Danai Koutra pronounced: dah-NYE
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News |
September 2022: Honored to give a keynote at ECML/PKDD. Many thanks to the organizers for giving me this opportunity! |
Sep 2021-Sep 2022: News overdue -- for my group's latest publications, please check out DBLP and/or Arxiv! |
Jan 2022-Dec 2022: On sabbatical at Amazon (working with researchers and engineers in Karthik Subbian's group). |
Dec 2021: Became an Amazon Scholar. |
July-August 2021: Giving keynote talks at the ACM KDD Applied Data Science track, the VLDB Scalable Data Science Research series, the KDD Outlier Detection and Description (ODD) workshop, and the ICML Workshop on Representation Learning for Finance and E-Commerce Applications. Thanks to all the track chairs and organizers for inviting me to present my group's work! |
May 2021: Received tenure and promoted to (Morris Wellman) Associate Professor! Many thanks to my students, postdocs, mentors, and collaborators for making this possible. |
December 2020: Giving an invited talk on knowledge graph completion with embeddings (and beyond) at the 14th Workshop on Graph-Based Natural Language Processing (TextGraphs-14), COLING. Many thanks to the organizers for the invitation! |
November 2020: Our paper A Hidden Challenge of Link Prediction: Which Pairs to Check?" was among the best paper candidates at IEEE ICDM'20 and invited for publication at KAIS! Congratulations to the lead student author, Caleb! |
October 2020: Honored to be included in the list of '10 women leading the way in data science’<> by Silicon Republic. |
September 2020: Our paper SpecGreedy: Unified Dense Subgraph Detection. received the Best Student Data Mining Award at ECML-PKDD'20. Congratulations to all the co-authors! |
September 2020: Two papers on knowledge graph completion accepted at EMNLP'20, one paper on link prediction accepted at IEEE ICDM'20 and two papers on extending graph neural networks beyond the traditional homophily assumption and neural execution engines accepted at NeurIPS'20. Congratulations to the lead studen authors Tara, Jiong and Yujun! |
September 2020: Gave an invited talk on "Representation Learning Beyond Homophily and Proximity" at the NetSci’20 Satellite: Statistical Inference for Network Models. Thanks to the organizers for the invitation! |
September 2020: Participated as a lecturer in the 5th International Summer School on Data Science (SSDS), where I talked about large-scale graph mining and network summarization. |
August 2020: Honored to receive a SIGKDD Rising Star Award, which is based on an individual's whole body of work in the first five years after the PhD. |
August 2020: Gave an invited talk on "The Power of Summarization in Network Analysis" (video), including knowledge graph analysis at the 16th International Workshop on Mining and Learning with Graphs (MLG) at KDD. : Statistical Inference for Network Models. Thanks to the organizers for the invitation! |
July 2020: Giving an invited talk at the ICML workshop Graph Representation Learning and Beyond. Many thanks to the organizers for the invitation! |
June 2020: Giving an invited talk on graph summarization in representation learning at the SIAM MDS minisymposium on Learning from Data on Networks. Many thanks to the organizers for the invitation! |
June 2020: Our paper "Democratizing EHR Analyses with FIDDLE - A Flexible Preprocessing Pipeline for Structured Clinical Data" is accepted at JAMIA! Congratulations to the students Shengpu Tang, Parmida Davarmanesh, Yanmeng Song, and the wonderful collaborators Jenna Wiens and Michael Sjoding. |
May 2020: One paper on measuring the persistence of activity in evolving networks is accepted at KDD '20. Congratulations to Caleb and Carol! |
April 2020: I founded the M-DICE team ("Data-Informed Cities for Everyone) along with MIDAS fellow Arya Farahi and PhD student Caleb. This is an interdisciplinary team of students that focuses on urban mobility in collaboration with the City of Detroit (Mayor's office) and the World Economic Forum (WEF). We described the partnership in a recent WEF report. |
