Jure Leskovec | |
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| Alma mater | University of Ljubljana |
| Awards | Lagrange Prize [1] Alfred P. Sloan Fellowship [2] |
| Scientific career | |
| Fields | Computer Science |
| Institutions | Stanford University |
| Thesis | Dynamics of Large Networks (2008) |
| Doctoral advisor | Christos Faloutsos [3] |
| Notable students | |
Jure Leskovec is a Slovenian computer scientist, entrepreneur and associate professor of Computer Science at Stanford University focusing on networks. He was the chief scientist at Pinterest. [4]
In 2004, Leskovec received a Diploma in Computer Science from the University of Ljubljana, Slovenia, researching semantic networks-based creation of abstracts, using machine learning; in 2008 he received a PhD in Computational and Statistical Learning from the Carnegie Mellon University.[ citation needed ]
After finishing his PhD, Leskovec worked as a postdoctoral fellow at Cornell University for a year. During this time, he was advised by Jon Kleinberg.
After his postdoctoral stint at Cornell University, Leskovec joined the faculty of Stanford University as an assistant professor in the Department of Computer Science in 2009. He was promoted to associate professor with tenure in 2016.
His general research area is applied machine learning and data science for large interconnected systems. His work focuses on modeling complex, richly-labeled relational structures, graphs, and networks for systems at all scales, from interactions of proteins in a cell to interactions between humans in a society. His research finds applications in a variety of settings including commonsense reasoning, recommender systems, computational social science, and computational biology with an emphasis on drug discovery. [5]
Leskovec co-founded a startup called Kosei in 2014 that was acquired by Pinterest in 2015. [6]
Paul Smolensky is Krieger-Eisenhower Professor of Cognitive Science at the Johns Hopkins University and a Senior Principal Researcher at Microsoft Research, Redmond Washington.
Jon Michael Kleinberg is an American computer scientist and the Tisch University Professor of Computer Science and Information Science at Cornell University known for his work in algorithms and networks. He is a recipient of the Nevanlinna Prize by the International Mathematical Union.
The Krasnow Institute for Advanced Study brings together researchers from many disciplines to study the phenomenon known as the mind. A unit of George Mason University, the Krasnow Institute also serves as a center for doctoral education in neuroscience. Research at the institute is funded by agencies such as the National Institutes of Health, the National Science Foundation and the Department of Defense.
Johannes Gehrke is a Technical Fellow at Microsoft focusing on AI. He is an ACM Fellow, an IEEE Fellow, and he received the 2011 IEEE Computer Society Technical Achievement Award and the 2021 ACM SIGKDD Innovation Award. From 1999 to 2015, he was a faculty member in the Department of Computer Science at Cornell University, where at the time of his leaving he was the Tisch University Professor of Computer Science.
Jennifer Tour Chayes is dean of the college of computing, data science, and society at the University of California, Berkeley. Before joining Berkeley, she was a technical fellow and managing director of Microsoft Research New England in Cambridge, Massachusetts, which she founded in 2008, and Microsoft Research New York City, which she founded in 2012.
Reverse image search is a content-based image retrieval (CBIR) query technique that involves providing the CBIR system with a sample image that it will then base its search upon; in terms of information retrieval, the sample image is very useful. In particular, reverse image search is characterized by a lack of search terms. This effectively removes the need for a user to guess at keywords or terms that may or may not return a correct result. Reverse image search also allows users to discover content that is related to a specific sample image or the popularity of an image, and to discover manipulated versions and derivative works.
Foster Provost is an American computer scientist, information systems researcher, and Professor of Data Science, Professor of Information Systems and Ira Rennert Professor of Entrepreneurship at New York University's Stern School of Business. He is also the Director for the Data Science and AI Initiative at Stern's Fubon Center for Technology, Business and Innovation. Professor Provost has a Bachelor of Science from Duquesne University in physics and mathematics and a Master of Science and Ph.D. in computer science from the University of Pittsburgh.
