Artificial Intelligence for Drug Discovery and Environmental Sciences

Authors

  • Supratik Mukhopadhyay Louisiana State University
  • Alvin Chris
  • Bess Adam

DOI:

https://doi.org/10.32473/flairs.38.1.139104

Abstract

Addressing global health challenges and environmental threats requires innovative technological solutions.
Despite advances in medicine, millions suffer from conditions lacking effective treatments, while antibiotic resistance grows and traditional drug development pipeline remains slow and costly.
DeepDrug, our AI-powered drug design pipeline, accelerate therapeutic discovery by efficiently analyzing vast datasets to identify promising compounds.
Simultaneously, climate change manifests through increasing natural disasters, pollution, habitat destruction, and agricultural disruption, threatening both human civilization and biodiversity.
Our research demonstrates how artificial intelligence can address these dual challenges through advanced data analysis, predictive modeling, and decision support systems.
We present applications ranging from drug discovery to environmental monitoring, including understanding satellite imagery, wildfire management, and predicting permafrost changes.

Author Biography

Supratik Mukhopadhyay, Louisiana State University

Supratik Mukhopadhyay is full Professor at Louisiana State University (LSU) at the Center for Computation and Technology and a Data Science Fellow at the Office of Data and Strategic Analytics. Prof. Mukhopadhyay led the DeepDrug team for automated drug discovery using Artificial Intelligence to semifinalist standing in the prestigious AI XPRIZE competition (among 147 teams worldwide), the world's top competition for using AI for solving moonshot challenges. Combination therapy discovered by the DeepDrug Artificial Intelligence Platform for COVID-19 progressed to human trials at the Riverside University Health System, California.
Apart from Drug Discovery, Prof. Mukhopadhyay has worked on AI for agriculture, education, port and supply chain security, satellite image understanding, video and image analytics, design of intelligent buildings and transportation systems, wildfire prediction and detection, conservation of endangered species, intelligent cyber-physical-human systems, etc. His DeepSat framework for satellite imagery understanding influenced NASA Earth Exchange. In the last 16 years, Prof. Mukhopadhyay has garnered more than $9 million in research grants. His research has been funded by the NSF, DARPA, ARO, ONR, NGA, NASA, DOE, USDOT, NRL, USDA, state agencies, nonprofit foundations, and private industry. Prof. Mukhopadhyay has published around 135 refereed publications in reputed journals and conferences. He has been awarded 4 US Patents and has 8 US patents pending. He has received numerous awards for his research. He cofounded a startup Ailectric for commercializing his research on sound, video, and image analytics. He serves as an associate editor for IEEE Transactions on Artificial Intelligence and Remote Sensing letters and has served in the program committees of AAAI.

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Published

14-05-2025

How to Cite

Mukhopadhyay, S., Chris, A., & Adam, B. (2025). Artificial Intelligence for Drug Discovery and Environmental Sciences. The International FLAIRS Conference Proceedings, 38(1). https://doi.org/10.32473/flairs.38.1.139104

Issue

Section

Invited Talk Papers/Abstracts