Jure Leskovec.
I am Associate Professor of Computer Science at Stanford University. My research focuses on mining and modeling large social and information networks, their evolution, and diffusion of information and influence over them. Problems I investigate are motivated by large scale data, the web and on-line media.
I am also Investigator at the Chan Zuckerberg Biohub.
What's new
- Tutorial on Deep Learning for Network Biology. Held at ISMB 2018 (July 6, Chicago, IL).
- Tutorial on Representation Learning on Networks. Held at WWW 2018 (April 24, Lyon, France).
- Wiki Workshop 2018. A forum bringing together researchers exploring all aspects of Wikipedia and other Wikimedia sites. Held at WWW 2018 (April 24, Lyon, France).
- MIS2: Misinformation and misbehavior mining on the Web. Workshop held at WSDM 2018.
- Tutorial on Antisocial Behavior On The Web: Characterization And Detection with Srijan Kumar, Justin Cheng. Held at WWW 2017 (April 2, Perth, Australia).
- Wiki Workshop 2017, A forum bringing together researchers exploring all aspects of Wikipedia and other Wikimedia sites. Held at WWW 2017 (April 3, Perth, Australia).
- Teaching the Mining Massive Datasets MOOC on Coursera.
- With Anand Rajaraman and Jeff Ullman we are working in a new edition of Mining of Massive Datasets book. PDFs are at MMDS.org
Latest publications
- Network enhancement as a general method to denoise weighted biological networks. Nature Communications, 2018.
- Embedding Logical Queries on Knowledge Graphs. NIPS, 2018.
- Graph Convolutional Policy Network for Goal-Directed Molecular Graph Generation. NIPS, 2018.
- Hierarchical Graph Representation Learning with Differentiable Pooling. NIPS, 2018.
- Dynamic Network Model from Partial Observations. NIPS, 2018.
- Drive2Vec: Multiscale State-Space Embedding of Vehicular Sensor Data. ITSC, 2018.
- Prioritizing Network Communities. Nature Communications, 2018.
- GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Models. ICML, 2018.
- Graph Convolutional Neural Networks for Web-Scale Recommender Systems. KDD, 2018.
- Learning Structural Node Embeddings via Diffusion Wavelets. C. KDD, 2018.
- Higher-Order Clustering in Networks. PRE, 2018.
- Modeling Polypharmacy Side Effects with Graph Convolutional Networks. Bioinformatics, 2018.
- Do Diffusion Protocols Govern Cascade Growth? ICWSM, 2018.
- Pixie: A System for Recommending 3+ Billion Items to 200+ Million Users in Real-Time. WWW, 2018.
- Community Interaction and Conflict on the Web. WWW, 2018.
- Modeling Interdependent and Periodic Real-World Action Sequences. WWW, 2018.
- I’ll Be Back: On the Multiple Lives of Users of a Mobile Activity Tracking Application. WWW, 2018.
- Modeling Individual Cyclic Variation in Human Behavior. WWW, 2018.
- Data-Driven Model Predictive Control of Autonomous Mobility-on-Demand Systems. ICRA, 2018.
- Accurate Influenza Monitoring and Forecasting Using Novel Internet Data Streams: A Case Study in the Boston Metropolis. JMIR Public Health and Surveillance, 2018.
- Large-scale analysis of disease pathways in the human interactome. Pacific Symposium on Biocomputing, 2018.