Ravi StarzlProgram Co-Director
Dr. Ravi Starzl specializes in the computational analysis and modeling of complex information-driven systems, with experience in such diverse domains as biotechnology, financial systems, and Internet topologies. His core competencies include software engineering, machine learning, mathematical modeling, Big Data systems, and several areas of biology.
Dr. Starzl has extensive experience with the computational and mathematical methods integral to the effective acquisition, management, and utilization of large amounts of information. Having led several massive data analysis projects – with data sets as large as 100+TB – Dr. Starzl is fluent in the methods of Big Data analytics, and is an active researcher in the area of parallelization of machine learning methods for Big Data. He also has extensive experience with many biotechnology and industrial technology quantification platforms, immunological and transplantation methods, as well as general clinical practices and healthcare management systems. Dr. Starzl also has direct experience in entrepreneurial biotechnology development and management.
For example, Dr. Starzl has conducted leading edge research into the elucidation of patterns of communication and function in the immune system by adapting and extending analytic techniques that have proven successful in areas with similar types of complexity, such as human language and finance, and is further extending his work into areas that can likewise be addressed by his analytic methodology.
Dr. Starzl’s typical investigational methodology is to pursue research objectives that deliver findings of practical significance as well as findings that advance fundamental understanding, via a multi-disciplinary systems approach using mathematics, computer science, domain knowledge, and empirical experience, yielding an iterative processes where both analytic findings and empirical observations can quickly infuse each other with meaning, and which can help guide the direction of investigation. This process can accelerate the identification and elucidation of key mechanisms, as well as enabling more effective model bootstrapping by using existing knowledge of a system. Ultimately, this allows a more rapid development or validation of new strategies, processes, or products.
Dr. Starzl is a Systems Scientist in the Language Technologies Institute at Carnegie Mellon University. He received his doctoral degree in Language and Information Technologies from the School of Computer Science at Carnegie Mellon University in 2012. At In addition to his research at CMU, Dr. Starzl develops and teaches classes on the topics of Big Data, biotechnology, and advanced software development. Prior to his academic work, Dr. Starzl held positions in private concerns such as University of Pittsburgh Medical Center and United Therapeutics Corporation. He has also participated in the founding, growth, and sale of several biotechnology and high-tech startups.
Updated 3 years ago.