Publications (Google Scholar)

2024

• Prediction-Powered Ranking of Large Language Models (Full paper)
  (with I. Chatzi, E. Straitouri and S. Thejaswi), Neural Information Processing Systems (NeurIPS), Vancouver (Canada), December 2024.

• Towards Human-AI Complementarity with Predictions Sets (Full paper)
  (with G. De Toni, N. Okati, S. Thejaswi and E. Straitouri), Neural Information Processing Systems (NeurIPS), Vancouver (Canada), December 2024.

• Controlling Counterfactual Harm in Decision Support Systems Based on Prediction Sets (Full paper)
  (with E. Straitouri and S. Thejaswi), Neural Information Processing Systems (NeurIPS), Vancouver (Canada), December 2024.

• Designing Decision Support Systems Using Counterfactual Prediction Sets (Full paper, spotlight presentation)
  (with E. Straitouri), 41st International Conference on Machine Learning (ICML), Vienna (Austria), July 2024.

• Towards a Computational Model of Responsibility Judgments in Sequential Human-AI Collaboration (Full paper, oral presentation)
  (with S. Tsirtsis and T. Gerstenberg), 46th Annual Conference of the Cognitive Science Society (CogSci), July 2024.

• Optimal Decision Making Under Strategic Behavior (Full paper)
  (with S. Tsirtsis, B. Tabibian, M. Khajehnejad, B. Schoelkopf and A. Singla), Management Science, February 2024.

• Counterfactual Token Generation in Large Language Models (Workshop paper)
  (with I. Chatzi, N. Corvelo Benz, E. Straitouri and S. Tsirtsis), NeurIPS Workshop on Causality and Large Language Models, December 2024.

• Matchings, Predictions and Counterfactual Harm in Refugee Resettlement Processes (Workshop paper)
  (with S. Lee, N. Corvelo Benz and S. Thejaswi), KDD Workshop on Ethical Artificial Intelligence: Methods and Applications, August 2024.

• Controlling Counterfactual Harm in Decision Support Systems Based on Prediction Sets (Workshop paper)
  (with E. Straitouri and S. Thejaswi), ICML Workshop on Humans, Algorithmic Decision-Making and Society, July 2024.

• Prediction-Powered Ranking of Large Language Models (Workshop paper)
  (with I. Chatzi, E. Straitouri and S. Thejaswi), CHI Workshop on Human-Centered Evaluation and Auditing of Language Models, May 2024.

• Towards a computational model of responsibility judgments in sequential human-AI collaboration (Workshop paper)
  (with S. Tsirtsis and T. Gerstenberg), CHI Workshop on Theory of Mind in Human-AI Interaction, May 2024.

2023

• Finding Counterfactually Optimal Action Sequences in Continuous State Spaces (Full paper)
  (with S. Tsirtsis), Neural Information Processing Systems (NeurIPS), New Orleans (LA, USA), December 2023.

• Human-Aligned Calibration for AI-Assisted Decision Making (Full paper)
  (with N. Corvelo Benz), Neural Information Processing Systems (NeurIPS), New Orleans (LA, USA), December 2023.

• Improving Expert Predictions with Conformal Prediction (Full paper)
  (with E. Straitouri, L. Wang and N. Okati), 40th International Conference on Machine Learning (ICML), Honololu (HI, USA), July 2023.

• On the Within-Group Discrimination of Screening Classifiers (Full paper)
  (with N. Okati and S. Tsirtsis), 40th International Conference on Machine Learning (ICML), Honolulu (HI, USA), July 2023.

• Designing Decision Support Systems Using Counterfactual Prediction Sets (Workshop paper)
  (with E. Straitouri), Workshop on AI and HCI (ICML), Honolulu (HI, USA), July 2023. Best Paper Award

• Finding Counterfactually Optimal Action Sequences in Continuous State Spaces (Workshop paper)
  (with S. Tsirtsis), Workshop on Counterfactuals in Minds and Machines (ICML), Honolulu (HI, USA), July 2023.