February 2020: Recognized as a WSDM'20 outstanding senior PC member! |
January 2020: One paper on unifying different refinement tasks in knowledge graphs via summarization is accepted at The Web Conference 2020. Congratulations to Caleb and Carol! |
January 2020: Honored to be named Morris Wellman Faculty Development Professor. |
January 2020: Research fellow Fatemeh Vahedian joins the GEMS Lab! |
December 2019: Congratulations to undergraduate researcher Carol Zheng for winning an honorable mention in CRA's outstanding undergraduate research award program! |
November 2019: Honored to receive a Precision Health Investigator award to gain a better understanding into the time-varying functional connectivity states via network science and deep neural networks. |
November 2019: Giving an invited talk at Tsinghua University. Thanks to Jie Tang for the invitation! |
November 2019: Giving an invited talk at the Institute of Computing Technology, Chinese Academy of Sciences. Thanks to Shenghua Liu for the invitation! |
November 2019: Arya Farahi comes back to Michigan as a MIDAS Data Science Fellow ! |
October 2019: Our paper on Distribution of Node Embeddings as Multiresolution Features for Graphs received the best student paper award at IEEE ICDM'19. Congratulations to my students Mark and Tara, and thanks to the reviewers and the award committee! |
October 2019: Joint paper with MSR on Activity Discovery in the Personal Web accepted at WSDM'20. Congratulations to Tara for leading this effort! |
October 2019: Successfully ran the Explore Graduate Studies in CSE workshop for the second year! We had about 50 undergraduate and MS participants from around the country. Many thanks to all the faculty and student volunteers, staff, and sponsors, without whom this event would not have been possible. |
September 2019: Giving an invited talk on The Power of Summarization in Representation Learning at the Great Lakes Workshop on Data Science. Thanks to the organizers for the invitation! |
September 2019: Giving an invited talk at Advances in managing and mining large evolving graphs (LEG) workshop at PKDD. Thanks to the organizers for the invitation! |
August 2019: Two papers accepted at ICDM'19! The first paper, GLIMPSE introduces the problem of personalized KG summarization, which is motivated by the disparity between individuals’ limited information needs and the massive scale of KGs; the inferred summaries can be stored and utilized on-device, allowing individuals private, anytime access to the information that interests them most. The second paper, RGM, tackles the graph classification problem; it introduces a fast-to-compute feature map that represents a graph via the distribution of its node embeddings in feature space, which has connections to kernel methods. Congratulations to Tara, Mark, Caleb, and our collaborators! |
July 2019: Invited to serve as a tutorial co-chair for ACM KDD'20. |
June 2019: Gave an invited talk at PNNL. Many thanks to Marco Minutoli and Mahantesh Halappanavar for hosting me! |
June 2019: One paper on node representations in higher-order networks (HONs) was accepted at ASONAM'19. Congratulations to Caleb for his first first-author publication! |
June 2019: Our paper, node2bits, is accepted at PKDD'19! It aims to find compact (binary) time- and attribute-aware node representations, which can be used for user stitching or entity resolution. Congratulations to Di and Mark, and our Adobe collaborator, Ryan Rossi! |
June 2019: Our clinical abstract "Democratizing EHR Analyses - A Comprehensive, Generalizable Pipeline for Learning from Clinical Data" is accepted at MLHC'19! Congratulations to the students Shengpu Tang, Parmida Davarmanesh, Yanmeng Song, and the wonderful collaborators Jenna Wiens and Michael Sjoding. |
May 2019: Honored to be selected for IJCAI Early Career Spotlight! Unfortunately though I had to decline due to scheduling conflict. |
May 2019: Slides from my talk on "(Pocket-size) Structural Embeddings in Large-scale Networks" at the "DOOCN-XII: Network Representation Learning" workshop at NetSci'19. Thanks to the organizers for the invitation! |
