Vasant Honavar

Huck Chair in Biomedical Data Sciences and AI; Professor and Edward Frymoyer Chair of Information Sciences and Technology

Vasant Honavar

Research Summary

Statistical machine learning algorithms for predictive modeling; modeling and inference of biological networks; characterization and prediction of protein-protein, protein-RNA, and protein-DNA interactions.

Huck Affiliations

Links

Most Recent Publications

Teng Xiao, Chao Cui, Huaisheng Zhu, Vasant Honavar, 2024, Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine on p. 1250-1256

Junjie Liang, Weijieying Ren, Hanifi Sahar, Vasant Honavar, 2024, Proceedings of the AAAI Conference on Artificial Intelligence on p. 13736-13743

Junjie Liang, Weijieying Ren, Sahar Hanifi, Vasant Honavar, 2024, Proceedings of the AAAI Conference on Artificial Intelligence on p. 13736-13743

Real world study of racial disparities associated with toxicities of sacituzumab govitecan.

Shista Priyadarshini, Justin Petucci, Avnish Katoch, Vasant Honavar, M Vasekar, 2024,

Analysis of a Single Heart Beat with Deep Learning for Prediction of Atrial Fibrillation in Patients with Cryptogenic Stroke: A Novel Approach to Electrocardiogram Data Augmentation

RS Shah, Daniel Otchere, J Petucci, AM Khursheed, J Raco, Vasant Honavar, A Maheshwari, 2024, Heart Rhythm on p. S784--S785

Interaction of racial disparities on outcomes and toxicities associated with treatment of HER2+ Breast Cancer-a TrinetX Database study

M Vasekar, Justin Petucci, Avnish Katoch, Vasant Honavar, 2024, Cancer Research on p. PO2--09

Cal-DPO: Calibrated Direct Preference Optimization for Language Model Alignment

Teng Xiao, Yige Yuan, Huaisheng Zhu, Mingxiao Li, Vasant Honavar, 2024,

TabLog: Test-Time Adaptation for Tabular Data Using Logic Rules

Weijieying Ren, Xiaoting Li, Huiyuan Chen, Vineeth Rakesh, Zhuoyi Wang, Mahashweta Das, Vasant Honavar, 2024, Proceedings of Machine Learning Research on p. 42417-42427

3M-Diffusion: Latent Multi-Modal Diffusion for Language-Guided Molecular Structure Generation

Huaisheng Zhu, Teng Xiao, Vasant Honavar, 2024,

Efficient Contrastive Learning for Fast and Accurate Inference on Graphs

Teng Xiao, Huaisheng Zhu, Zhiwei Zhang, Zhimeng Guo, Charu C. Aggarwal, Suhang Wang, Vasant G. Honavar, 2024, Proceedings of Machine Learning Research on p. 54363-54381

Most-Cited Papers

Yiwei Sun, Suhang Wang, Xianfeng Tang, Tsung-Yu Hsieh, Vasant Honavar, 2020, on p. 673--683

Li C. Xue, Drena Dobbs, Alexandre M J J Bonvin, Vasant Honavar, 2015, FEBS Letters on p. 3516-3526

Aria Khademi, David Foley, Sanghack Lee, Vasant Honavar, 2019, on p. 2907-2914

Cunliang Geng, Yong Jung, Nicolas Renaud, Vasant Honavar, Alexandre M.J.J. Bonvin, Li C. Xue, 2020, Bioinformatics on p. 112-121

Explainable Multivariate Time Series Classification: A Deep Neural Network Which Learns to Attend to Important Variables As Well As Time Intervals

Tsung Yu Hsieh, Suhang Wang, Yiwei Sun, Vasant Honavar, 2021, on p. 607-615

Yasser El-Manzalawy, Tsung Yu Hsieh, Manu Shivakumar, Dokyoon Kim, Vasant Honavar, 2018, BMC Medical Genomics on p. 71

Yimin Zhou, Yiwei Sun, Vasant Honavar, 2019, on p. 283-293

Yasser El-Manzalawy, Drena Dobbs, Vasant G. Honavar, 2017, on p. 255-264

Yiwei Sun, Suhang Wang, Tsung Yu Hsieh, Xianfeng Tang, Vasant Honavar, 2019, on p. 3527-3533

