Travis Williams

Senior Scientist Biomedical & Clinical Informatics

Location: CoRE Building, 96 Frelinghuysen Road, Room 712 Piscataway, NJ 08854
Phone: (848) 445-5225
Email: tw593@rutgers.edu

Biography
Travis received his PhD in Electrical Engineering from North Carolina A&T State University in 2017. His dissertation, “Advanced Image Classification using Deep Neural Networks,” combined wavelet theory and deep learning to increase the accuracy and efficiency of deep learning algorithms. He worked as a Research Scholar at Memorial Sloan Kettering Cancer Center under Drs. Amber Simpson & Mithat Gönen. His research at MSK applied machine learning to classifying tumors in the pancreas and liver as cancerous, benign, predicting survival, etc.

Currently in his role as a Senior Scientist, he advises professors, medical doctors and
researchers, and students/postdocs/fellows in the areas of machine learning, deep learning, and image processing. Additionally, he creates workshops for the broader Rutgers community on topics of interest in machine learning and image processing. Some projects he has been working on with other researchers include: Prognostic factors for neurological post-acute sequelae of SARS-CoV-2 Infection; Prognostic markers of heart rate variability in neurological conditions; Using multi-modal data fusion to build a predictive model for disease progression in oral potentially malignant disorders.

Skills and Expertise:
Pattern Recognition, Biomedical Informatics, Biomedical Signal Processing, Deep Learning, Digital Signal Processing, Digital Image Processing, Computer Vision

Recent Publications:

1. Williams, Travis and Li, Robert, “Threshout Regularization for Deep Neural Networks”, 2021 IEEE SoutheastCon, March 2021.
2. Travis L. Williams, Lily V. Saadat, Mithat Gonen, Alice Wei, Richard K. G. Do & Amber L. Simpson (2021) “Radiomics in surgical oncology: applications and challenges”, Computer Assisted Surgery, 26:1, 85-96, DOI: 10.1080/24699322.2021.1994014
3. K. A. Harrington, T. L. Williams, S. A. Lawrence, J. Chakraborty, M. A. Al Efishat, M. A. Attiyeh M.D., G. Askan, Y. Chou, A. Pulvirenti M.D., C. A. McIntyre, M. Gonen, O. Basturk, V. P. Balachandran, T. P. Kingham M.D., M. I. D’Angelica, W. R. Jarnagin M.D., J. A. Drebin, R. K. G. Do M.D., P. J. Allen M.D., and A. L. Simpson “A multimodal radiomics and cyst fluid inflammatory markers model to predict preoperative risk in intraductal papillary mucinous neoplasms”, Journal of Medical Imaging 7(3), 031502 (25 June 2020).
4. T. L. Williams, K. A. Harrington, S. A. Lawrence, J. Chakraborty, M. A. Al Efishat, M. A. Attiyeh M.D., G. Askan, Y. Chou, A. Pulvirenti M.D., C. A. McIntyre, M. Gonen, O. Basturk, V. P. Balachandran, T. P. Kingham M.D., M. I. D’Angelica M.D., W. R. Jarnagin M.D., J. A. Drebin, R. K. G. Do M.D., P. J. Allen M.D., and A. L. Simpson “A combined radiomics and cyst fluid inflammatory markers model to predict preoperative risk in pancreatic cystic lesions”, Proc. SPIE 11315, Medical Imaging 2020: Image-Guided Procedures, Robotic Interventions, and Modeling, 113151Q (16 March 2020)
5. Roberts, S., Strome, A., Choi, C., Andreou, C., Kossatz, S., Brand, C., Williams, T., Bradbury, M., Kircher, M., Reshetnyak, Y., Grimm, J., Lewis, J., Reiner, T., “Acid specific dark quencher QC1-pHLIP for multi-spectral optoacoustic diagnoses of breast cancer”, Scientific Reports, 9, 2019.
6. Williams, Travis and Li, Robert, “Wavelet Pooling for Convolutional Neural Networks”, ICLR 2018, April 30 –May 3, 2018.