Specializations

  • Social Networks
  • Causal Inference
  • Computational Computer Science

Biography

Martin Saveski is an incoming Assistant Professor (starting September 2023) at the University of Washington Information School. His research develops tools for analyzing large-scale social data, aiming to provide a better understanding of social structure and behaviors online while also impacting the design of digital social systems. His recent work has focused on reducing political polarization online, improving the quality of online conversations, and causal inference in social systems. His research often falls at the intersections of Social Networks, Machine Learning, and Causal Inference. His work typically appears in venues such as ICWSM, WWW, and KDD, and has included collaborations with researchers at Twitter, Facebook, and LinkedIn. His research has been awarded a best paper honorable mention at WWW ’18 and has been featured in popular media outlets, including The New York Times, NPR, and the MIT Tech Review.

Education

  • Postdoctoral Scholar, Management Science & Engineering, Stanford University, 2023
  • Ph D, Media Arts and Sciences, Massachusetts Institute of Technology, 2020
  • MSC, Data Mining and Knowledge Management, University Pierre and Marie Curie & Polytechnic University of Catalonia, 2013
  • BSC, Computing Science, Staffordshire University, 2010

Awards

  • Best Reviewer - ICWSM: International Conference on Web and Social Media, 2021
  • Rising Star in Data Science - University of Chicago Rising Stars, 2021
  • Best Reviewer - ICWSM: International Conference on Web and Social Media, 2019
  • Best Paper Honorable Mention - WWW: The Web Conference, 2018
  • Scholarship - European Union full scholarship for a two-year Master’s Degree, 2011-2013
  • Scholarship - Macedonian national scholarship for students with advanced achievements, 2008-2010

Publications and Contributions

  • Conference Paper
    Counterfactual Evaluation of Peer Review Assignment Strategies in Computer Science and Artificial Intelligence (2022)
    International Congress on Peer Review and Scientific Publication, Peer Review Congress’22 Authors: Martin Saveski, Steven Jecmen, Nihar B. Shah, Johan Ugander
  • Conference Paper
    Engaging Politically Diverse Audiences on Social Media (2022)
    International Conference on Web and Social Media, ICWSM’22a Authors: Martin Saveski, Doug Beeferman, David McClure, Deb Roy
  • Conference Paper
    Perspective-taking to Reduce Affective Polarization on Social Media (2022)
    International Conference on Web and Social Media, ICWSM’22b Authors: Martin Saveski, Nabeel Gillani, Ann Yuan, Prashanth Vijayaraghavan, Deb Roy
  • Journal Article, Academic Journal
    Algorithmic and Human Prediction of Success in Human Collaboration From Visual Features (2021)
    Nature Scientific Reports, Nature Scientific Reports’21 Authors: Martin Saveski, Edmond Awad, Iyad Rahwan, Manuel Cebrian
  • Conference Paper
    Balanced Influence Maximization in the Presence of Homophily (2021)
    International Conference on Web Search and Data Mining, WSDM'21 Authors: Md Sanzeed Anwar, Martin Saveski, Deb Roy
  • Conference Paper
    Social Catalysts: Characterizing People Who Spark Conversations Among Others (2021)
    Conference on Computer-Supported Cooperative Work and Social Computing, CSCW'21 Authors: Martin Saveski, Farshad Kooti, Sylvia Morelli Vitousek, Carlos Diuk, Bryce Bartlett, Lada Adamic
  • Conference Paper
    The Structure of Toxic Conversations on Twitter (2021)
    The Web Conference, WWW'21 Authors: Martin Saveski, Brandon Roy, Deb Roy
  • Conference Paper
    Testing for Arbitrary Interference on Experimentation Platforms (2019)
    Biometrika, Biometrika’19 Authors: Jean Pouget-Abadie, Guillaume S.J., Martin Saveski, Weito Duan, Souvik Ghosh, Ya Xu, Edo Airoldi
  • Conference Paper
    Me, My Echo Chamber, and I: Introspection on Social Media Polarization (2018)
    The Web Conference, WWW’18 Authors: Nabeel Gillani, Ann Yuan, Martin Saveski, Soroush Vosoughi, Deb Roy
  • Conference Paper
    Detecting Network Effects: Randomizing Over Randomized Experiments (2017)
    International Conference on Knowledge Discovery and Data Mining, KDD'17 Authors: Martin Saveski, Jean Pouget-Abadie, Guillame S.J., Weitao Duan, Souvik Ghosh, Ya Xu, Edo Airoldi
  • Conference Paper
    Human Atlas: A Tool for Mapping Social Networks (2016)
    The Web Conference, WWW'16 Authors: Martin Saveski, Eric Chu, Soroush Vosoughi, Deb Roy
  • Conference Paper
    Topic Modeling in Twitter: Aggregating Tweets by Conversations (2016)
    International Conference on Web and Social Media, ICWSM'16 Authors: David Alvarez-Melis, Martin Saveski
  • Conference Paper
    Tracking the Yak: An Empirical Study of Yik Yak (2016)
    International Conference on Web and Social Media, ICWSM'16 Authors: Martin Saveski, Sophie Chou, Deb Roy
  • Conference Paper
    One-Pass Ranking Models for Low-Latency Product Recommendations (2015)
    International Conference on Knowledge Discovery and Data Mining, KDD'15 Authors: Antonio Freno, Martin Saveski, Rodolphe Jenatton, Cédric Archambeau
  • Conference Paper
    Item Cold-Start Recommendations: Learning Local Collective Embeddings (2014)
    Conference on Recommender Systems, RecSys'14 Authors: Martin Saveski, Amin Mantrach
  • Conference Paper
    The Geography of Online News Engagement (2014)
    International Conference on Social Informatics, Socinfo'14 Authors: Martin Saveski, Daniele Quercia, Amin Mantrach
  • Conference Paper
    Joint Semi-supervised Learning of Hidden Conditional Random Fields and Hidden Markov Models (2013)
    Pattern Recognition Letters, Pattern Recognition Letters’13 Authors: Yann Soullard, Martin Saveski, Thierry Artières
  • Conference Paper
    Automatic Construction of Wordnets by Using Machine Translation and Language Modeling (2010)
    Language Technologies Conference, LTC’10 Authors: Martin Saveski, Igor Trajkovski