• Human-Aligned Calibration for AI-Assisted Decision Making (Workshop paper)
  (with N. Corvelo Benz), Workshop on AI and HCI (ICML), Honolulu (HI, USA), July 2023.

• On the Within-Group Unfairness of Screening Classifiers (Workshop paper)
  (with N. Okati and S. Tsirtsis), Workshop on Ethical Artificial Intelligence: Methods and Applications (KDD), Long Beach (CA, USA), August 2023.

2022

• Counterfactual Temporal Point Processes (Full paper)
  (with K. Noorbakhsh), Neural Information Processing Systems (NeurIPS), New Orleans (LA, USA), December 2022.

• Counterfactual Inference of Second Opinions (Full paper)
  (with N. Corvelo Benz), 38th Conference on Uncertainty in Artificial Intelligence (UAI), Eindhoven (Netherlands), August 2022.

• Learning to Switch Among Agents in a Team via 2-Layer Markov Decision Processes (Full paper)
  (with V. Balazadeh, A. De and A. Singla), Transactions on Machine Learning Research (TMLR), July 2022.

• Improving Screening Processes via Calibrated Subset Selection (Full paper, spotlight presentation)
  (with L. Wang and T. Joachims), 39th International Conference on Machine Learning (ICML), Baltimore (MD, USA), July 2022.

• Quantifying the Effects of Contact Tracing, Testing, and Containment Measures in the Presence of Infection Hotspots (Full paper)
  (with L. Lorch, H. Kremer, W. Trouleau, S. Tsirtsis, A. Szanto and B. Schoelkopf), ACM Transactions on Spatial Algorithms and Systems (TSAS), April 2022.

• Listening to Bluetooth Beacons for Epidemic Risk Mitigation (Full paper)
  (with G. Barthe, R. De Viti, P. Druschel, D. Garg, P. Ingo, H. Kremer, M. Lentz, L. Lorch, A. Mehta and B. Schoelkopf), Nature Scientific Reports, April 2022.

• Pooled Testing of Traced Contacts Under Superspreading Dynamics (Full paper)
  (with S. Tsirtsis, A. De and L. Lorch), PLOS Computational Biology, March 2022.

• Provably Improving Expert Predictions with Prediction Sets (Workshop paper)
  (with E. Straitouri, L. Wang and N. Okati), Workshop on Distribution-Free Uncertainty Quantification (ICML), Baltimore (MD, USA), July 2022.

• Counterfactual Inference of Second Opinions (Workshop paper)
  (with N. Corvelo Benz), Workshop on Human-Machine Collaboration and Teaming (ICML), Baltimore (MD, USA), July 2022.

2021

• Counterfactual Explanations in Sequential Decision Making Under Uncertainty (Full paper)
  (with S. Tsirtsis and A. De), Neural Information Processing Systems (NeurIPS), Virtual, December 2021.

• Differentiable Learning under Triage (Full paper)
  (with N. Okati and A. De), Neural Information Processing Systems (NeurIPS), Virtual, December 2021.

• Large-scale randomized experiments reveals that machine learning-based instruction helps people memorize more effectively (Full paper)
  (with U. Upadhyay, G. Lancashire and C. Moser), npj Science of Learning, Aug 2021.

• The Network Visibility Problem (Full paper)
  (with K. Gatmiry), ACM Transactions on Information Systems (TOIS), April 2021.

• Classification Under Human Assistance (Full paper)
  (with A. De, N. Okati and A. Zarezade), 35th AAAI Conference on Artificial Intelligence (AAAI), Virtual, February 2021.

• Reinforcement Learning under Algorithmic Triage (Workshop paper)
  (with E. Straitouri, A. Singla and V. Balazadeh), Workshop on Cooperative AI (NeurIPS), Virtual, December 2021.

• Learning to Switch Among Agents in a Team (Workshop paper)
  (with V. Balazadeh, A. De and A. Singla), Workshop on Human-AI Collaboration in Sequential Decision-Making (ICML), Virtual, July 2021.

