Principal Investigator

Tae Hyun Hwang

I am the first Endowed Director in AI Research at Vanderbilt University Medical Center, leading the Molecular AI Initiative to unite artificial intelligence with molecular biology for precision medicine. My laboratory develops next-generation AI systems for 3D and 4D molecular modeling, live imaging, and spatial omics to predict and guide therapeutic response. We are advancing AI-driven discovery for antibody–drug conjugates (ADCs), cellular therapy and other novel therapeutics and expanding our molecular AI platform to organ transplantation and diabetes. Our goal is to build intelligent molecular systems that transform how we understand, diagnose, and treat human disease—through innovation, collaboration, and translation to the clinic.

Education

UNIVERSITY OF MINNESOTA TWIN CITIES
Ph.D., Computer Science, 2011

INHA UNIVERSITY, KOREA
B.E., Computer Science, 2004

Research Scientist

Changjin Hong

I am interested in developing novel algorithms and high-quality informatics pipelines to analyze multi-omic, high-throughput data to make a high impact in aiding disease diagnosis and therapy. My current research projects include:

• Alternative polyadenylation associated with diseases

• Prioritizing disease-causing genes with patient phenotypes

• Analysis of the gut microbiome

Education

UNIVERSITY OF MINNESOTA TWIN CITIES
Ph.D., Electrical Engineering, 2008

HANYANG UNIVERSITY, KOREA
B.S., Electrical and Computer Engineering, 1999

Research Scientist

Sunho Park

My research interest is to develop machine learning models on highly complex bio-medical data related to cancer. For example, I have developed deep Gaussian process (DGP)-based prediction models of microsatellite instability (MSI) status using super-high-resolution Hematoxylin and Eosin (H & E) stained whole slide images (MSI is a known biomarker for immunotherapy in multiple cancer types). I am also interested in spatially resolved transcriptomic (including protein markers) which enables us to capture the genetic information of cancer in the spatial contexts. My goal is to develop not only accurate prediction models but also pattern identification methods which eventually can lead to targetable biomarkers.

Education

POHANG UNIVERSITY OF SCIENCE AND TECHNOLOGY, KOREA
Ph.D., Computer Science, Feb. 2013

KOREA UNIVERSITY, KOREA
B.S., Electrical, Electronics and Radiowave Engineering, 2004

Associate Data Science Analyst

Minji Kim

My research interests are in applying deep learning in biomedical fields.

Education

Texas A&M University-Commerce
M.S., Computer Science, 2021

Hongik University, Korea
B.S., Electronic and Electrical Engineering, 2019

Graduate Student

Jean René Clemenceau

My interests are on translational research focused on utilizing computational techniques to interrogate the tumor-immune microenvironment with the ultimate goal improving patient outcomes. My approaches are based on integrating spatial transcriptomics, proteomics, tissue imaging and single cell technologies in the search for actionable biomarkers.

Education

Cleveland Clinic Lerner College of Medicine
Ph.D., Molecular Medicine, Exp. 2024

Baylor University
B.S., Informatics, 2013

Research Associate

Inyeop Jang

My research interest are in deep learning based Medical Image Processing.

Education

Gwangju Institute of Science and Technology, Korea
Ph.D. 2013, M.S. 2008, Mechatronics

Sejong University, Korea
B.E., Computer Science and Engineering, 2006

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If you're interested in implementing the latest artificial intelligence and machine learning technologies to biomedical research while having access to the full spectrum of real-patient data in a first-class institution, get in touch!

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