Presentations

  • Data Science for Healthier Social Platforms (2022)
    Carnegie Mellon University (Heinz) - Pittsburgh, PA
  • Data Science for Healthier Social Platforms (2022)
    Cornell University (IS) - Ithaca, NY
  • Data Science for Healthier Social Platforms (2022)
    University of Illinois Chicago (CS) - Chicago, IL
  • Data Science for Healthier Social Platforms (2022)
    University of Illinois Chicago (CS) - Urbana-Champaign, IL
  • Data Science for Healthier Social Platforms (2022)
    University of Washington (iSchool) - Seattle, WA
  • Data Science for Healthier Social Platforms (2022)
    Georgia Institute of Technology (CSE) - Atlanta, GA
  • Data Science for Healthier Social Platforms (2022)
    Dartmouth College (CS) - Hanover, NH
  • Engaging Politically Diverse Audiences on Social Media (2022)
    Social AIs working group, Stanford University - Palo Alto, CA
  • Counterfactual Evaluation of Peer-Review Assignment Strategies (2021)
    Conference on Digital Experimentation, MIT (CODE@MIT) - Cambridge, MA
  • Engaging Politically Diverse Audiences on Social Media (2021)
    Computer Science, Carnegie Mellon University - Pittsburgh, PA
  • Engaging Politically Diverse Audiences on Social Media (2021)
    International Conference on Computational Social Science (IC2S2) - Virtual
  • Engaging Politically Diverse Audiences on Social Media (2021)
    Rising Stars in Data Science, University of Chicago - Chicago, IL
  • Engaging Politically Diverse Audiences on Social Media (2021)
    Institute for Communication and Media Studies, University of Bern - Bern, Switzerland
  • Polarization and Toxicity in Political Discourse (2020)
    Twitter - Virtual
  • The Structure of Toxic Conversations (2020)
    Computational Social Science Seminar, Facebook - Virtual
  • The Structure of Toxic Conversations (2019)
    Health, Usage and Behavior team, Twitter - Virtual
  • The Structure of Toxic Conversations (2019)
    Social Analytics Lab, MIT Sloan - Cambridge, MA
  • Detecting Network Effects: Randomizing Over Randomized Experiments (2018)
    International Conference on Computational Social Science (IC2S2) - Evanston, IL
  • Detecting Network Effects: Randomizing Over Randomized Experiments (2017)
    Conference on Digital Experimentation, MIT (CODE@MIT) - Cambridge, MA
  • Detecting Network Effects: Randomizing Over Randomized Experiments (2017)
    Social Analytics Lab, MIT Sloan - Cambridge, MA
  • Detecting Network Effects: Randomizing Over Randomized Experiments (2017)
    Scalable Cooperation Group, MIT - Cambridge, MA