• Counterfactual Explanations in Sequential Decision Making Under Uncertainty (Workshop paper)
  (with S. Tsirtsis and A. De), Workshop on Interpretable Machine Learning in Healthcare (ICML), Virtual, July 2021.

• Differentiable Learning under Triage (Workshop paper)
  (with N. Okati and A. De), Workshop on Human in the Loop Learning (ICML), Virtual, July 2021.

2020

• Decisions, Counterfactual Explanations and Strategic Behavior (Full paper)
  (with S. Tsirtsis), Neural Information Processing Systems (NeurIPS), Virtual, December 2020.

• On the Design of Consequential Ranking Algorithms (Full paper)
  (with B. Tabibian, V. Gomez, A. De and B. Schoelkopf), The 2020 Conference on Uncertainty in Artificial Intelligence (UAI), Virtual, 2020.

• NEVAE: A Deep Generative Model for Molecular Graphs (Full paper)
  (with B. Samanta, A. De, G. Jana, V. Gomez, P. K. Chattaraj and N. Ganguly), Journal of Machine Learning Research (JMLR), 2020.

• Tracking progress towards malaria elimination in China: individual-level estimates of transmission and its spatiotemporal variation using a diffusion network approach (Full paper) [Biorxiv]
  (with I. Routledge, S. Lai, K. E. Battle, A. C. Ghani, K. B. Gustafson, S. Mishra, J. L. Proctor, A. J. Tatem, Z. Li, S. Bhatt), PLOS Computational Biology, 2020.

• Fair Decisions Despite Imperfect Predictions (Full paper)
  (with K. Kilbertus, B. Schoelkopf, K. Muandet and I. Valera), 23rd International Conference on Artificial Intelligence and Statistics (AISTATS), Virtual, June 2020.

• Regression Under Human Assistance (Full paper)
  (with A. De, P. Koley and N. Ganguly), 34rd AAAI Conference on Artificial Intelligence (AAAI), New York (NY), February 2020.

• Can A User Guess What Her Followers Want? (Full paper)
  (with A. De, A. Singla and U. Upadhyay), 12th ACM International Conference on Web Search and Data Mining (WSDM), Houston (Texas), February 2020.

• Classification under Human Assistance (Workshop paper)
  (with A. De, N. Okati and A. Zarezade), Workshop on Consequential Decisions in Dynamic Environments (NeurIPS), Virtual, December 2020.

• Decisions, Counterfactual Explanations and Strategic Behavior (Workshop paper)
  (with S. Tsirtsis), 4th Workshop on Mechanism Design for Social Good (MD4SG), Virtual, August 2020.

2019

• Teaching Multiple Concepts to Forgetful Learners (Full paper) [Arxiv]
  (with A. Hunziker, Y. Chen, O. M. Aodha, A. Krause, P. Perona, Y. Yue and A. Singla), Neural Information Processing Systems (NeurIPS), Vancouver (Canada), December 2019.

• Fairness Constraints: A Flexible Approach for Fair Classification (Full paper)
  (with B. Zafar, I. Valera and K. Gummadi), Journal of Machine Learning Research (JMLR), 2019.

• Enhancing Human Learning via Spaced Repetition Optimization (Full paper)
  (with B. Tabibian, U. Upadhyay, A. De, A. Zarezade and B. Schoelkopf), Proceedings of the National Academy of Sciences (PNAS), 2019.

• NeVAE: A Deep Generative Model for Molecular Graphs (Full paper)
  (with B. Samanta, A. De, G. Jana, P. K. Chattaraj and N. Ganguly), 33rd AAAI Conference on Artificial Intelligence (AAAI), Honolulu (Hawaii), February 2019

• On the Complexity of Opinions and Online Discussions (Full paper) [Arxiv]
  (with U. Upahyay, A. De and A. Pappu), 12th ACM International Conference on Web Search and Data Mining (WSDM), Melbourne (Australia), February 2019.