May 2019: Slides from my talk on "Inference, summarization and interpretation of noisy network data" at the Machine Learning in Network Science satellite at NetSci'19. Many thanks to the organizers for the invitation! |
April 2019: Three papers accepted at KDD'19! They span neural networks for brain data to latent network summarization and representation learning for professional role inference from email networks. Congratulations to Yujun, Jiong, Di, Mark, Tara, Marlena, and all the collaborators who have contributed to these projects! |
April 2019: I'm looking for a postdoc (for 1-2 years) to work on large-scale graph mining in the GEMS Lab. The topic is flexible and will be decided collaboratively based on prior experience and future goals. To apply, please send your CV and cover letter to dkoutra@umich.edu. |
March 2019: Received a gift from Adobe. Thanks Adobe! |
March 2019: I'm thrilled to receive an NSF CAREER award to support my work on multi-scale summarization of networks over time, with applications to knowledge graphs, neuroscience, deep neural networks & social sciences! [Project Website] |
March 2019: Received a gift from Adobe. Thanks Adobe! |
February 2019: Recognized as a WSDM'19 outstanding PC member! Thanks to the SPC members who nominated me! |
January 2019: Project on "Analyzing the Relation between Product Features and Consumer Preferences" was awarded by P&G! This project is in collaboration with co-PIs Rada Mihalcea and David Fouhey. |
January 2019: Received an Amazon research award for "Adaptive Personalized Knowledge Graph Summarization". The project is in collaboration with Davide Mottin. Thanks Amazon! |
December 2018: Our paper on coupled clustering of time-series and networks, which is motivated by the problem of human-trafficking, is accepted at SDM! |
December 2018: Received an MCubed award for "Crowdsourcing Adaptive Video Analysis" with Walter Lasecki and Srinivasaraghavan Sriram! |
December 2018: Invited to serve as a demo co-chair for ACM CIKM'19. |
December 2018: Yujun and Marlena are selected to attend CRA-W Grad Cohort '19! |
November 2018: Invited to serve as a tutorial co-chair for ACM KDD'19. |
November 2018: I am a guest editor for the "Applied Network Science Special Issue on Machine Learning with Graphs", along with Austin Benson, Ciro Cattuto, Shobeir Fakhraei, Vagelis Papalexakis, and Jiliang Tang. Looking forward to receiving your submissions! |
September 2018: Organizing the 4th Explore Graduate Studies in CSE. One hundred students from around the country will get a chance to learn more about the graduate application process and receive 1-1 feedback. Thank you to all the faculty and student volunteers, alumni and amazing UM staff, without whom organizing this event would not have been possible! Also, special thanks to Rackham Graduate School, the College of Engineering and CSE for funding the event! |
August 2018: Our paper on graph alignment based on representation learning is accepted at CIKM! Congratulations to Mark, Haoming, and Tara! |
August 2018: Along with Jilles Vreeken and Francesco Bonchi, I will be presenting our tutorial on "Summarizing Graphs at Multiple Scales: New Trends" at ICDM 2018 (Singapore)! |
July 2018: Received an Army Research Office Young Investigator Award! The project focuses on speeding up the computation of linear-system-based graph methods in distributed and multiquery settings. |
June 2018: Gave talks at Amazon and Google AI, and visited Facebook in the Bay Area. Thanks to my hosts, Christos Faloutsos, Dana Movshovitz-Attias, and Aude Hofleitner! |
June 2018: Gave a talk on multi-source analysis and had fun participating in working groups at Dagstuhl Seminar,"High-Performance Graph Algorithms"! Thanks for the invitation! |
June 2018: Gave a talk on multi-source analysis and had fun participating in working groups at Dagstuhl Seminar,"High-Performance Graph Algorithms"! Thanks for the invitation! |
May 2018: Our paper on career transitions in computing research is accepted at KDD! Congratulations to Tara and Maryam! |
Apr 2018: Received an Adobe Digital Experience Research award. Thanks Adobe! |
