School Of Medicine
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AI Deep Dive: Harnessing Technology for Improved Speech Health
On October 27th, we had the privilege of hosting an AI Deep Dive Session with Dr. Matthew Pontell, where we discussed the use of generative AI for enhancing speech therapy and improving speech dysfunction. This session brought to light the innovative strategies and recovery techniques that promise better speech… Read MoreNov. 2, 2023
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Active Learning Strategies for Efficient Growth of BGC Database (DSI-SRP)
This DSI-SRP fellowship funded Chaehyun “Amy” Song to work in the laboratory of Dr. Allison Walker, Ph.D. in the Department of Pathology, Microbiology and Immunology during the summer of 2023. Amy is a rising junior with a major in Biochemistry and Chemical Biology and a minor in Computer Science. In… Read MoreAug. 21, 2023
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Evaluating and Applying Machine-Learning Models in Predicting Gene Regulation and Expression in Neuropsychiatric Disorders (DSI-SRP)
This DSI-SRP fellowship funded Namju Kim to work in the laboratory of Dr. Eric Gamazon, Ph.D. in the Department of Medicine during the summer of 2023. Namju is a rising junior with a major in Molecular and Cellular Biology and a minor in Data Science. Neuropsychiatric diseases are partially caused… Read MoreAug. 21, 2023
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Modeling Signaling Pathways Using Recurrent Neural Networks (DSI-SRP)
This DSI-SRP fellowship funded Alexander Lin to work in the laboratory of Dr. Gregor Neuert, Ph.D. in the Department of Molecular Physiology and Biophysics during the summer of 2023. Alexander is a rising sophomore with majors in Computer Science and Biochemistry and a minor in Data Science. His project focused… Read MoreAug. 14, 2023
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MS DS Student, Rio Jia: Innovating in Augmented Reality Art
We are thrilled to highlight the achievements of one of our graduate students at the Data Science Institute, Rio Jia. Rio has made significant contributions to an Augmented Reality (AR) Art project in collaboration with the FRIST Center for Autism & Innovation and Dr. Kendra H. Oliver. Dr. Oliver… Read MoreJun. 28, 2023
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Newly established Center for Applied AI in Protein Dynamics launching with the DSI a bootcamp program for graduate students
Vanderbilt University School of Medicine Basic Sciences recently established the Center for Applied Artificial Intelligence in Protein Dynamics, led by Hassane Mchaourab, to explore the intersection of artificial intelligence (AI), machine learning, and macromolecular mechanisms to understand protein structures and their functions in the human body. The center’s research aims… Read MoreApr. 18, 2023
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DSI hosts Women in Data Science (WiDS) conference for data scientists and aspiring data scientists to learn from other women in the field
The Data Science Institute welcomed women who are leading the way in data science at our annual Women in Data Science (WiDS) conference on March 7. The conference was an opportunity for women in data science to connect, network and learn from other women in the field. Read MoreMar. 8, 2023
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AI Deep Dive Nov 4: Using Large Language AI Models to Support Language Instruction
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… Read MoreOct. 20, 2022
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AI Deep Dive Nov 4: Using Large Language AI Models to Support Language Instruction
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… Read MoreOct. 20, 2022
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AI Deep Dive: Training a Transformer Model on EEGs
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… Read MoreSep. 29, 2022