• Regression Under Human Assistance (Workshop paper)
  (with A. De, P. Koley and N. Ganguly), Workshop on Human-Centric Machine Learning (NeurIPS), Vancouver (Canada), December 2019.

• Optimal Decision Making Under Strategic Behavior (Workshop paper)
  (with M. Khajehnejad, B. Tabibian, B. Schoelkopf and A. Singla), Workshop on Human-Centric Machine Learning (NeurIPS), Vancouver (Canada), December 2019.

• Improving Consequential Decision Making under Imperfect Predictions (Workshop paper) (with K. Kilbertus, B. Schoelkopf, K. Muandet and I. Valera), Workshop on Data Collection, Curation, and Labeling for Mining and Learning (KDD), Alaska (AK, USA), August 2019.

• Can A User Guess What Her Followers Want? (Workshop paper)
  (with A. De, U. Upadhyay and A. Singla), Workshop on Behavioral EC (EC), Phoenix (AZ, USA), June 2019.

• Building Consequential Rankings (Workshop paper)
  (with B. Tabibian, V. Gomez, A. De and B. Schoelkopf), International Workshop on Misinformation, Computational Fact-Checking and Credible Web (The Web Conference), San Francisco (CA, USA), May 2019.

2018

• Deep Reinforcement Learning of Marked Temporal Point Processes (Full paper) [Arxiv] [Code]
  (with U. Upadhyay and A. De), Neural Information Processing Systems (NeurIPS), Montreal (Canada), December 2018.

• Enhancing the Accuracy and Fairness of Human Decision Making (Full paper) [Arxiv]
  (with I. Valera and A. Singla), Neural Information Processing Systems (NeurIPS), Montreal (Canada), December 2018.

• Estimating spatiotemporally varying malaria reproduction numbers in a near elimination setting (Full paper)
  (with I. Routledge, J. E. Romero Chevez, Z. Cucunuba, C. Guinovart, K. Schneider, P. Walker, K. Gustafson, A. Ghani and S. Bhatt), Nature Communications, 2018.

• Steering Social Activity: A Stochastic Optimal Control Point of View (Full paper) [bibtex]
  (with A. Zarezade, A. De, U. Upadhyay and H. Rabiee), Journal of Machine Learning Research (JMLR), 2018.

• On the Causal Effect of Badges (Full paper) [Code] [Arxiv] [bibtex]
  (with T. Kusmierczyk), The Web Conference (WWW), Lyon (France), April 2018.

• Fake News Detection in Social Networks via Crowd Signals (Full paper) [Arxiv] [bibtex]
  (with S. Tschiatschek, A. Singla. A. Merchant and A. Krause), The Web Conference (WWW) Alternate Track on Journalism, Misinformation, and Fact-checking, Lyon (France), April 2018.

• Leveraging the Crowd to Detect and Reduce the Spread of Fake News and Misinformation (Full paper) [Code] [Website] [bibtex]
  (with J. Kim, B. Tabibian, A. Oh and B. Schoelkopf), 11th ACM International Conference on Web Search and Data Mining (WSDM), Los Angeles (CA, USA), February 2018.

• Stochastic Optimal Control of Epidemic Processes in Networks (Workshop paper) [Arxiv]
  (with L. Lorch, A. De, S. Bhatt, W. Trouleau and U. Upadhyay), ML4H Workshop at Neural Information Processing Systems (NeurIPS), Montreal (Canada), December 2018.

• Designing Random Graph Models Using Variational Autoencoders with Applications to Chemical Design (Workshop paper) [bibtex] [Arxiv] [Code]
  (with B. Samanta, A. De and N. Ganguly), Workshop in Theoretical Foundations and Applications of Deep Generative Models (TADGM), 35th International Conference on Machine Learning (ICML), Stockholm (Sweden), July 2018.

