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BIMSA Member Seminar
Natural Vector Methods and Artificial Intelligence: Applications in Bioinformation
Natural Vector Methods and Artificial Intelligence: Applications in Bioinformation
Organizers
Speaker
Time
Monday, April 14, 2025 12:45 PM - 1:25 PM
Venue
A6-101
Online
Zoom 388 528 9728
(BIMSA)
Abstract
In this lecture, we first introduce the natural processing of Professor Stephen Yau's biological team and its method extension.
Then we explain how to use non-precise negotiated natural processing + AI to study biological information problems.
We gave two examples:
1: Predicting uncertain non-standard base codes
2: Classification of coding RNA and non-coding RNA (classification between non-coding RNA, and
Create our own structural and functional data sets to explore whether mutation/inserion will lose or transform functionality)
Speaker Intro
Researcher at Beijing Institute of Mathematical Sciences and Applications
Xi'an Jiaotong University, Bachelor's and Master's in Computational Mathematics.
UIC University, PhD in Computer Science, Research Direction: Nonlinear Filter Control, Supervisor: Stephen S.-T Yau 丘成栋
After graduation, he mainly worked in the field of wireless communications in the United States. He worked as a senior engineer in Lucent, Alcatel-Lucent, Nokia and other companies.
Joined Beijing Institute of Mathematical Sciences and Applications (BIMSA) in Jan. of 2024, currently engaged in research on neural networks, artificial intelligence, big data, machine learning and biomathematics.
Xi'an Jiaotong University, Bachelor's and Master's in Computational Mathematics.
UIC University, PhD in Computer Science, Research Direction: Nonlinear Filter Control, Supervisor: Stephen S.-T Yau 丘成栋
After graduation, he mainly worked in the field of wireless communications in the United States. He worked as a senior engineer in Lucent, Alcatel-Lucent, Nokia and other companies.
Joined Beijing Institute of Mathematical Sciences and Applications (BIMSA) in Jan. of 2024, currently engaged in research on neural networks, artificial intelligence, big data, machine learning and biomathematics.