Our Team

Professor Ashish Goel is a distinguished scholar whose expertise in algorithms, computational design, and large-scale systems plays a vital role at The Standard School of Machine Learning (TheSSML). With a primary appointment in Management Science and Engineering and a courtesy appointment in Computer Science at Stanford University, he brings an exceptional interdisciplinary perspective grounded in rigorous mathematical thinking and real-world computational applications.

Professor Goel’s research focuses on the design, analysis, and implementation of algorithms that address complex problems across digital platforms, marketplaces, decision systems, and networked environments. His work contributes foundational tools used in modern computational systems—ranging from randomized algorithms and graph analytics to large-scale optimization and social network design. His research often bridges theory and practice, informing areas such as online platforms, information dissemination, digital democracy, and market mechanisms.

He earned his PhD in Computer Science from Stanford University in 1999, where he developed core expertise in algorithmic theory and computational frameworks. Before returning to Stanford as faculty, he served as an Assistant Professor of Computer Science at the University of Southern California from 1999 to 2002, further deepening his contributions to algorithmic research and teaching.

At TheSSML, Professor Goel helps students understand how algorithmic thinking and machine learning principles can be integrated to build scalable, ethical, and impactful intelligent systems. His approach emphasizes clarity, computational rigor, and innovative application, shaping the next generation of researchers and practitioners who will drive advancements in AI, data science, and technological decision-making.