• Enhancing Human Decision Making via Assignment Optimization (Workshop paper) [bibtex] [Arxiv]
  (with I. Valera and A. Singla), Workshop in Fairness, Accountability and Transparency in Machine Learning (FATML), 35th International Conference on Machine Learning (ICML), Stockholm (Sweden), July 2018.

• Coevolve: A Joint Point Process Model for Information Diffusion and Network Co-evolution (Extended abstract) [Code] [Arxiv] [bibtex]
  (with M. Farajtabar, Y. Wang, S. Li, H. Zha and L. Song), The Web Conference (WWW) Journal Track, Lyon (France), April 2018.

2017

• From Parity to Preference: Learning with Cost-effective Notions of Fairness (Full paper) [bibtex]
  (with B. Zafar, I. Valera, K. Gummadi and A. Weller), Neural Information Processing Systems (NIPS), Long Beach (CA, USA), December 2017.

• Optimizing Human Learning (Workshop paper) [Arxiv] [bibtex]
  (with B. Tabibian, U. Upadhyay, A. De, A. Zarezade and B. Schoelkopf), Workshop in Teaching Machines, Robots and Humans, Neural Information Processing Systems (NIPS), Long Beach (CA, USA), December 2017.

• Preference vs. Parity-based Notions of Fairness (Workshop paper) [bibtex]
  (with B. Zafar, I. Valera, K. Gummadi and A. Weller), Fairness, Accountability and Transparency in Machine Learning (FATML), Halifax (Canada), August 2017.

• Cheshire: An Online Algorithm for Activity Maximization in Social Networks (Invited paper) [bibtex]
  (with A. Zarezade, A. De and H. Rabiee), 55th Annual Allerton Conference on Communication, Control, and Computing, November 2017.

• Coevolve: A Joint Point Process Model for Information Diffusion and Network Co-evolution (Full paper) [Code] [Arxiv] [bibtex]
  (with M. Farajtabar, Y. Wang, S. Li, H. Zha and L. Song), Journal of Machine Learning Research (JMLR), 2017.

• Fairness Constraints: Mechanisms for Fair Classification (Full paper) [Code] [Arxiv] [bibtex]
  (with B. Zafar, I. Valera and K. Gummadi), 20th International Conference on Artificial Intelligence and Statistics (AISTATS), April 2017.

• Scalable Influence Maximization for Multiple Products in Continuous-Time Diffusion Networks (Full paper) [Arxiv] [bibtex]
  (with N. Du, Y. Liang, M. Balcan, H. Zha and L. Song), Journal of Machine Learning Research (JMLR), 2017.

• Uncovering the Spatiotemporal Patterns of Collective Social Activity (Full paper) [Appendix] [Arxiv] [bibtex]
  (with M. Jankowiak), 2017 SIAM International Conference on Data Mining (SDM), Houston (TX, USA), April 2017.

• Distilling Information Reliability and Source Trustworthiness from Digital Traces (Full paper) [Website] [Arxiv] [bibtex]
  (with B. Tabibian, I. Valera, M. Farajtabar, L. Song and B. Schoelkopf), 26th International World Wide Web Conference (WWW), Perth (Australia), April 2017.

• Modeling the Dynamics of Online Learning Activity (Full paper) [Code] [Arxiv] [bibtex]
  (with C. Mavroforakis and I. Valera), 26th International World Wide Web Conference (WWW), Perth (Australia), April 2017.

• Fairness Beyond Disparate Treatment & Disparate Impact: Learning Classification without Disparate Mistreatment (Full paper) [Code] [Arxiv] [bibtex]
  (with B. Zafar, I. Valera and K. Gummadi), 26th International World Wide Web Conference (WWW), Perth (Australia), April 2017. Best Paper Award Honorable Mention

• RedQueen: An Online Algorithm for Smart Broadcasting in Social Networks (Full paper) [Code] [Website] [Arxiv] [bibtex]
  (with A. Zarezade, U. Upadhyay and H. Rabiee), 10th ACM International Conference on Web Search and Data Mining (WSDM), Cambridge (UK), February 2017.

