Murat Kocaoglu

Murat Kocaoglu

Incoming Assistant Professor in the Department of Computer Science at Johns Hopkins University. Assistant Professor in School of ECE, Department of Computer Science (by courtesy), Department of Statistics (by courtesy) at Purdue.
Previously Research Staff Member at the MIT-IBM Watson AI Lab.
UT Austin Alumni.

Service

Area Chair/Senior PC/Meta-reviewer for

Talks and Activities

  1. Invited Talk on “Causal Machine Learning: Fundamentals and Applications”, CCAIM Seminar Series, University of Cambridge, Nov. 2024.

  2. Invited Talk on “Causal Machine Learning: Fundamentals and Applications”, Computer Science Seminar, Johns Hopkins University, Nov. 2024.

  3. Invited Talk on “High-dimensional Causal Inference via Deep Generative Models with Applications in Trustworthy AI”, Colloquium Talk, Department of Statistics, Purdue University, Oct. 2024.

  4. Invited Talk on “Principled Causal Methods for Computer Security”, Amazon AI and Security Talk Series, Amazon, Online, Oct. 2024.

  5. Invited Talk on “Causal Machine Learning: Fundamentals and Applications”, IDEAL Workshop on Graph Representation Learning, University of Illinois Chicago, May 2024.

  6. Invited Talk on “Causal Machine Learning: Fundamentals and Applications”, MMLS 2024, Minneapolis, May 2024.

  7. Invited Talk on “Causal Machine Learning: Fundamentals and Applications”, Purdue University, Department of Computer Science, March 2024.

  8. Invited Talk on “Causal Machine Learning: Fundamentals and Applications”, Middle East Technical University, Department of Electrical and Electronics Engineering, March 2024.

  9. Invited Talk on “Approximate Causal Effect Identification under Weak Confounding”, Information Theory Applications Workshop (ITA), San Diego, CA, Feb. 2024.

  10. Invited Talk on “Causal Discovery via Common Entropy” at the Causal Inference & Quantum Foundations Workshop, Perimeter Institute, Waterloo, ON, Canada, Apr. 2023. Recording

  11. Invited Talk on “Entropic Causal Inference and Approximate Minimum Entropy Coupling”, Information Theory Applications Workshop (ITA), San Diego, CA, Feb. 2023.

  12. TILOS Seminar Series Invited Talk on “Causal Discovery for Root-cause Analysis,” Online, Jan. 2023.

  13. Guest Editor for the Special Issue on “Information-theoretic Methods for Causal Inference and Discovery”, Entropy, MDPI, 2023.

  14. ICON Seminar on “Causal Discovery for Root-cause Analysis”, Purdue University, October 2022. YouTube recording.

  15. Pacific Northwest National Laboratory (PNNL) Research Seminar on “Causal Discovery for Root-cause Analysis”, July 2022.

  16. Purdue ML Reading Group Talk on “Cost-Optimal Experimental Design for Causal Discovery”, April 2022.

  17. Invited Participant at Simons Institute Causality Workshop, UC Berkeley, February 2022.

  18. General chair for The AAAI-22 Workshop on Information-Theoretic Methods for Causal Inference and Discovery (ITCI’22), Vancouver, Canada, February 2022.

  19. Session Chair for ICERM Workshop on Advances in Theory and Algorithms for Deep Reinforcement Learning, Online, Aug. 2, 2021.

  20. Discussant in Causality Session at UAI’21, Online, July 27, 2021.

  21. Mentorship Circles at ICLR’21 Online, March 3, 2021.

  22. Purdue ECE Talk: Entropic Methods for Causal Discovery, Online talk for graduate students and the faculty, Mar. 4, 2021.

  23. Session chair for IJCAI’20, Machine Learning - Learning Generative Models, Jan. 2021.

  24. Lightning Talk in Young Researchers Workshop on CausalGAN, ORIE, Cornell University, Ithaca, NY, Oct. 2019.

  25. Co-organized “Bridging Causal Inference, Reinforcement Learning and Transfer Learning Workshop” in IBM AI Research Week, 2019.

  26. Invited Talk in AAAI-WHY19 Spring Symposium on CausalGAN, Stanford, CA, March 25-27, 2019.

  27. Shannon Channel Talk: Entropic Methods for Causal Discovery, Online talk hosted by Salim El Rouayheb, Mar. 1st, 2019.

  28. Hands-on machine learning workshop (jointly with Alex Dimakis), 2018 North American School of Information Theory, Texas A&M University, May 20-23, 2018.

  29. M. Kocaoglu, “Energy Minimization with Coding: Minimum Energy Channel and Network Codes,” COST Action IC0804 Meeting, Istanbul, Turkey, Dec. 2012.

Recognitions

  1. Reviewer Award for UAI 2022, Top Reviewer

  2. Reviewer Award for ICLR 2022, Highlighted Reviewer

  3. Reviewer Award for UAI’21, Amongst Top 5% of Reviewers

  4. Reviewer Award for ICLR 2021, Outstanding Reviewer

  5. Reviewer Award for ICML 2020, Amongst Top 33% of Reviewers

  6. Reviewer Award for NeurIPS 2019, Amongst Top 50% of Reviewers

  7. Reviewer Award for NeurIPS 2018, Amongst Top 218 Reviewers

Notes