Amitava Roy
University of Montana, MT·Biology
Computational biology, the use of computing to analyze and model biological data and molecules, is growing rapidly, and researchers increasingly need advanced skills that are often hard to learn on one campus. This grant funds a training program, not a research project.
- Fields
Biology
Computer Science
Biochemistry
- Topics
computational biology
computational genomics
bioinformatics
- Grants
- 1 known grant, through Aug 2027
What they work on
- Run three two-week Advanced Studies Institutes in Singapore (2025–2027) that train U.S. graduate students in computational genomics, in silico ligand–protein interaction and biomolecular structure and dynamics, centered on one system such as the glucocorticoid receptor.
- Combine lectures with project-based learning, including small-group projects on the theme system and personal projects proposed by participants, guided by international experts and covering artificial intelligence in computational biology.
- Connect participants with academic and industry researchers in Southeast Asia through A*STAR and industry talks, recruiting from underrepresented groups, rural regions and EPSCoR states, with yearly independent evaluation.
More about the research
It runs three Advanced Studies Institutes (ASIs) for U.S. graduate students, held once a year from 2025 to 2027 in Singapore in collaboration with Singapore's Agency for Science, Technology and Research (A*STAR).
Why it matters
The program aims to give U.S. graduate students hands-on skills in genomics, protein–ligand modeling and biomolecular simulation, along with international research connections. These skills are increasingly needed in academic and industry computational biology. By recruiting from rural regions, EPSCoR states and underrepresented groups, it could widen who enters the field.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Andrew Mesecar
Purdue University, IN·Biochemistry
Coordinate three cancer research programs (Cell Identity and Signaling; Targets, Structures, and Drugs; and Drug Delivery and Molecular Sensing) that link basic discoveries to new therapies and diagnostics.
Assefaw Gebremedhin
Washington State University, WA·Computer Science
Develop robust and trustworthy machine learning algorithms with anomaly-detection features that flag malicious activity in AI systems used in healthcare, autonomous vehicles and smart cities.
Anand Sarwate
Rutgers University-New Brunswick, NJ·Engineering
Design a framework for adding AI capabilities to the COSMOS city-scale programmable wireless testbed so researchers can easily access wireless infrastructure and AI tools for wireless data.
The school
University of Montana: 3 labs on PI Pages, $144M a year on research, 74 research doctorates a year.
Reach out
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