• Uncovering the Dynamics of Crowdlearning and the Value of Knowledge (Full paper, oral presentation) [Arxiv] [bibtex]
  (with U. Upadhyay and I. Valera), 10th ACM International Conference on Web Search and Data Mining (WSDM), Cambridge (UK), February 2017.

• A broad view of the ecosystem of socially engineered exploit documents (Full paper) [bibtex]
  (with S. Le Blond, C. Gilbert, U. Upadhyay and D. Choffnes), Network and Distributed System Security Symposium (NDSS), San Diego (CA, USA), 2017.

• Reconciling Privacy and Utility in Continuous-Time Diffusion Networks (Full paper) [bibtex]
  (with M. Backes, P. Manoharan and B. Surma), 30th IEEE Computer Security Foundations Symposium (CSF), Santa Barbara (CA, USA), 2017.

2016

• Learning and Forecasting Opinion Dynamics in Social Networks (Full paper) [Supplementary] [Arxiv] [bibtex]
  (with A. De, I. Valera, N. Ganguly and S. Bhattacharya), Neural Information Processing Systems (NIPS), Barcelona (Spain), December 2016.

• On Crowdlearning: How do People Learn in the Wild? (Workshop paper, oral presentation) [bibtex]
  (with U. Upadhyay and I. Valera), Workshop in ML for Education, Neural Information Processing Systems (NIPS), Barcelona (Spain), December 2016.

• Fairness Beyond Disparate Treatment and Disparate Impact: Learning Classification without Disparate Mistreatment (Workshop paper) [bibtex]
  (with B. Zafar, I. Valera and K. Gummadi), Fairness, Accountability and Transparency in Machine Learning (FATML), New York (NY, USA), November 2016.

• Smart Broadcasting: Do You Want to be Seen? (Full paper) [Code] [Arxiv] [bibtex]
  (with M. Karimi, E. Tavakoli, M. Farajtabar and L. Song), 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), San Francisco (CA, USA), 2016.

• Recurrent Marked Temporal Point Process: Embedding Event History to Vector (Full paper) [Code] [bibtex]
  (with N. Du, H. Dai, R. Trivedi, U. Upadhyay and L. Song), 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), San Francisco (CA, USA), 2016.

• On the Efficiency of the Information Networks in Social Media (Full paper, oral presentation) [bibtex]
  (with M. Babaei, P. Grabowicz, I. Valera and K. Gummadi), The 9th ACM International Conference on Web Search and Data Mining (WSDM), San Francisco (CA, USA), February 2016.

• Estimating Diffusion Networks: Recovery Conditions, Sample Complexity & Soft-thresholding Algorithm (Full paper) [bibtex]
  (with L. Song, H. Daneshmand, B. Schoelkopf), Journal of Machine Learning Research (JMLR), 2016.

• Influence Estimation and Maximization in Continuous-Time Diffusion Networks (Full paper) [Code] [bibtex]
  (with L. Song, N. Du, H. Zha, B. Schoelkopf), ACM Transactions on Information Systems (TOIS), February 2016.

2015

• Coevolve: A Joint Point Process Model for Information Diffusion and Network Co-evolution (Full paper) [Appendix] [Arxiv] [bibtex]
  (with M. Farajtabar, Y. Wang, S. Li, H. Zha and L. Song), Neural Information Processing Systems (NIPS), Montreal (Canada), December 2015. Full oral presentation (15 out of 1838)

• Hierarchical Dirichlet Hawkes Process for Modeling the Dynamics of Online Learning Activity (Poster, spotlight presentation)
  (with C. Mavroforakis and I. Valera), Workshop on Networks in the Social and Information Sciences at the 29th Annual Conference on Neural Information Processing Systems (NIPS), 2015.

