Pengzhan Hao
Software engineer on Cloud
Joined Google in 2022, working in GKE, and focusing on Node & runtime area.
Most projects landed on bringing ARM-based VMs to GKE, introduced more flexibilities in node customization and pod lifecycle improvement for preemptible VMs
Contributed to Kubernetes open source community and became a member in 2023
Now working on making GKE a more productive platform for AI/ML
Research and study life in Binghamton University
Wide interests in multiple research areas, and spend most of my time in Edge computing, distributed systems and networks, and mobile operating system research. Under supervision from Professor Yifan Zhang, I spent 7 years in these research areas and outcome publications
I worked as a teaching assistant for Operating system and Distributed system courses for both graduate and undergraduate levels. Mostly, I helped lecturers finish academic goals and hosted Labs for students. Before and during my research career, I finished my Master’s level education with a full grade point average.
Publications
EDDL: A Distributed Deep Learning System for Resource-limited Edge Computing Environment
Pengzhan Hao, and Yifan Zhang The Sixth ACM/IEEE Symposium on Edge Computing (ACM/IEEE SEC) San Jose, CA, USA, 2021.
A Case for Web Service Bandwidth Reduction on Mobile Devices with Edge-hosted Personal Services
Yongshu Bai, Pengzhan Hao, and Yifan Zhang The 37th IEEE International ConferenDDL – Edge distributed deep learning frameworkce on Computer Communications (IEEE INFOCOM) Honolulu, HI, USA, 2018.
EdgeCourier: An Edge-hosted Personal Service for Low-bandwidth Document Synchronization in Mobile Cloud Storage Services
Pengzhan Hao, Yongshu Bai, Xin Zhang, and Yifan Zhang The 2nd ACM/IEEE Symposium on Edge Computing (ACM/IEEE SEC) San Jose, CA, USA, 2017.
Poster: Securing Device Inputs for Smartphones Using Hypervisor Based Approach
Xin Zhang, Yongshu Bai, Pengzhan Hao, and Yifan Zhang The 15th ACM International Conference on Mobile Systems, Applications, and Services (ACM MobiSys) Niagara Falls, NY, USA, 2017.
Poster: EPS – Edge-hosted Personal Services for Mobile Users
Pengzhan Hao, Yongshu Bai, Xin Zhang, and Yifan Zhang The 15th ACM International Conference on Mobile Systems, Applications, and Services (ACM MobiSys) Niagara Falls, NY, USA, 2017.
Undergraduate life in Beihang University
From 2011 to 2015, I attended the Software Engineering program at Beihang University. Overall, I received 3.25 out of 4 when graduating. During most of the era, I was enthusiasm in participating Movie Association and Mountain Climbing Association, and also worked as student assistant for career program for the last year.
Starting from my junior year, I studied and researched consecutively in two labs. Worked in Android Kernel and module localization and smart urban computing areas. In urban computing areas, led a small team to participate in a joint project together by the Advanced Computer application technology engineering research center(Beihang University) and Microsoft Research Asia(MSRA).
Projects
EDDL – Edge distributed deep learning framework
A lite-weight c++ written framework(based on Dlib) for distributed neural network training on embedded devices and mobile phones. With supporting of our implemented runtime profilers, training devices can interconnect in an optimized network topology under various network environments. In our last publication, we showed our framework can perform distributed training for diverse neural networks on resource-limited devices. The EDDL framework also showed well scalability in large amounts of devices. We are currently working on network optimization on per-batch communication time and overall convergence time.
Edge Courier
A proxy-based protocol for incremental file synchronization and cooperative online document editing. This protocol supports file hosting services including Google Drive, Dropbox, and OneDrive as well as document collaboration services such as G Suite and Microsoft 365. Edge courier can significantly decrease bandwidth consumption for collaborative editing web apps, and also showed advancement in cloud file storage services.
RTRouting assistant
A real time routing prototype which can guide vehicle to alternative routes with high-volume traffic prediction. The predicted traffic alert is generated by a pre-trained model learned from history monitored traffics, real time event warnings and a abnormal traffic prediction model. This project belongs to a urban computing project studied together by Advance computer application technology engineering research center(Beihang University) and Microsoft Research Asia(MSRA).
Recognition
ACM/IEEE SEC student travel grant
IEEE • 2017, 2021
ACM MobiSys 2017 student travel grant
ACM • 2017