Apr 2018: Tara was selected for a prestigious NSF graduate research fellowship. Congratulations! Go GEMS, go blue! |
Apr 2018: Tara was selected to attend CRA-W Grad Cohort '18! |
Apr 2018: Our paper "Biogeography and environmental conditions shape bacteriophage-bacteria networks across the human microbiome" was accepted in PLOS Computational Biology. |
Mar 2018: Co-organizing the 14th MLG workshop (Mining and Learning with Graphs), which is held in conjunction with KDD on August 20th. The deadline for paper submissions is May 8th. Looking forward to receiving your papers! |
Mar 2018: Our paper "GeoAlign: Interpolating Aggregates over Unaligned Partitions" received the best paper runner-up award at EDBT. Congratulations Jie! |
Feb 2018: Our survey on graph summarization was accepted at ACM Computing Surveys! Congratulations to Yike, Tara and Abhilash! |
Feb 2018: Our paper on a unifying approach towards summarizing large graphs was accepted at the Social Networks Analysis and Mining (SNAM) journal. Congratulations to Yike and Tara! |
Jan 2018: Our paper on Hash-based Multiple Graph Alignment was accepted at the Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD). Congratulations to Mark, Wei, Shengjie and Kuan-Yu! |
Dec 2017: Our paper on Flow-based Random Walk with Restart in a Multi-query Setting was accepted at SIAM International Conference on Data Mining (SDM). Congratulations to Yujun for her first-author paper, and Mark and Di for contributing to this work! |
Dec 2017: Elected as the Program Director of the SIAG on Data Mining and Analytics. |
Dec 2017: Invited to serve as a demo co-chair for ICDM 2018. |
Nov 2017: One paper on fusion of multiple geographic data sources accepted at EDBT. Congratulations Jie! |
Nov 2017: Invited to serve as an Associate Editor of ACM Transactions on Knowledge Discovery from Data (TKDD). |
Nov 2017: Our paper on hashing-based network discovery was selected as one of the best papers of ICDM'17 (invited for potential publication at the KAIS Journal, Springer)! Congratulations to my student Tara! |
Nov 2017: I'm on Amazon.com! Well, my work is. My book on Individual and Collective Graph Mining: Principles, Algorithms, and Applications is published! |
Nov 2017: Attending ICDM! I'm co-organizing and running the ICDM PhD Forum. I'm also a keynote speaker at the ICDM workshop on High Performance Graph Data Mining and Machine Learning (HPGDML)", New Orleans, LA. |
October 2017: Talk at NSF- FAST Workshop 2017: Machine Learning for Discovery Sciences, Yerevan, Armenia. |
August 2017: NSF EAGER with Hanghang Tong on Correspondence Discovery in Disparate Networks. Thank you NSF! |
August 2017: Trove.AI grant for Making Sense of Communication-based Social Graphs. Thank you Trove.AI! |
August 2017: Two regular papers accepted at ICDM (one on domain-specific exploratory analysis of graphs and one on hashing-based network discovery)! Congratulations to my students Di and Tara for their first-author papers! |
July 2017: Microsoft Azure Research Award to work on "Interactive and Collective Exploration of Large-scale Graphs". Thanks Microsoft! |
July 2017: Attended the Microsoft Research Faculty Summit -- The Edge of AI! |
June 2017: Invited to serve as an ICDM PhD Forum 2017 co-chair. Encourage your students to submit part of their dissertation work by August 18! |
May 2017: Congratulations to Tara Safavi for winning a Women Techmakers Scholarship (formerly Google Anita Borg Memorial Scholarship)! Tara will be joining GEMS Lab as a PhD students in Fall '17. |
April 2017: Slides on graph summarization available here! Learn about this space and consider contributing! Thanks to everyone who stayed until the very end of SDM to attend the tutorial! =) |
April 2017: Talk on efficient inference of networks from time series data at NetInf '17!. |
Nov 2016: Tutorial on ``Summarizing Large-Scale Graph Data: Algorithms, Applications and Open Challenges'' accepted at SDM 2017! |
Nov 2016: We are accepting proposals for the KDD CUP 2017! The deadline is on December 9. |
Nov 2016: Giving a talk on summarizing networks at the the Hasso Plattner Institute in Berlin. |
Oct 2016: Thank you Intel for the server donation! |
