About Me

Byung Hoon Ahn

1/23/2023: I joined Apple after graduation. To reach me, please drop me a message in LinkedIn.


Ph.D. in Computer Science. University of California San Diego
Advisor: Prof. Hadi Esmaeilzadeh

M.S. in Computer Science. University of California San Diego
Advisor: Prof. Hadi Esmaeilzadeh

B.Eng. in Electrical Engineering. Korea University
Advisor: Prof. Sung-Jea Ko


Software Engineer

Jan. 2023-present: Compiler Engineer at Apple
Oct. 2020-Jun. 2022: Research Scientist at Protopia AI
Jan. 2015-Jun. 2018: Software Engineer at Samsung Research

Research Intern

Oct. 2022-Jan. 2023: Research Scientist Intern at Intel Labs
Jun. 2022-Sep. 2022: Machine Learning Intern at Apple
Jun. 2020-Sep. 2020: Interim Engineering Intern at Qualcomm AI Research
Jul. 2019-Sep. 2019: Interim Engineering Intern at Qualcomm AI Research

Research Assistant

Sep. 2018-Dec. 2022: Graduate Student Researcher at ACT Lab, UCSD
Jul. 2014-Dec. 2014: Undergraduate Student Researcher at CVIP Lab, Korea University

Honors and Awards

Best Paper Award Nomination. DAC 2022 (2022)
DAC Young Fellow. DAC 2022 (2022)
Outstanding Reviewer Award. ICLR 2021 (2021)
Qualcomm Innovation Fellowship Finalist. Qualcomm (2020)
Korean Government Scholarship for Overseas Studies. NIIED. Ministry of Education (2018-2020)
CSE Department Fellowship. UC San Diego (2018)
Super Rookie Award. Samsung Research (2015)
Teaching Service Scholarship. Korea University (2014)
Semester High Honors. Korea University (3 semesters, 2011-2014)
Honors Scholarship. Korea University (4 semesters, 2009-2014)


  • AI for Optimized Execution of AI
    Byung Hoon Ahn
    Ph.D. Dissertation, 2022
  • Accelerating Federated Learning Through Attention on Local Model Updates
    Parsa Assadi, Byung Hoon Ahn, Hadi Esmaeilzadeh
    NeurIPS Workshop on Federated Learning: Recent Advances and New Challenges, 2022
  • Yin-Yang: Programming Abstraction for Cross-Domain Multi-Acceleration
    Joon Kyung Kim, Byung Hoon Ahn, Sean Kinzer, Soroush Ghodrati, Rohan Mahapatra, Brahmendra Yatham, Shu-Ting Wang, Dohee Kim, Parisa Sarikhani, Babak Mahmoudi, Divya Mahajan, Jongse Park, Hadi Esmaeilzadeh
    IEEE Micro Special Issue on Compiling for Accelerators, 2022 [paper]
  • Glimpse: Mathematical Embedding of Hardware Specification for Neural Compilation
    Byung Hoon Ahn, Sean Kinzer, Hadi Esmaeilzadeh
    DAC, 2022 [paper]
    Nominated for the Best Paper Award at DAC 2022
  • Exploring Efficient ML-based Scheduler for Microservices in Heterogeneous Clusters
    Rohan Mahapatra, Byung Hoon Ahn, Shu-Ting Wang, Hanyang Xu, Hadi Esmaeilzadeh
    ISCA Workshop on Machine Learning for Computer Architecture and Systems, 2022 [paper]
  • Responsible AI and Confidential Inferencing – NetApp AI with Protopia Image and Data Transformation
    Sathish Thyagarajan, Michael Oglesby, Byung Hoon Ahn, Jennifer Cwagenberg
    NetApp AI Use Cases [Technical Report], 2022
  • Protopia AI: Taking on the Missing Link in AI Privacy and Data Protection
    Byung Hoon Ahn, DoangJoo Synn, Masih Derkani, Eiman Ebrahimi, Hadi Esmaeilzadeh
    NeurIPS Demonstrations, 2021 [paper|overview|demo]
  • FastStereoNet: A Fast Neural Architecture Search for Improving the Inference of Disparity Estimation on Resource-Limited Platforms
    Mohammad Loni, Ali Zoljodi, Amin Majd, Byung Hoon Ahn, Masoud Daneshtalab, Mikael Sjödin, Hadi Esmaeilzadeh
    IEEE SMC, IF=13.45, 2021 [paper]
  • Abstractions and Mechanisms for AI-Enabled Compilation of Deep Neural Networks
    Byung Hoon Ahn
    Ph.D. Thesis Proposal [Academic Milestone], 2020
  • Planaria: Dynamic Architecture Fission for Spatial Multi-Tenant Acceleration of Deep Neural Networks
    Soroush Ghodrati, Byung Hoon Ahn, Joon Kyung Kim, Sean Kinzer, Brahmendra Yatham, Navateja Alla, Hardik Sharma, Mohammad Alian, Eiman Ebrahimi, Nam Sung Kim, Cliff Young, Hadi Esmaeilzadeh
    MICRO, 2020 [paper|video]
  • Compilation and Optimization Techniques for Machine Learning Workloads
    Byung Hoon Ahn
    Ph.D. Research Exam [Academic Milestone], 2020 [research exam]
  • Chameleon: Adaptive Code Optimization for Expedited Deep Neural Network Compilation
    Byung Hoon Ahn, Prannoy Pilligundla, Amir Yazdanbakhsh, Hadi Esmaeilzadeh
    ICLR, 2020 [paper|video]
  • Ordering Chaos: Memory-Aware Scheduling of Irregularly Wired Neural Networks for Edge Devices
    Byung Hoon Ahn, Jinwon Lee, Jamie Menjay Lin, Hsin-Pai Cheng, Jilei Hou, Hadi Esmaeilzadeh
    MLSys, 2020 [paper|slide]
    Featured in Qualcomm’s Invited Talk in EMC² Workshop at NeurIPS 2019 and TinyML Summit 2020
  • Reinforcement Learning and Adaptive Sampling for Optimized DNN Compilation
    Byung Hoon Ahn, Prannoy Pilligundla, Hadi Esmaeilzadeh
    ICML Workshop on Reinforcement Learning for Real Life, 2019 [paper]