Meet the Team

Meet our surgeon scientists involved in Artificial Intelligence, Machine Learning and Natural Language Processing in the Surgical Innovation Center

Arman Kilic MD 

Arman Kilic, M.D.

Cardiothoracic Surgeon & Director

Cardiac Surgery Research Group and Projects 

  • Applying AI to heart transplant allocation in the United States.
  • Utilizing AI and ML for clinical decision support, matching recipients and donors for heart transplants in the U.S. 
  • Developing dynamic ML models to predict mortality in the cardiovascular ICU.
I Bostock MD 

Ian Bostock, M.D. MS

Thoracic Surgeon

  • Utilizing machine learning algorithms to analyze preoperative PET-CT scans to determine the likelihood of complete pathologic response after neoadjuvant chemoradiation in patients with esophageal cancer remission.
T Brothers MD 

Thomas Brothers, M.D.

Vascular Surgeon

  • Developing risk models and providing clinical decision support in peripheral vascular disease.
Dr Thomas Curran 

Thomas Curran, M.D. MPH 

Colorectal Surgeon

  • Utilizing machine learning for personalized venous thromboembolism (VTE) risk prediction and management recommendations for VTE prophylaxis.
Dr Eriksson 

Evert Eriksson, M.D.

Acute Care Surgeon

  • Applying AI to chest wall injury for reconstruction surgery.
  • Utilizing AI to determine factors associated with unstable chest wall injuries.
Heather Evans MD 

Heather Evans, M.D. MS

Acute Care Surgeon

  • Investigating an AI algorithm for automatic detection of  surgical wound infections
Kevin Hughes MD  

Kevin Hughes, M.D.

Surgical Oncologist

Dr Mukherjee 

Rupak Mukherjee, Ph.D. 

Cardiothoracic Surgery Research

  • Utilizing natural language processing to evaluate applications for surgical residency programs.
Dr. Ozhathil, M.D. 

Deepak Ozhathil, M.D. 

Burn Surgery 

  • Utilizing Next Generation Sequencing (NGS) technology to collect data about the microbiome and metagenomics of the burn wound and establish a data and bio-repository.  
Ravi Veeraswamy, MD

Ravi Veeraswamy, M.D. 

Vascular Surgery

  • Applying artificial intelligence for better stroke risk prediction using carotid imaging data.  

Meet the Data and AI Research Team

John Del Gaizo, Ph.D., Lead AI Researcher, leads a team of AI researchers that aims to facilitate AI research in the Harvey and Marcia Schiller Surgical Innovation Center. The team offers AI consultation and prototyping, and access to advanced computational hardware for MUSC Department of Surgery researchers and external collaborators. He has a Ph.D. from the Clemson-MUSC biomedical data science program, years of industrial experience, and extensive knowledge of MUSC data infrastructure and IT capabilities, creating a unique opportunity to be able to support and lead data science efforts in the center.

Brett Welch 

Brett Welch, MBA, MHA 

Program Manager


Khaled Shorbaji. M.D. MPH 

Surgical Outcomes Research Manager

A Alameldin 

Ahmed Alameldin

AI Researcher

Mr Mathi 

Roshan Mathi, MS  

AI Researcher

Learn More About Our Data and AI Scientists 

Brett Welch, MBA, MHA is the program manager for the Harvey and Marcia Schiller Surgical Innovation Center, managing more than 50 projects and facilitating the research from start to finish, including the QI process. Mr. Welch is a data scientist with experience in managing healthcare projects, operational management, and analytics. 

Khaled Shorbaji. M.D. MPH is a biostatistician who manages the surgical outcomes research operations/efforts in the Harvey and Marcia Schiller Surgical Innovation Center. Dr. Shorbaji has a medical degree from Damascus University and a Master's degree in Public Health from Case Western Reserve University. Dr. Shorbaji has an interest in surgical outcomes research. 

Ahmed Alameldin is an AI Researcher who is completing his Master's in Biomedical Data Science at Clemson University. He is a Fulbright Scholar from Egypt with a demonstrated history of working in health wellness who is skilled in R, Python, Machine Learning, and Deep Learning. His interest focuses on Natural Language Processing and its applications in medical text classification, AI Explainability and Fairness of some deep learning models, and Convolutional Neural Networks for medical image classification. 

Roshan Mathi, MS is an AI Researcher with experience in ML and AI. After receiving a master's degree and working at a startup healthcare company, he joined to work on novel approaches to predict healthcare outcomes and to create diagnostic tools for healthcare providers. Over the past year, he had an abstract accepted by the American Heart Association and presented work at national and regional conferences. He is currently working on anomaly detection with time series data and predicting surgical outcomes after organ transplants.