• Modeling Adoption and Usage of Competing Products (Full paper, oral presentation) [Arxiv] [bibtex]
  (with I. Valera), IEEE International Conference on Data Mining (ICDM), Atlantic City (NJ, USA), November 2015. Recommended to KAIS best papers from ICDM

• Fairness Constraints: A Mechanism for Fair Classification (Short paper) [Arxiv] [bibtex]
  (with B. Zafar, I. Valera and K. Gummadi), Workshop in Fairness, Accountability and Transparency in Machine Learning, 32nd International Conference on Machine Learning (ICML), Lille (France), July 2015.

• On the Users' Efficiency in the Twitter Information Network (Short paper, poster) [bibtex]
  (with M. Babaei, P. Grabowicz and I. Valera), 9th International Conference on Web and Social Media (ICWSM), Oxford (UK), May 2015.

• Co-evolutionary Dynamics of Information Diffusion and Network Structure (Short paper, poster) [bibtex]
  (with M. Farajtabar, Y. Wang, S. Li, H. Zha and L. Song), Workshop in Diffusion, Activity and Events in Networks: Models, Methods and Applications, International World Wide Web Conference (WWW), Florence (Italy), May 2015.

• Back to the Past: Source Identification in Diffusion Networks from Partially Observed Cascades (Full paper) [Appendix] [bibtex]
  (with M. Farajtabar, N. Du, M. Zamani, H. Zha and L. Song), 18th International Conference on Artificial Intelligence and Statistics (AISTATS), San Diego (USA), May 2015. Full oral presentation (27 out of 442)

2014

• Shaping Social Activity by Incentivizing Users (Full paper, poster) [Code] [Appendix] [Arxiv] [bibtex]
  (with M. Farajtabar, N. Du, I. Valera, H. Zha and L. Song), Neural Information Processing Systems (NIPS), Montreal (Canada), December 2014.

• Modeling Adoption of Competing Products and Conventions in Social Media (Poster, spotlight presentation)
  (with I. Valera and K. Gummadi), Workshop in Networks: From Graphs to Rich Data at the 28th Annual Conference on Neural Information Processing Systems (NIPS), 2014.

• Finding Good Cascade Sampling Processes for the Network Inference Problem (Open Problem)
  (with L. Song and B. Schoelkopf) 2014 Conference on Learning Theory (COLT), Barcelona (Spain), June 2014.

• Estimating Diffusion Network Structures: Recovery Conditions, Sample Complexity & Soft-thresholding Algorithm (Full paper) [Appendix] [Arxiv] [bibtex]
  (with H. Daneshmand, L. Song and B. Schoelkopf) 31th International Conference on Machine Learning (ICML), Beijing (China), June 2014. Recommended to JMLR fast track (18 out of 1260+)

• Quantifying Information Overload in Social Media and its Impact on Social Contagions (Full paper, plenary session) [arXiv] [bibtex]
  (with K. Gummadi and B. Schoelkopf), Eighth International AAAI Conference on Weblogs and Social Media (ICWSM), Ann Arbor (MI), June 2014.

• Uncovering the Structure and Temporal Dynamics of Information Propagation (Journal paper) [Code] [Website] [Cambridge Site]
  (with J. Leskovec, D. Balduzzi and B. Schoelkopf), Network Science, April 2014.

2013

• Scalable Influence Estimation in Continuous-Time Diffusion Networks (Full paper) [Appendix] [arXiv] [Website] [bibtex]
  (with N. Du, L. Song and H. Zha), Neural Information Processing Systems (NIPS), South Lake Tahoe (CA), December 2013. Outstanding Paper Award

• Quantifying the Impact of Information Overload on Information Dissemination in Social Media (Poster, spotlight presentation)
  (with K. Gummadi and B. Schoelkopf), Workshop on Information in Networks (WIN), 2013.

• Modeling Information Propagation with Survival Theory (Full paper) [arXiv] [bibtex]
  (with J. Leskovec and B. Schoelkopf), 30th International Conference on Machine Learning (ICML) 2013, Atlanta (GA), June 2013.

• Structure and Dynamics of Diffusion Networks [bibtex]
  Ph.D. Thesis, Department of Electrical Engineering, Stanford University, May 2013.

