"In light of my multifaceted training as a mathematician, engineer, statistician, and biologist, I hold distinct epistemological beliefs regarding the limits of knowledge and the reliability of various methodologies. As a mathematician, I maintain that any proposition that is true can be proven by a valid argument, and any proposition that cannot be proven is likely false. As an engineer, I hold the conviction that with the right tools and methodology, we can prove any proposition beyond reasonable doubt. As a statistician, I acknowledge the limitations of our knowledge and emphasize the importance of empirical evidence to disprove rather than prove any hypothesis, with the understanding that our knowledge is always provisional and subject to revision in the face of new evidence. Finally, as a biologist, I recognize the intrinsic complexity and variability of living systems, and thus, the inevitable presence of confounding factors that limit our ability to draw reliable conclusions from empirical observations alone. My philosophical stance reflects the unique insights and limitations of each discipline, while recognizing the inherent complexity of the world around us".




Avi (Avinash) is a multidisciplinary researcher with a diverse background in mathematics, engineering, statistics, and biology. He holds a PhD in computer science and has over 13 years of experience developing machine learning methods. Avinash's research has been widely recognized and has received several prestigious awards, including the Michelson Prize by the Human Vaccines Project, the K99 Young Investigator Award from the National Cancer Institute, and the Irving Foundation's recognition as one of the 40 most promising young Cancer Immunology scientists.

Avi's expertise is the product of an international education, with extensive training at Harvard, as well as in India, France, Switzerland, Germany, the US, and Israel. His research is situated at the intersection of data science and cancer immunology, where he is dedicated to developing artificial intelligence and probabilistic approaches that enable a systems-level understanding of tumor and immune microenvironments. Drawing on the cutting-edge research program he developed at Harvard, Avi's work has resulted in several critical discoveries, including the identification of bipotent drugs with dual anticancer potential, a new class of genetic interactions that drive response and resistance to cancer therapies, and Bayesian approaches for identifying genetic determinants of heart failure. Along with supervising a machine learning group of graduate students, Avi collaborates with several leading academic labs and pharmaceutical companies to develop new treatments for advanced cancer patients.

Beyond his research, Avi is also deeply invested in mentoring young students, particularly those from challenging backgrounds. He believes that with dedication, hard work, and passion, anyone can overcome adversity and achieve great things. By sharing his own journey, he hopes to inspire and guide others to find their own path to success.