Generic No Photo Available Image

Kiwan Maeng

Assistant Professor


  • School of Electrical Engineering and Computer Science
  • Computer Science and Engineering

W330 Westgate Building


Personal or Departmental Website




  • B.S., Electrical and Computer Engineering, Seoul National University, 2016
  • Ph.D., Electrical and Computer Engineering, Carnegie Mellon University, 2021


Conference Proceedings

  • Bilge Acun, Benjamin Lee, Fiodar Kazhamiaka, Kiwan Maeng, Udit Gupta, Manoj Chakkaravarthy, David Brooks and Carole-Jean Wu, 2023, "Carbon Explorer: A Holistic Framework for Designing Carbon Aware Datacenters", Proceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS), pp. 118--132
  • Rishabh Jain, Scott Cheng, Vishwas Kalagi, Vrushabh Sanghavi, Samvit Kaul, Meena Arunachalam, Kiwan Maeng, Adwait Jog, Anand Sivasubramaniam, Mahmut T Kandemir and Chitaranjan Das, 2023, "Optimizing CPU Performance for Recommendation Systems At-Scale"
  • Emily Ruppel, Milijana Surbatovich, Harsh Desai, Kiwan Maeng and Brandon Lucia, 2022, "An Architectural Charge Management Interface for Energy-Harvesting Systems", 2022 55th IEEE/ACM International Symposium on Microarchitecture (MICRO), pp. 318--335
  • Carole-Jean Wu, Ramya Raghavendra, Udit Gupta, Bilge Acun, Newsha Ardalani, Kiwan Maeng, Gloria Chang, Fiona Aga, Jinshi Huang, Charles Bai, Michael Gschwind, Anurag Gupta, Myle Ott, Anastasia Melnikov, Salvatore Candido, David Brooks, Geeta Chauhan, Benjamin Lee, Hsien-Hsin S Lee, Bugra Akyildiz, Max Balandat, Joe Spisak, Ravi Jain, Mike Rabbat and Kim Hazelwood, 2022, "Sustainable ai: Environmental implications, challenges and opportunities", Proceedings of Machine Learning and Systems (MLSys), 4, pp. 795--813
  • Kiwan Maeng, Haiyu Lu, Luca Melis, John Nguyen, Mike Rabbat and Carole-Jean Wu, 2022, "Towards fair federated recommendation learning: Characterizing the inter-dependence of system and data heterogeneity", Proceedings of the 16th ACM Conference on Recommender Systems (RecSys), pp. 156--167


  • Maximilian Lam, Jeff Johnson, Wenjie Xiong, Kiwan Maeng, Udit Gupta, Minsoo Rhu, Hsien-Hsin S Lee, Vijay Janapa Reddi, Gu-Yeon Wei, David Brooks and G. Edward Suh, 2023, "GPU-based Private Information Retrieval for On-Device Machine Learning Inference", arXiv preprint arXiv:2301.10904
  • Sanjay Kariyappa, Chuan Guo, Kiwan Maeng, Wenjie Xiong, G Edward Suh, Moinuddin K Qureshi and Hsien-Hsin S Lee, 2022, "Cocktail Party Attack: Breaking Aggregation-Based Privacy in Federated Learning using Independent Component Analysis", arXiv preprint arXiv:2209.05578
  • Hanieh Hashemi, Wenjie Xiong, Liu Ke, Kiwan Maeng, Murali Annavaram, G. Edward Suh and Hsien-Hsin S Lee, 2022, "Data Leakage via Access Patterns of Sparse Features in Deep Learning-based Recommendation Systems", arXiv preprint arXiv:2212.06264
  • Kiwan Maeng, Chuan Guo, Sanjay Kariyappa and Edward Suh, 2022, "Measuring and Controlling Split Layer Privacy Leakage Using Fisher Information", NeurIPS 2022 Federated Learning Workshop

Research Projects

Honors and Awards


Service to Penn State:

Service to External Organizations:

  • Organizing Conferences and Service on Conference Committees, Peer Reviewer, April 2023
  • Organizing Conferences and Service on Conference Committees, Peer Reviewer, October 2022 - April 2023
  • Organizing Conferences and Service on Conference Committees, Peer Reviewer, November 2022 - February 2023