Our Team
Aakash Tripathi
Lead Developer
Department of Machine Learning, Moffitt Cancer Center & Research Institute | Department of Electrical Engineering, University of South Florida
Led the development of the multimodal embedding framework, designed and implemented the neural network architectures, and conducted computational experiments.
Contact: aakash.tripathi@moffitt.org
Asim Waqas
Lead Developer
Department of Machine Learning, Moffitt Cancer Center & Research Institute | Departments of Cancer Epidemiology, Moffitt Cancer Center & Research Institute
Led the molecular processing, and organization efforts, and contributed to the molecular model development.
Contact: asim.waqas@moffitt.org
Matthew B. Schabath
Clinical Advisor
Departments of Cancer Epidemiology, Moffitt Cancer Center & Research Institute
Provided clinical expertise, validated the clinical relevance of the findings, and contributed to results interpretation.
Contact: matthew.schabath@moffitt.org
Yasin Yilmaz
Statistical Advisor
Department of Electrical Engineering, University of South Florida
Provided guidance on algorithm design and statistical analysis.
Contact: yasiny@usf.edu
Ghulam Rasool
Project Lead
Department of Machine Learning, Moffitt Cancer Center & Research Institute | Department of Electrical Engineering, University of South Florida
Conceived and supervised the study, secured funding, and provided overall direction.
Contact: ghulam.rasool@moffitt.org
Acknowledgements
We would like to thank the National Institutes of Health (NIH) and The Cancer Genome Atlas (TCGA) for providing the data used in this project. Additionally, we acknowledge the computational resources provided by Moffitt Cancer Center & Research Institute and the University of South Florida.