Yuchen Hou, Congcong Wu, Dong Yang, Tao Ye, Vasant G. Honavar, Adri C.T. Van Duin, Kai Wang, Shashank Priya, 2020, Journal of Applied Physics

News Articles Featuring Vasant Honavar

Huck researchers reflect on the 2024 Nobel Prize in Chemistry

This month, the Nobel Prize in Chemistry was awarded to three scientists credited with historic breakthroughs surrounding proteins and their structures. Three Huck researchers working on similar challenges chime in with their thoughts.

ICDS Day seeks to amplify synergy for interdisciplinary research opportunities

Oct. 23 event aims to bring together faculty, students and industry professionals to foster innovation and interdisciplinary collaboration.

ICDS associate director's work driven by unanswered fundamental questions in AI

The work of Vasant Honavar, the Dorothy Foehr Huck and J. Lloyd Huck Chair in biomedical data sciences and artificial intelligence (AI) and a professor of data science in the College of Information Sciences and Technology professor of data science, is driven by answering fundamental questions using machine learning.

$20M NSF grant to support center to study how complex biological processes arise

A $20 million grant from the U.S. National Science Foundation (NSF) will support the establishment and operation of the National Synthesis Center for Emergence in the Molecular and Cellular Sciences (NCEMS) at Penn State.

Millennium Café series to feature special editions in October, November

The Millennium Café, held every Tuesday by the Materials Research Institute (MRI) featuring two talks by Penn State researchers that serve as an exchange of ideas and solutions, will hold three special sessions in October and November.

Vasant Honavar named Huck Chair in Biomedical Data Sciences and AI

Vasant Honavar, professor in the College of Information Sciences and Technology, has been named the Dorothy Foehr Huck and J. Lloyd Huck Chair in Biomedical Data Sciences and Artificial Intelligence by the University’s Huck Institutes of the Life Sciences.

Researchers deploy AI to detect bias in AI and humans

Researchers have developed a tool using artificial intelligence (AI) to detect unfair bias in protected areas such as race or gender. The tool could be used in finding bias in AI systems or even bias by human decisions makers, according to the researchers at Penn State and Columbia University.

What is bias in AI really, and why can’t AI neutralize it?

Selection algorithms everywhere are exhibiting traits that appear to be racist, sexist, and otherwise discriminatory. Have neural networks already developed their own neuropathy? Or are people somehow the problem?

AI to fight unfair discrimination

Researchers developed a new artificial intelligence (AI) tool for detecting unfair discrimination such as race or gender.

Penn State researchers develop bias-detecting technology

Researchers at Penn State and Columbia University have developed artificial intelligence technology that can detect unfair discrimination within specific demographics.

Artificial intelligence tool can identify gender and racial bias

Scientists have developed a new artificial intelligence (AI) tool for detecting unfair discrimination—such as on the basis of race or gender.

Researchers Create New AI Tool for Detecting Unfair Discrimination

Penn State and Columbia University researchers have created a new artificial intelligence tool to detect unfair discrimination based on gender and race. For example, a long-standing concern of civilized societies has been preventing unfair treatment of individuals based on gender, race, or ethnicity.

US researchers create AI tool that can detect discrimination on basis of race, gender

A team of researchers at Pennsylvania State and Columbia University created an artificial intelligence (AI) tool for detecting discrimination with respect to a protected attribute, such as race or gender.

'AI will see you now': Panel to discuss the AI revolution in health and medicine

​This month’s CyberScience Seminar, organized by the Institute for CyberScience (ICS), will be held from 1:30–3 p.m. on Thursday, April 11, in 233B HUB-Robeson Center and will feature a panel of Penn State experts who will discuss the benefits — and the risks — of using AI in the healthcare industry.​

Is artificial intelligence affecting the job market?

The term Artificial Intelligence elicits images of cyborgs and terminators; human-like robots intent on pursuing death and destruction. Hollywood representations distort what AI really is and the technological achievements that scientists are making.