Panagiotis G. Ipeirotis is a professor and George A. Kellner Faculty Fellow at the Department of Technology, Operations, and Statistics at Leonard N. Stern School of Business of New York University.
Robert David Kleinberg is an American theoretical computer scientist and professor of Computer Science at Cornell University.
Jianchang (JC) Mao is a Chinese-American computer scientist and Vice President, Google Assistant Engineering at Google. His research spans artificial intelligence, machine learning, computational advertising, data mining, and information retrieval. He was named a Fellow of the Institute of Electrical and Electronics Engineers (IEEE) in 2012 for his contributions to pattern recognition, search, content analysis, and computational advertising.
Geoffrey J. Gordon is a professor at the Machine Learning Department at Carnegie Mellon University in Pittsburgh and director of research at the Microsoft Montréal lab. He is known for his research in statistical relational learning and on anytime dynamic variants of the A* search algorithm. His research interests include multi-agent planning, reinforcement learning, decision-theoretic planning, statistical models of difficult data, computational learning theory, and game theory.
Gautam Das is a computer scientist in the field of databases research. He is an ACM Fellow and IEEE Fellow.
Wei Wang is a Chinese-born American computer scientist. She is the Leonard Kleinrock Chair Professor in Computer Science and Computational Medicine at University of California, Los Angeles and the director of the Scalable Analytics Institute (ScAi). Her research specializes in big data analytics and modeling, database systems, natural language processing, bioinformatics and computational biology, and computational medicine.
node2vec is an algorithm to generate vector representations of nodes on a graph. The node2vec framework learns low-dimensional representations for nodes in a graph through the use of random walks through a graph starting at a target node. It is useful for a variety of machine learning applications. node2vec follows the intuition that random walks through a graph can be treated like sentences in a corpus. Each node in a graph is treated like an individual word, and a random walk is treated as a sentence. By feeding these "sentences" into a skip-gram, or by using the continuous bag of words model paths found by random walks can be treated as sentences, and traditional data-mining techniques for documents can be used. The algorithm generalizes prior work which is based on rigid notions of network neighborhoods, and argues that the added flexibility in exploring neighborhoods is the key to learning richer representations of nodes in graphs. The algorithm is considered one of the best graph classifiers.
Tina Eliassi-Rad is an American computer scientist and the inaugural President Joseph E. Aoun Professor at Northeastern University. Her research is at the intersection of artificial intelligence, network science, and applied ethics. In 2023, she won the Lagrange Prize for her work on ethical approaches to artificial intelligence.
Himabindu "Hima" Lakkaraju is an Indian-American computer scientist who works on machine learning, artificial intelligence, algorithmic bias, and AI accountability. She is currently an Assistant Professor at the Harvard Business School and is also affiliated with the Department of Computer Science at Harvard University. Lakkaraju is known for her work on explainable machine learning. More broadly, her research focuses on developing machine learning models and algorithms that are interpretable, transparent, fair, and reliable. She also investigates the practical and ethical implications of deploying machine learning models in domains involving high-stakes decisions such as healthcare, criminal justice, business, and education. Lakkaraju was named as one of the world's top Innovators Under 35 by both Vanity Fair and the MIT Technology Review.
A graph neural network (GNN) belongs to a class of artificial neural networks for processing data that can be represented as graphs.
Yixin Chen is a computer scientist, academic, and author. He is a professor of computer science and engineering at Washington University in St. Louis.
Jeanne M. Van Briesen is an American civil engineer who is Vice Provost and the Duquesne Light Company Professor at Carnegie Mellon University. Her research considers the realization of sustainable natural and engineered water systems. She is a Fellow of the American Society of Civil Engineers, Environmental and Water Resources Institute, Association of Environmental Engineering and Science Professors and American Association for the Advancement of Science.
Liang Zhao is a computer scientist and academic. He is an associate professor in the Department of Compute Science at Emory University.
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