• Structure and Dynamics of Information Pathways in On-line Media (Full paper, plenary session) [arXiv] [Website] [bibtex]
  (with J. Leskovec and B. Schoelkopf), 6th ACM International Conference on Web Search and Data Mining (WSDM), Rome (Italy), February 2013.

2012

• Modeling Information Propagation with Survival Theory (Abstract)
  (with B. Schoelkopf), Workshop in Algorithmic and Statistical Approaches for Large Social Networks at the 26th Annual Conference on Neural Information Processing Systems (NIPS), 2012.

• Bridging Offline and Online Social Graph Dynamics (Short paper, poster) [Long version] [bibtex]
  (with M. Rogati), 21st ACM Conference on Information and Knowledge Management (CIKM) 2012, Maui (HI, USA), October 2012.

• Influence Maximization in Continuous Time Diffusion Networks (Full paper) [Code] [Website] [Video] [bibtex]
  (with B. Schoelkopf), 29th International Conference on Machine Learning (ICML), Edinburgh (UK), June 2012.

• Submodular Inference of Diffusion Networks from Multiple Trees (Full paper) [Code] [Website] [Video] [bibtex]
  (with B. Schoelkopf), 29th International Conference on Machine Learning (ICML), Edinburgh (UK), June 2012.

• Inferring Networks of Diffusion and Influence [arXiv] [Website] [bibtex]
  (with J. Leskovec and A. Krause), ACM Transactions on Knowledge Discovery from Data (TKDD), February 2012.

2011

• Uncovering the Temporal Dynamics of Diffusion Networks (Full paper) [Code] [arXiv] [Website] [Video] [bibtex]
  (with D. Balduzzi and B. Schoelkopf), 28th International Conference on Machine Learning (ICML), Bellevue (WA, USA), June 2011.

• Towards Brain-Robot Interfaces in Stroke Rehabilitation (Full paper) [bibtex]
  (with M. Grosse-Wentrup, J. Hill, A. Gharabaghi, B. Schoelkopf and J. Peters), 12th International Conference on Rehabilitation Robotics (ICORR), Zurich (Switzerland), June 2011.

• Closing the Sensorimotor Loop: Haptic Feedback Helps Decoding of Motor Imagery (Full Paper) [bibtex]
  (with J. Peters, J. Hill, B. Schoelkopf, A. Gharabaghi and M. Grosse-Wentrup), Journal of Neural Engineering, April 2011.

2010

• Closing the Sensorimotor Loop: Haptic Feedback Facilitates Decoding of Arm Movement Imagery (Full paper) [bibtex]
  (with J. Peters, J. Hill, B. Schoelkopf, A. Gharabaghi and M. Grosse-Wentrup), SMC Workshop in Shared-Control for BMI, Istanbul (Turkey), October 2010.

• Epidural ECoG Online Decoding of Arm Movement Intention in Hemiparesis (Full paper) [bibtex]
  (with M. Grosse-Wentrup, J. Peters, G. Naros, J. Hill, B. Schoelkopf and A. Gharabaghi), ICPR Workshop on Brain Decoding at ICPR, Istanbul (Turkey), August 2010.

• Inferring Networks of Diffusion and Influence (Full paper) [Code] [Website] [Video] [bibtex]
  (with J. Leskovec and A. Krause), 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), Washington (DC, USA), July 2010. Best Research Paper Award Honorable Mention

• BCI and robotics framework for stroke rehabilitation (Abstract)
  (with J. Peters, J. Hill, A. Gharabaghi, B. Schölkopf and M. Grosse-Wentrup), 4th International BCI Meeting, Asilomar (CA, USA), June 2010.

2009

• Denoising photographs using dark frames optimized by quadratic programming (Full paper) [bibtex]
  (with J. Kober and B. Schoelkopf), 1st IEEE International Conference in Computational Photography (ICCP), San Francisco (CA, USA), April 2009.