Aug 2016: Won the 2016 ACM SIGKDD Dissertation Award! My dissertation (and the full abstract) is available here. |
Aug 2016: Invited panelist for the workshop Explore Graduate Studies in Computer Science and Engineering, University of Michigan, Ann Arbor (October 8). Apply by September 9! |
Aug 2016: Two papers accepted at the 12th MLG workshop (at KDD)! |
Apr 2016: Invited to serve as KDD Cup 2017 co-chair. We are looking for cool and innovative proposals! :) |
Apr 2016: Invited to serve as SIAM SDM 2017 publicity co-chair. Consider submitting papers, and workshop / tutorial proposals! |
Mar 2016: Co-organizing the 12th MLG workshop (Mining and Learning with Graphs), which is held in conjunction with KDD on August 14th. The deadline for paper submissions is May 27th. |
Mar 2016: Invited talk at the Origins and Future of Pattern Processing and Intelligence: From Brains to Machines Workshop, which is part of the ASU Origins Project. |
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Dec 2015: Elected as secretary of the SIAM Activity Group on Data Mining and Analytics! |
Oct 2015: Received an honorable mention for the SCS Doctoral Dissertation Award, and nominated to ACM for the Doctoral Dissertation Award! |
Aug 2015: Talk at the University of Michigan for visitors from the Qatar Computing Research Institute. |
May 2015: Presenting our paper on controversies and information seeking at WWW! |
May 2015: Our paper on temporal graph summarization was accepted at KDD! |
Feb - May 2015: Invited talks. |
Jan 2015: Visiting the Saarland University and giving a talk on understan-ding large graphs. |
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Dec 2014: Uploaded the slides for our ICDM tutorial here. |
Dec 2014: Giving a tutorial on node and graph similarity at ICDM'14 @ Shenzen, China (with Tina Eliassi-Rad and Christos Faloutsos). |
Nov 2014: Invited to attend the Rising Stars in EECS Workshop @ UC Berkeley. |
Oct 2014: In Hawaii, to advertize Glance and explore UIST'14. |
Sept 2014: Selected to attend the 2nd Heidelberg Laureate Forum in Germany. |
Sept 2014: Invited talk at MLconf, in Atlanta. |
Aug 2014: at KDD, New York. |
May 2014: Events and Controversies in the news (MIT Technology Review, Technology.org)! |
Publications |
[DBLP]
[Google Scholar]
[ Code by the GEMS Lab]
Teaching |
EECS 476 - Data Mining (~60 students), Winter 2020, University of Michigan, Ann Arbor.
EECS 576: Advanced Data Mining, Fall 2019, University of Michigan, Ann Arbor.
EECS 598-008: Advanced Data Mining, Winter 2019, University of Michigan, Ann Arbor.
EECS 498-001 - Data Mining (~60 students), Fall 2018, University of Michigan, Ann Arbor.
EECS 598-008: Mining Large-Scale Graph Data (65 students), Winter 2018, University of Michigan, Ann Arbor.
EECS 498-001 - Data Mining (new course!) (63 students), Fall 2017, University of Michigan, Ann Arbor.
Summarizing Large-Scale Graph Data: Algorithms, Applications and Open Challenges. SIAM SDM 2017, Houston, TX, April 2017.
EECS 484 - Database Management Systems (283 students), Winter 2017, University of Michigan, Ann Arbor.
EECS 598-004: Mining Large-Scale Graph Data (34 students), Fall 2016, University of Michigan, Ann Arbor.
EECS 484 - Database Management Systems (120 students), Winter 2016, University of Michigan, Ann Arbor.
EECS 598 - Graph Mining and Exploration at Scale: Methods and Applications (23 students), Fall 2015, University of Michigan, Ann Arbor.
Node and graph similarity: Theory and Applications. With Tina Eliassi-Rad and Christos Faloutsos. IEEE ICDM 2014, Shenzen, China, December 2014. (acceptance ratio: 22%)
Node similarity, graph similarity and matching: Theory and Applications. With Tina Eliassi-Rad and Christos Faloutsos. SDM 2014, Philadelphia, PA, April 2014. (over 100 researchers attended!)
15-415 Database Applications: TA, Spring 2013 -- Instructor: Christos Faloutsos.
15-381 Artificial Intelligence: Representation and Problem Solving: TA, Fall 2012 -- Instructors: Ariel Procaccia and Emma Brunskill.
Scripts |
Our code and other resources can be found on our github repository. If what you're looking for is not there, feel free to email us directly.
