov. 18, 2022—The practice of data science is changing with the rise of powerful, flexible and capable models called transformers. You can solve many different problems using a single pre-trained model, sometimes with no additional training on your data (“zero-shot” solutions). From text, to images, to audio (“textless Natural Language Processing”), you can ask and answer questions,...
Detecting Colliding Black Holes: AI Deep Dive Dec. 2
Nov. 14, 2022—Cosmic cataclysmic events such as the collision of black holes create strong gravitational waves which can be detected on Earth. Instruments such as LIGO can detect distortions of space that herald the passing of these gravity waves, but analyzing these signals is a computationally-intensive and time-consuming endeavor. Can AI offer a solution to speed discovery,...
AI Deep Learning Class Open to Graduate Students, Seniors
Nov. 9, 2022—This Spring, the Data Science Institute course on transformers, AI deep learning models, will be open to graduate students and seniors with permission of the instructor. The course, DS-5899 Special Topics in Data Science–Transformers in Theory and Practice, covers transformers models as applied to natural language processing, audio, image, video, multimodel problems, Bayesian inference, reinforcement...
AI Deep Dive Nov 4: Using Large Language AI Models to Support Language Instruction
Oct. 20, 2022—Multilingual large language models have demonstrated strong performance in natural language processing tasks. In this discussion, we explore how these transformer-based models might be used to support language instruction. In the current case study, we’ll examine possible uses of these models to support instruction in Hindi. Might these models be able to: Identify the core...
AI Deep Dive: Exploring the Narrative Arc
Oct. 7, 2022—When reading a longer document, such as a novel, your interpretation of the text you are currently reading is informed by what’s come before. Your attention to particular details, wording, or ideas; whether you perceive an action in a positive or negative light; what you think about a particular character. Currently, transformer-based Large Language Models...
AI Deep Dive: Training a Transformer Model on EEGs
Sep. 29, 2022—Friday, September 30 at 1:00pm the Data Science Institute will host Prof. Sasha Key in a discussion of applying transformer deep learning models to the problem of analyzing multichannel EEG in response to multiple stimulus/recording conditions (e.g., faces vs. objects, speech vs. nonspeech, attend vs. ignore, etc.). Transformers are powerful sequence learners, and can be...
New DSI Postdoctoral Fellow, Abbie Petulante
Sep. 20, 2022—We’re pleased to be able to introduce Abigail (Abbie) Petulante as a new DSI Postdoctoral Fellow! Abbie received her PhD in Astronomy this year at Vanderbilt where she applied a wide variety of machine learning and deep learning techniques to model the development of large structures comprised of dark matter in simulations of the evolution...
New DSI Postdoctoral Fellow, Joshua Su
Sep. 20, 2022—We’re pleased to be able to introduce Zhaoqian (Joshua) Su as a new DSI Postdoctoral Fellow! Joshua comes to us from the Einstein College of Medicine where as a Postdoctoral Fellow he applied deep learning to problems related to the formation protein structures such as peptide fibrils. As a member of the DSI Data Science...