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Dr. Raghvendra Mall
Computational Biology & Machine Learning Generalist
Google Scholar
Career
Career Transition & Focus
New Role at QCRI
Joining as Senior Scientist (U.S. Equivalent Associate Professor) focusing on extracting meaningful biology via biomedical LLMs.
Research Focus
Designing machine learning techniques for applied sciences, with primary focus on computational biology and computational immunology.
Collaboration
Collaboration Opportunities
Academic Partnerships
Looking to collaborate with M.S. and doctoral students interested in research at the intersection of AI + biologics, focusing on top-tier publications.
Industry Ventures
Open to being an advisor or part of seed-funded startups working at the intersection of AI + biological sciences in cancer and infectious diseases.
Recognition
Recent Achievements & Recognition
1
Strategic Advisor Role
Became Strategic Advisor of Bioinformatics for pre-seed startup Eternal.
2
IEEE Recognition
Awarded prestigious "Computing's Top 30 Early Career Professionals" by IEEE Computer Society.
3
Editorial Positions
Section Editor for Journal of Translational Medicine and Associate Editor for Frontiers in Medicine and Public Health.
Recognition
Competition Success
2.5%
Top Ranking
Team PolyBeasts ranked 53 out of 2240 (Silver Medal) in Neurips Open Polymer Prediction Challenge 2025.
4th
Place Finish
Team Amari ranked 4th in Autoimmune Disease Machine Learning Challenge (Crunch 2).
10%
Top Percentile
Team Patho_omics ranked in top 10% (34 out of 355 teams) in Global AI Hackathon 2025.
Research
Latest Research Publications
1
Cell Chemical Biology (2025)
"A potent NLRP3 inhibitor effective against both MCC950-sensitive and-resistant inflammation" - Impact Factor: 7.2
2
Nature Communications (2025)
"Ferroptosis-activating metabolite acrolein antagonizes necroptosis and anti-cancer therapeutics" - Impact Factor: 14.7
3
WIREs Computational Molecular Science (2025)
"Strategies for Redesigning Withdrawn Drugs to Enhance Therapeutic Efficacy and Safety" - Impact Factor: 16.8
4
Cell (2024)
"NLRP12-PANoptosome activates PANoptosis and pathology in response to heme and PAMPs" - Impact Factor: 67
Tools
Web-Based Research Tools
Web-server for predicting peptide-HLA binding, providing crucial insights for immunological research and vaccine development.
Advanced tool for protein/peptide toxicity prediction, published in Bioinformatics with high-accuracy predictions.
Comprehensive web server for protein property prediction and drug repurposing solutions using deep learning algorithms.
Research
Open Source Contributions
Developed "RGBM" (Regularized Gradient Boosting Machines for Inferring Gene Regulatory Networks), now available on CRAN with comprehensive tutorial documentation.
This package enables researchers to infer complex gene regulatory networks using advanced machine learning techniques.
Career
Professional Experience Timeline
1
Director of Computational Biology (2023-25)
Biotechnology Research Center, Technology Innovation Institute - Leading computational biology initiatives and research teams.
2
Senior Research Scientist (2021-23)
St. Jude Children's Research Hospital, Memphis, TN - Advanced pediatric cancer research through computational approaches.
3
Research Scientist (2018-21)
Qatar Computing Research Institute, Doha - U.S. equivalent Assistant Professor position in computational research.
4
Post-doctoral Researcher (2016-18)
Qatar Computing Research Institute, Doha - Foundation research in machine learning applications for biological sciences.
Academic Background
Academic Foundation
Doctorate Achievement
Finished doctorate Summa Cum Laude with congratulations of Board of Examiners at KU Leuven, Belgium under Prof. Johan Suykens.
Research Focus
Specialized in sparsity in large-scale machine learning, developing kernel-based models for network analysis and data visualization through optimization techniques.
Dr. Mall's journey from academic excellence to industry leadership demonstrates the power of combining theoretical knowledge with practical applications in computational biology and machine learning.
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