Input: csv file with (x,y,value) triplets
Output: heatmap for scatter data in log-log scale
Code: heatmap.rar
Input: tab-separated file with one observation
per line (each column corresponds to a feature)
Output: the 1D distribution for each feature
all the pairwise 2D distributions
Code: distributionPlots.zip
Code: setEnv.sh
Bio |
Danai Koutra is an Associate Director of the Michigan Institute for Data Science (MIDAS) and an Associate Professor in Computer Science and Engineering at the University of Michigan, where she leads the Graph Exploration and Mining at Scale (GEMS) Lab. She is also an Amazon Scholar. Her research focuses on principled, practical, and scalable methods for large-scale real networks, and her interests include graph summarization, graph representation learning, graph neural networks, knowledge graph mining, similarity and alignment, temporal graph mining, and anomaly detection. She has won an NSF CAREER award, an ARO Young Investigator award, the 2020 SIGKDD Rising Star Award, research faculty awards from Google, Amazon, Facebook and Adobe, a Precision Health Investigator award, the 2016 ACM SIGKDD Dissertation award, and an honorable mention for the SCS Doctoral Dissertation Award (CMU). She holds a patent on bipartite graph alignment, and has 8 award-winning papers in top data mining conferences. Over time, she has held a variety of service roles: She is an Associate Editor of ACM Transactions on Knowledge Discovery from Data (TKDD) and a program co-chair for ECML/PKDD 2023. She was a track co-chair for The Web Conference 2022, a co-chair of the Deep Learning Day at KDD 2022, the Secretary of the new SIAG on Data Science in 2021, and has routinely served in the organizing committees of all the major data mining conferences. She has worked at IBM, Microsoft Research, and Technicolor Research. She earned her Ph.D. and M.S. in Computer Science from CMU, and her diploma in Electrical and Computer Engineering at the National Technical University of Athens.
* Upcoming Travel |
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March--?? 2020: All travel canceled due to the pandemic (which makes it easy to keep this list up-to-date :) ). |
June 2020: SIAM Conference on Discrete Mathematics (invited talk) in Portland, Oregon. |
May 2020: SIAM Mathematics of Data Science Conference (MDS) (invited talk) in Cincinnati, Ohio. |
November 2019: Tsinghua University in Beijing, China. |
November 2019: ICDM in Beijing, China. |
September 2019: Great Lakes Workshop on Data Science, Notre Dame. |
September 2019: PKDD in Wurzburg, Germany. |
August 2019: KDD in Anchorage, Alaska. |
June 2019: Midwest Machine Learning Symposium (MMLS) in Madison. |
May 2019: NetSci 2019 in Vermont. |
May 2019: SIAM SDM 2019 in Calgary. |
November 2018: IEEE ICDM 2018 in Singapore. |
October 2018: Allerton Conference and UIUC. |
August 2018: ACM SIGKDD in London (organizing MLG and presenting our paper on career transitions with Tara). |
June 2018: Amazon and Google, in CA. |
June 2018: Dagstuhl Seminar,"High-Performance Graph Algorithms", Schloss Dagstuhl in Germany |
May 2018: SIAM SDM, San Diego, CA. |
April 2018: Graph Exploitation Symposium, Dedham, MA |
Nov 2017: ICDM", New Orleans, LA |
Oct 2017: NSF- FAST Workshop 2017: Machine Learning for Discovery Sciences, Yerevan, Armenia |
August 2017: Attending KDD in Halifax, CA! I'm involved with the KDD Cup, the MLG workshop and I am presenting our paper on MovieDesign. |
July 2017: Attending the MSR Faculty Summit in Seattle! |
April 2017: Giving a tutorial on graph summarization at SDM in Houston. |
Nov 2016: Giving a talk on summarizing networks at the the Hasso Plattner Institute in Berlin. |
August 28-Sept 2, 2016: BIRS Workshop on Models and Algorithms for Crowds and Networks, Oaxaca, Mexico |
August 13-17, 2016: KDD, San Fransisco, CA |
May 4-7, 2016: SDM, Miami, FL |
April 4-5, 2016: NSF Career Workshop, Virginia |
March 24-25, 2016: Big Ten Women's Workshop, Milwaukee, WI |
March 11-13, 2016: Origins of Pattern Processing, Arizona |
Outreach for diversity in computing (2018-2020):
MIDAS Data Science Summer Camp for High School Students (2019-2020):
Affiliations:
Funding Sources:
Past: