Dear all,
Our next AI seminar is scheduled to be on February 9th , 2-3 PM. It will be followed by a 30-minute Q&A session with the graduate students.
Location: KEC 1001
Zoom link: https://oregonstate.zoom.us/j/96491555190?pwd=azJHSXZ0TFQwTFFJdkZCWFhnTW04UT09
Learning Universal Sequence Representations and Interpretable ML Models for Microbial Communities
Gail Rosen
Professor
Electrical and Computer Engineering
Drexel University
Abstract:
Microbes are found in every nook and cranny of the world and regulate the planetary carbon and oxygen cycles that are vital to life. Through high-throughput DNA/RNA sequencing, we can collect a vast amount of data about communities
of microbes in diverse environments. In this talk, I will discuss development of large language models to tackle the first step in understanding this vast amount of data for taxonomy/gene identification, including antimicrobial resistance. Then, I will demonstrate
our efforts to predict overall microbiome phenotype from metagenomic data and to explain important features, such as species composition, community hierarchy, functions, and mutations. Finally, I will address scalability of methods for sustainability.
Speaker Bio:
Gail Rosen received a B.S., M.S., and Ph.D. from the Georgia Institute of Technology. She is a recipient of an NSF CAREER award, a Drexel Faculty Career Development award, and Drexel Provost’s Fellowship. She serves on the editorial
board of the Association for Microbiology’s mSystems and BMC Microbiome journals. She heads the Ecological and Evolutionary Signal-processing and Informatics (EESI) lab, organizes the Center for Biological Discovery from Big Data, and serves on the board and
is a founding member of the University Research Computing Facility at Drexel. For the past 3 summers, she organized 2-week Drexel-Rowan-UChicago Biological Data Science summer workshops, which reached 8000+ participants around the world. In 2022-2023, she
spent a year as a visiting scholar at the National Institute of Standards and Technology, benchmarking cancer-somatic variant calling methods. Her interests are in machine learning and evolution.
Please watch this space for future AI Seminars :
https://engineering.oregonstate.edu/EECS/research/AI
Rajesh Mangannavar,
Graduate Student
Oregon State University
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AI Seminar Important Reminders:
-> For graduate students in the AI program, attendance is strongly encouraged