Modeling interdisciplinary citation dynamics across subfields of sciences. William L. Hamilton, Rex Ying, Jure Leskovec. I am a first year PhD student at CS Stanford. "Too much of a Good Thing?” Foreign Policy, 18 December 2013 (with Ruben Enikolopov). January 1st, 2016. Jure Leskovec; Conference, WWW 2018. TextGarden: our text mining library . • Used language and social network features to classify fictional and real relationshipswith scikit-learn, NLTK, and Keras. Advisor: Jure Leskovec. • Advised by David Jurgens in the Stanford Network Analysis Project (PI: Jure Leskovec)and NLP group (PI: Dan Jurafsky). During my undergraduate, I worked with Prof. Shou-De Lin at National Taiwan University, Prof. Jian Tang at MILA, and Prof. Jure Leskovec at Stanford. Keyulu Xu, Weihua Hu, Jure Leskovec, and Stefanie Jegelka. PhD Study, Research School of Computer Science, The Australian National University, Australia (2011 - 2015) His research advances computational methods that leverage large-scale behavioral data to extract actionable insights about our lives, health and happiness through combining techniques from data science, social network analysis, and natural language processing. Teaching load committee, 2006-2007. Advisors: Dan Jurafsky and Jure Leskovec Thesis: Representation Learning Methods for Computational Social Science MSc in Computer Science Graduated: October 2014 McGill University, Montreal, QC, Canada Advisor: Joelle Pineau Thesis: Compressed Predictive State Representation BSc in Computer Science Graduated: May 2013 OFFICE ADDRESS University of Chicago . Chicago, IL 60637 (773) 702-3242, SSA (773) 834-0811, Harris School . Research on hierarchical representation learning. Knowledge-aware Graph Neural Networks with Label Smoothness Regularization for Recommender Systems. [link] Research Intern, Microso Research Worked with Susan Dumais, Eric Horvitz, and James W. Pennebaker Examining audience configurations in emailing 2019 Research Fellow, Crisis Text Line In collaboration with Cristian Danescu-Niculescu-Mizil, analyzing crisis October, 2017. "The structural roots of group influence: Social closure vs. structural diversity.” Working Paper. 2019. 1 FOTINI CHRISTIA MIT Political Science, 77 Massachusetts Avenue, Room E53-417, Cambridge, MA 02139, ACADEMIC POSITIONS October 2020-present: Director Sociotechnical Systems Research Center, IDSS, MIT Project types: Data analysis/Modeling project: Discovers interesting relationships within a significant amount of data Algorithmic project that extends/builds on what we learned in class Extend/Improve/Speed-up some existing algorithm Define a new problem and solve it 3/14/2013 Jure Leskovec & Anand Rajaraman, Stanford CS345a: Data Mining 4 Summer 2017 Max Planck Institute for Software Systems, Kaiserslautern, Research Intern Research on stochastic optimal control. Advisor: Yoav Shoham. McGill University, Montreal, Canada 2004{2008 B. Eng. Community Content and Behavior After Massive Growth 2017 Zhiyuan Lin, Niloufar Salehi, Bowen Yao, Yiqi Chen, Michael Bernstein; Conference, AAAI ICWSM 2017. e-mail: ude.dscu.gne@yeluacmj New: Amazon 2018 dataset We've put together a new version of our Amazon data, including more reviews and additional metadata The core of human cognition lies in the structured, reusable concepts that help us to rapidly adapt to new tasks and provide reasoning behind our decisions. JENS LUDWIG. • Modeling Social Networks with Node Attributes using the Multiplicative Attribute Graph Model: by Myunghwan Kim and Jure Leskovec, The 27th Conference on Uncertainty in … Community Interaction and Conflict on the Web Srijan Kumar, William L. Hamilton, Jure Leskovec, Dan Jurafsky. Hongwei Wang, Fuzheng Zhang, Mengdi Zhang, Jure Leskovec, Miao Zhao, Wenjie Li, Zhongyuan Wang. Undergraduate mentor, 2003-2008. International Conference on Learning Representations (ICLR), 2020. Hardware. If you would like to learn more about me, please see my [ CV] or contact me at sunfanyun [at] CV Pros ; Gas Gauge ... but we only lose around 40% of the visits when compared to a fully reopening with usual maximum occupancy,” Jure Leskovec, an … I am currently serving as the co-director of the Data Science Initiative with Jure Leskovec. I am a third-year Computer Science Ph.D. student at Stanford, advised by Prof. Jure Leskovec. . 