Machine Learning

In Drug Discovery & Development


Mission


Over the past decade, machine learning has achieved remarkable successes in various research domains, including computer vision, natural language processing, and robotics learning. Artificial intelligence driven by machine learning algorithms is rapidly gaining popularity in the field of drug discovery and development. However, given the complexity of human biology, applying AI to drug discovery is significantly more challenging than image classification! Our group is formed by members with diverse expertise and research background to fullfil three key objectives:

  • Develop innovative approaches to incorporate biochemical knowledge into the development of AI algorithms, enable data-to-knowledge transition, and exploit the knowledge derived from data for drug development.

  • Nurture multidisciplinary collaborations among the different stakeholders in the drug discovery fields, and unite researchers of similar interests at Connecticut to turn the impossible into possible.

  • Train the next generation of life science professionals to be prepared for the big data and AI revolution. Educate computational scientists with biological and chemical knowledge for data-driven drug discovery research.

Projects


Drug Representation

Property Prediction

Chemical Reaction

Feature Extraction

Team


Jinbo Bi

Professor at UCONN CSE. Ph.D. in Mathematics. Expertise in machine learning, big data analytics, computer vision, and medical informatics.

Minghu Song

Yale Center of Molecular Discovery, Ph.D. in Organic Chemistry from RPI and M.S. in Data Science from UC Berkeley. Expertise in computer-aided drug discovery.

Chunjiang Zhu

Postdoctoral at University of Connecticut. He obtained his Ph.D. in Computer Science at the City University of Hong Kong, expertise in data science and data analytics.

Chao Shang

Ph.D. Student at University of Connecticut. Expertise in machine learning and deep graph learning using large-scale datasets, with an emphasis on healthcare informatics.

Qinqing Liu

Ph.D. student in CSE, University of Connecticut. M.S. in Statistics and B.S. in Mathematics. Expertise in machine learning, algorithm and statistical inference.

Xinyu Wang

Undergraduate student from the University of Connecticut. Interested in machine learning, data analysis, mathematical modeling and drug discovery.

John Wohl

Undergraduate student at the University of Connecticut. Interested in dimension reduction, computer vision, autoencoders, and software development.

Kieran Clarke

Undergraduate student from the University of Connecticut. Interested in machine learning and doing work on classification algorithms for a drug discovery project.

Jay Patel

Undergraduate student at the University of Connecticut. Interested in machine learning, software development, and medical informatics.

Let's Get In Touch!


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