Publications

You may also review my Google Scholar profile.

Preprints

• Fair clustering for data summarization: Improved approximation algorithms and complexity insights* (Full paper)
  Ameet Gadekar, Aristides Gionis, Suhas Thejaswi
  [Arxiv]

• Diversity-aware clustering: computational complexity and approximation algorithms (Full paper)
  Suhas Thejaswi, Ameet Gadekar, Bruno Ordozgoiti, Aristides Gionis
  [Arxiv]

2024

• Controlling counterfactual harm in decision support systems based on prediction sets (Full paper)
  Eleni Straitouri, Suhas Thejaswi, Manuel Gomez-Rodriguez
  Advances in Neural Information Processing Systems (NeurIPS 2024)
  [ArXiv] [Code]

• Prediction powered ranking of large language models (Full paper)
  Evi Chatzi, Eleni Straitouri, Suhas Thejaswi, Manuel Gomez-Rodriguez
  Advances in Neural Information Processing Systems (NeurIPS 2024)
  [ArXiv] [Code]

• Towards human-AI complementarity with predictions sets (Full paper)
  Giovanni De Toni, Nastaran Okati, Suhas Thejaswi, Eleni Straitouri, Manuel Gomez-Rodriguez
  Advances in Neural Information Processing Systems (NeurIPS 2024)
  [ArXiv] [Code]

• Matchings, Predictions and Counterfactual Harm in Refugee Resettlement Processes (Workshop paper, oral presentation)
  Seung Eon Lee, Nina Corvelo Benz, Suhas Thejaswi, Manuel Gomez Rodriguez
  In Ethical Artificial Intelligence: Methods and Applications workshop @ KDD 2024
  [ArXiv] [Code]

• Controlling counterfactual harm in decision support systems based on prediction sets (Workshop paper)
  Eleni Straitouri, Suhas Thejaswi, Manuel Gomez-Rodriguez
  In Humans, Algorithmic Decision-Making and Society workshop @ ICML 2024
  [ArXiv] [Code]

• Fair column subset selection (Full paper, oral presentation)
  Antonios Matakos, Bruno Ordozgoiti, Suhas Thejaswi
  In Knowledge Discovery and Data Mining (KDD), 2024
  [ArXiv] [Paper] [Code]

• Prediction powered ranking of large language models (Workshop paper)
  Ivi Chatzi, Eleni Straitouri, Suhas Thejaswi, Manuel Gomez-Rodriguez
  In HEAL workshop @ Human Factors in Computing Systems (CHI), 2024
  [ArXiv] [Paper] [Code] [Poster]

2022

• Scalable algorithm designs for mining massive datasets
  Suhas Thejaswi
  PhD Thesis, 2022
  [Thesis] [Slides]

• Clustering with fair-center representation: parameterized approximation algorithms and heuristics (Full paper, oral presentation)
  Suhas Thejaswi, Ameet Gadekar, Bruno Ordozgoiti, Michal Osadnik
  In Knowledge Discovery and Data Mining (KDD), 2022
  [ArXiv] [Paper] [Code] [Slides] [Poster]
  Related blogpost - featured in Kudos research showcase

2021

• Diversity-aware k-median: clustering with fair-center representation (Full paper, oral presentation)
  Suhas Thejaswi, Bruno Ordozgoiti, Aristides Gionis
  In Machine Learning and Knowledge Discovery in Databases-Research Track (ECML PKDD), 2021
  [ArXiv] [Paper] [Code] [Slides]

2020

• Restless reachability problems in temporal graphs
  Suhas Thejaswi, Juho Lauri, Aristides Gionis
  [ArXiv] [code] [Slides] [Video]

• Finding path motifs in large temporal graphs using algebraic fingerprints (Full paper)
  Suhas Thejaswi, Aristides Gionis, Juho Lauri
  In BigData journal (special issue on best of SIAM data mining 2020)
  [ArXiv] [Paper] [Code]

• Pattern detection in large temporal graphs using algebraic fingerprints (Full paper)
  Suhas Thejaswi, Aristides Gionis
  In SIAM International Conference on Data Mining, 2020
  [Paper] [Code] [Slides]
  Best paper candidate
  Invited for a journal publication in best papers of SIAM data mining 2020

2018

• Engineering motif search for large motifs* (Full paper)
  Petteri Kaski, Juho Lauri, Suhas Thejaswi
  In Symposium of Experimental Algorithms (SEA), 2018
  [Paper] [Code] [Slides]

2017

• Scalable parameterised algorithms for two Steiner problems
  Suhas Thejaswi
  Master’s Thesis, 2017
  [Thesis] [Code] [Slides]
  A talk on the process of writing master’s thesis @ Aalto University

*Authors in alphabetical order.