2015 (with Leon Yao, Stephen Wittels and Jure Leskovec). “What Can Civil War Scholars Tell US about the Syrian Conflict,” appeared in The Political Science of Syria’s War, POMEPS Briefings in collaboration with Foreign Policy, 18 December 2013. Many GNN variants have been proposed and have achieved state-of-the-art results on both node and … How Powerful are Graph Neural Networks?. However, existing meta-learning … Stochastic Training of Graph Convolutional Networks with Variance Reduction. DPGN: Distribution Propagation Graph Network for Few-shot Learning. Himabindu Lakkaraju, Jure Leskovec. MIR: MIR is a WAP (web on cell phones) application for reading email from various IMAP email accounts.Simple and efficient. Specialization: Algorithmic game theory. Proceedings of the International Conference on … 22.The Local Closure Coefficient: A New Perspective On Network Clustering. Developing algorithms that are able to generalize to a novel task given only a few labeled examples represents a fundamental challenge in closing the gap between machine- and human-level performance. Written in Python, available under GPL. Acceptance rate: 14%. in Software Engineering (with distinction). GNNs follow a neighborhood aggregation scheme, where the representation vector of a node is computed by recursively aggregating and transforming representation vectors of its neighboring nodes. A Tight Analysis of Greedy Yields Subexponential Time Approximation for Uniform Decision Tree. 1155 thEast 60 Street . KDD 2019. paper; Yu Gong, Yu Zhu, Lu Duan, Qingwen Liu, Ziyu Guan, Fei Sun, Wenwu Ou, Kenny Q. Zhu. If you are interested in any of these positions, please send your full CV and a short (i.e., one page) cover letter detailing your research background and interests to with the subject line “POSTDOC APPLICANT”. Breadth-First Search Optimization Stanford, USA Wang, Dan J. and Jure Leskovec. I am currently pursuing a PhD in Computer Science (CS) at Stanford University, advised by Prof. Jure Leskovec and Prof. Johan Ugander.Previously, I completed my undergrad at Columbia University, where I majored in CS and concentrated in Sociology, and was advised by Prof. Kathy McKeown. ICML 2018. paper. TIM ALTHOFF CURRICULUM VITAE PaulG.AllenSchoolofComputerScience&Engineering UniversityofWashington Box352355,3800EStevensWayNE Seattle,WA98195,USA Adaptive Sampling Towards Fast Graph Representation Learning. Jianfei Chen, Jun Zhu, Le Song. Graph Neural Networks (GNNs) are an effective framework for representation learning of graphs. Tel/ Whatsapp 0735543661 (apel de L-V de la 09.00 pina la 17.00, trimiterea cv-urilor se face la adresa de email Sc Rad-Trans Srl din Bacau angajeaza pentru activitatea de deszapezire in Botosani, Vaslui si Neamt soferi categoria C, C + E. CV la, fax 0234510263, tel 0745125926 intre orele 18-20. Curriculum Vitae April, 2018 . In ICLR. Stanford University, Stanford, CA, USA 2008{2010 M.S. Julian McAuley Associate Professor. Teaching & Advising NeurIPS 2018. paper code Tim Althoff is an assistant professor in the Paul G. Allen School of Computer Science & Engineering at the University of Washington. Advised by Rui Li and Jure Leskovec. Wang, Dan J. Zarya: the BIG machine, donated by HP: 4 processors, 32GB ram, 1TB disk space. Google Scholar; Ling Yang, Liangliang Li, Zilun Zhang, Xinyu Zhou, Erjin Zhou, and Yu Liu. EDUCATION Ph.D. Economics, Duke University, Durham, NC 1994 Room 4102 Computer Science Department @ UCSD. Lakkaraju, Jure Leskovec and Jens Ludwig, NBER Working Papers 23180, National Bureau of Economic Research, Inc. “The Theory is Predictive, but is it Complete? Undergraduate curriculum committee, 2004-2010. in Computer Science in 2018, both from the University of Tokyo, where I worked with Prof. Masashi Sugiyama on machine learning and Prof. Hirosuke Yamamoto on information theory. Stanford Network Analysis Platform (SNAP) is a general purpose network analysis and graph mining library.It is written in C++ and easily scales to massive networks with hundreds of millions of nodes, and billions of edges. Interpretable Decision Sets: A Joint Framework for Description and Prediction. in Mathematical Engineering in 2016, and an M.S. April 23, 2018 - April 27, 2018, Lyon, France Better When It Was Smaller? I am serving a three-year term as Statistics Department Chair. Software. Proceedings of WWW, 2015. SNAP for C++: Stanford Network Analysis Platform. An Application to Human Perception of Randomness,” joint with Jon Kleinberg and Annie Liang, draft, 2015. Wenbing Huang, Tong Zhang, Yu Rong, Junzhou Huang.

jure leskovec cv

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