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Yanjun Qi
Machine Learning For Computational Biology
Deep Learning In Bioinformatics
Computational Biology
Bioinformatics Data Analysis
About
Yanjun Qi is an Associate professor (tenured) of the University of Virginia, Department of Computer Science since 2013. She was a senior researcher in the Machine Learning Department at NEC Labs American, Princeton, NJ from July 2008 to August 2013. Her research interests are within machine learning, deep learning, and bioinformatics. She obtained her Ph.D. degree from the School of Computer Science at Carnegie Mellon University in May 2008 and received her Bachelor's degree with highest honors from the Computer Science Department at Tsinghua University, Beijing. She has served as PCs and reviewers for multiple renowned international conferences/ journals and has co-chaired the NIPS “Machine Learning for Computational Biology” workshop. Dr. Qi has received a CAREER award from NSF.
Research Performance Summary
2001-2025
Active Research Span
First Recorded Paper
Video Retrieval with the Informedia Digital Video Library System.
Year:
2001
Citations:
25
Venue:
TREC
Latest Recorded Paper
Peacemaker or Troublemaker: How Sycophancy Shapes Multi-Agent Debate
Year:
2025
Citations:
0
Venue:
arXiv preprint arXiv:2509.23055
Last 10 Years Publication Activity
This timeline shows the professor's yearly publication activity.
Publication Venues and Collaboration
Journal, Conference, and Book Publication Breakdown
Top Coauthors
Wang
Sekhon
Research Impact by Period
Papers
13
Citations
39
Avg. Citations / Paper
3
H-Index
4
Papers
43
Citations
3506
Avg. Citations / Paper
81.5
H-Index
18
Papers
41
Citations
9345
Avg. Citations / Paper
227.9
H-Index
23
Papers
30
Citations
2726
Avg. Citations / Paper
90.9
H-Index
18
Papers
13
Citations
1862
Avg. Citations / Paper
143.2
H-Index
12
Papers
5
Citations
336
Avg. Citations / Paper
67.2
H-Index
5
Contact and Professional Links
Detected Research Keywords
Inertial Body Sensors
Protein Interaction Prediction
Protein Protein Interaction
Sentiment Classification Supervised
Interactions Hiv Human
Hiv Human Proteins
Graph Convolutional Networks
Sparse Gaussian Graphical
Opportunities Obstacles Learning
Obstacles Learning Biology