Satwik Rajaram is an Assistant Professor in the Lyda Hill Department of Bioinformatics and the Department of Pathology.
Dr. Rajaram's formal training is in theoretical physics. His switch to biology occured during his Ph.D (at the University of Illinois at Urbana Champaign) as he developed statistical-physics-inspired approaches to help humans comprehend high-dimensional biological data.
Dr. Rajaram's post-doctoral research in the joint labs of Drs. Altschuler and Wu (at UTSW and then at UCSF) explored the implications of cellular heterogeneity, primarily through quantitative microscopy. He developed machine learning approaches that automatically identified relevant image phenotypes -sometimes invisible to the human eye- and accurately profiled heterogeneous cellular populations. His work also explored the associated experimental design questions, such as how fews cells are needed to represent a population's heterogeneity reliably?
At UTSW, Dr. Rajaram will develop digital pathology approaches to understand the spatial organization of tumors. By combining machine identified phenotypes and existing pathology scoring within the framework established by cancer biology, he hopes to establish tissue organization itself as a predictive biomarker.
- Digital Pathology
- Intra-Tumor Heterogeneity
- Machine learning applied to tissue images
- Spatial organization of pathological tissue
- Some implications of renormalization group theoretical ideas to statistics
- Rajaram S, Taguchi Y-h, Oono Y Physica D: Nonlinear Phenomena 2005 205 207-214