Jiin Woo

Carnegie Mellon University, Pittsburgh, PA, USA
Email: jiinw [at] andrew [dot] cmu [dot] edu
LinkedIn / Google Scholar

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I am a third-year PhD student in Electrical and Computer Engineering department at Carnegie Mellon University (CMU). I am advised by Yuejie Chi and Gauri Joshi. Before coming to CMU, I was a machine learning engineer at NAVER Search. Previously, I received an M.S. in Electrical Engineering (advised by Yung Yi) and a B.S. in Mathematical Sciences in Korea Advanced Institute of Science and Technology (KAIST).

My research interests lie in reinforcement learning, federated learning, and statistical inference.

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Selected Publications/Preprints

Reinforcement Learning

• Federated Offline Reinforcement Learning: Collaborative Single-Policy Coverage Suffices
  Jiin Woo, Laixi Shi, Gauri Joshi, Yuejie Chi
  preprint
  [arxiv]

• The Blessing of Heterogeneity in Federated Q-Learning: Linear Speedup and Beyond
  Jiin Woo, Gauri Joshi, Yuejie Chi
  ICML, 2023
  [arxiv][slides]

Statistical Inference with Social Network Data

• Iterative Learning of Graph Connectivity from Partially‑Observed Cascade Samples
  Jiin Woo, Jungseul Ok, Yung Yi
  ACM MobiHoc, 2020
  [paper]

• Information Source Finding in Networks: Querying With Budgets
  Jaeyoung Choi, Sangwoo Moon, Jiin Woo, KyungHwan Son, Jinwoo Shin, Yung Yi
  IEEE/ACM Transactions on Networking, 2020
  [paper]

• Rumor Source Detection under Querying with Untruthful Answers
  Jaeyoung Choi, Sangwoo Moon, Jiin Woo, KyungHwan Son, Jinwoo Shin, Yung Yi
  IEEE INFOCOM, 2017
  [paper]

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Awards & Scholarships

• Hsu Chang Memorial Fellowship (2022-2023)
• Carnegie Institute of Technology Dean’s Fellowship (2021-2022)
• KAIST Support Scholarship (2016-2018)
• Excellence Award in Creative Challenge Type SW R&D Program (2015)
• The National Scholarship for Science and Engineering (2011-2015)

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Teaching Experience

• TA for 18-813B: Special Topics in Artificial Intelligence: Foundations of Reinforcement Learning, Spring 2023

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