Jure Leskovec is a distinguished Slovenian-American scholar renowned for his transformative contributions to the field of network analysis and machine learning systems. He currently serves as Professor of Computer Science at Stanford University, where he is affiliated with the Stanford AI Lab, the Machine Learning Group, within which he leads his own research group, and the Center for Research on Foundation Models. Following completion of his bachelor's degree in computer science at the University of Ljubljana, Slovenia, he earned his PhD in machine learning from Carnegie Mellon University in 2008, subsequently conducting postdoctoral research at Cornell University from 2008 to 2009 under Jon Kleinberg. His professional journey includes a pivotal role as Chief Scientist at Pinterest following the acquisition of his startup Kosei, and he currently co-founded Kumo.AI, a machine learning startup with $37 million in funding raised to date.
Professor Leskovec pioneered the field of Graph Neural Networks, creating foundational methodologies that have revolutionized how researchers analyze relational data structures across diverse domains. His development of PyG (PyTorch Geometric), the most widely-used graph neural network library, has provided research and industry communities with essential tools for advancing graph representation learning. His research spans applications from drug discovery and computational biology to social media recommendation systems, with his work being implemented in products at major technology companies including Facebook, Pinterest, Uber, YouTube, and Amazon. During the global pandemic, his research group developed models that were leveraged by multiple countries to inform public health strategies, demonstrating the real-world impact of his scientific contributions.
Leskovec's scholarly contributions have been recognized with prestigious awards including the Microsoft Research Faculty Fellowship, Alfred P. Sloan Fellowship, and Lagrange Prize in 2015, with his work accumulating numerous best paper and 10-year test of time awards at premier research venues. He has mentored numerous students and researchers who have gone on to become leaders in academia and industry, solidifying his role as a key architect in shaping the next generation of AI experts. His recent work focuses on advancing generative AI capabilities within graph structures, addressing fundamental challenges in commonsense reasoning and multi-modal representation learning. As machine learning faces new challenges in education and ethical implementation, Professor Leskovec continues to provide thoughtful leadership, advocating for responsible pedagogical approaches while driving innovation in graph-based artificial intelligence systems.
