Zhihe(Kyrie) Zhao 赵之赫

Zhihe(Kyrie) Zhao

趙 之 赫

Ph.D Candidate

"Five Loaves & Two Fish"
zhaozhihe2333 AT gmail.com

Biography

I am a FIRST 2nd 3rd year Ph.D candidate in AIoT Lab at the Chinese University of Hong Kong, advised by Professor Guoliang Xing. Before, I received my Bachelor degree (2019) in computer science and technology from University of Liverpool and Master degree (2021) from Duke University (Quit Ph.D with Master). I enjoy exploring and building things that are elegant, novel and impactful, both in research and life. My research is motivated by designing efficient and intelligent computing systems for core problems in real-world AIoT examples.

[RESEARCH] I'm open to collaborate with people who are interested in:
(a) Boosting DNN compilation efficiency across Heterogenous Devices. (b) Unified Compiler for the Holistic Pipeline in AIoT Examples. (c) Smart healthcare.

[Startup] I am co-founder and CEO of ThingX, a Hong Kong Science and Technology Park-based company which provides smart health solutions based on our MLOps, LLMOps, AIoT Tech Stack (training/inference/optimization/scheduling). Please contact me if you are interested.

[Startup] I am also co-founder of Robot Storm Dynamics. A startup focuses on the bringing the power of embodied AI into vertical consumer domains. Leap into the future of AGI robot.

Research Interests:

Professional Services:

  • PC Member of MobiCom'24 Artifact Evaluation
  • PC Member of MobiCom'23@S3 Workshop
  • PC Member of MobiSys'23 Artifact Evaluation
  • Shadow PC Member of EuroSys'24
  • Reviewer of IEEE JSAC
  • Reviewer of MLSys’23@On-device Intelligence Workshop
  • Reviewer of IEEE Transactions on Mobile Computing (TMC)
  • Reviewer of AAAI’23@DCAA
  • Reviewer of MICCAI'23
  • External Reviewer of IoTDI'23 Poster&Demo

News:

  • [2024-04] Two demo abstracts accepted to IPSN 2024
  • [2024-03] Co-authored paper accepted to IOTJ
  • [2023-10] Two poster abstracts accepted to SenSys 2023
  • [2023-09] One paper accepeted to SenSys 2023
  • [2023-04] Co-authored paper accepeted to IEEE TVT
  • [2022-12] One paper accepeted to HotMobile 2023
  • [2022-11] Aaron won Best Poster Award (1/35) from SenSys 2022
  • [2022-11] BlastNet selected as one of Best Paper Finalists (7/52) at SenSys 2022
  • [2022-10] One poster abstract accepted to SenSys 2022
  • [2022-09] Receive Huawei Spark Award as 1st place
  • [2022-09] Co-authored paper accepted to SenSys 2022
  • [2022-01] Co-authored paper accepted to IPSN 2022
  • [2021-01] One paper accepted to IoTDI 2021
  • [2019-05] Gave a talk at TEDx
  • [2018-09] One demo abstract accepted to Sensys 2018

Selected Publications

Miriam: Exploiting Elastic Kernels for Real-time Multi-DNN Inference on Edge GPU
Accepted by the 21th ACM Conference on Embedded Networked Sensor Systems (SenSys 2023)
Zhihe Zhao, Neiwen Ling, Nan Guan, Guoliang Xing
BalanceFL: Addressing Class Imbalance in Long-tail Federated Learning
Poster Abstract: TensorBind: Unifying On-device Tensor Program Optimization through Foundation Model
Accepted by the 21th ACM Conference on Embedded Networked Sensor Systems (SenSys 2023)
Zhihe Zhao, Neiwen Ling, Kaiwei Liu, Nan Guan, Guoliang Xing
BalanceFL: Addressing Class Imbalance in Long-tail Federated Learning
Poster Abstract: CNN-guardian: Secure Neural Network Inference Acceleration on Edge GPU
Accepted by the 21th ACM Conference on Embedded Networked Sensor Systems (SenSys 2023)
Qipeng Xie, Hao Yang, Linshan Jiang, Zhihe Zhao, Siyang Jiang, Shiyu Shen, Salabat Khan, Zhe Liu, Kaishun Wu
BalanceFL: Addressing Class Imbalance in Long-tail Federated Learning
Moses: Exploiting Cross-device Transferable Features for On-device Tensor Program Optimization
Accepted by the 24th International Workshop on Mobile Computing Systems and Applications (HotMobile 2023)
Zhihe Zhao, Xian Shuai, Neiwen Ling, Nan Guan, Zhenyu Yan, Guoliang Xing
BalanceFL: Addressing Class Imbalance in Long-tail Federated Learning
Poster Abstract: Aaron: Compile-time Kernel Adaptation for Multi-DNN Inference Acceleration on Edge GPU
Best Poster Award (~2.8%, 1 out of 35 accepeted posters)
Accepted by the 20th ACM Conference on Embedded Networked Sensor Systems (SenSys 2022)
Zhihe Zhao, Neiwen Ling, Nan Guan, Guoliang Xing
BalanceFL: Addressing Class Imbalance in Long-tail Federated Learning
BlastNet: Exploiting Duo-Blocks for Cross-Processor Real-Time DNN Inference
Best Paper Finalist (~13.4%, 7 out of 52 accepted papers)
Accepted by the 20th ACM Conference on Embedded Networked Sensor Systems (SenSys 2022)
Neiwen Ling, Xuan Huang, Zhihe Zhao, Nan Guan, Zhenyu Yan, Guoliang Xing
BalanceFL: Addressing Class Imbalance in Long-tail Federated Learning
BalanceFL: Addressing Class Imbalance in Long-tail Federated Learning
Accepted by ACM / IEEE International Conference on Information Processing in Sensor Networks (IPSN 2022)
Xian Shuai, Yulin Shen, Siyang Jiang, Zhihe Zhao, Zhenyu Yan, Guoliang Xing
BalanceFL: Addressing Class Imbalance in Long-tail Federated Learning
EdgeML: An AutoML Framework for Real-Time Deep Learning on the Edge
Accepted by ACM/IEEE International Conference on Internet-of-Things Design and Implementation (IoTDI 2021)
Zhihe Zhao, Kai Wang, Neiwen Ling, Guoliang Xing
EdgeML: An AutoML Framework for Real-Time Deep Learning on the Edge
Demo Abstract: ECRT: An Edge Computing System for Real-Time Image-based Object Tracking
Accepted by the 16th ACM Conference on Embedded Networked Sensor Systems (SenSys 2018)
Zhihe Zhao, Zhehao Jiang, Neiwen Ling, Xian Shuai, Guoliang Xing
Demo Abstract: ECRT: An Edge Computing System for Real-Time Image-based Object Tracking

Experience

 
 
 
 
 
Research Intern
HUAWEI
March 2022 – July 2022
 
 
 
 
 
Embedded Software Engineer Intern
RT-Thread OS
Feb 2017 – Apr 2017 ShangHai, China
 
 
 
 
 
Co-Founder
Youdu Smart Tech CO., Ltd (start-up)
Sep 2015 – Mar 2017 SuZhou, China

Honors and Awards

  • SenSys'22 Best Poster Award (~2.8%, 1 out of 35 accepeted posters), 2022
  • SenSys'22 Best Paper Finalist (~13.4%, 7 out of 52 accepted papers), 2022
  • Huawei Spark Award, 2022
  • BOSCH AIoT Fellowship, 2021
  • CUHK IE Ph.D Fellowship, 2021
  • Duke ECE Ph.D Fellowship, 2019
  • National Scholarship, 2018