Xiaozhe Yao (姚晓哲)
Xiaozhe Yao is a first-year doctoral student advised by Prof. Dr. Ce Zhang at DS3Lab, Systems Group, Department of Computer Science, ETH Zurich. With interests spanning from MLOps algorithms and systems to application of machine learning in existing systems, his long-term goal is to make machine learning automatic and accessible.
Prior to ETH Zurich, Xiaozhe Yao gained his Master’s degree at the University of Zurich in Data Science, advised by Prof. Dr. Michael Böhlen and Qing Chen. Before that, he completed his Bachelor’s study at Shenzhen University in Computer Science, advised by Prof. Dr. Shiqi Yu. He interned at Shenzhen Institute of Advanced Technology in 2016 where he investigated recommendation systems for food nutrition data. Since then, he has been working on machine learning and computer vision systems aiming to reduce the barriers to applying algorithms.
Between 2021 and 2022, he worked on the project AID as an Innovator Fellow at the Library Lab, ETH Zurich. The objective of AID is to support the application of machine learning algorithms by imitating a real library. It provides a unified programming interface to access and manage machine learning models, a digital library for searching, filtering and inspecting machine learning models.
In inverse chronological order:
- Mazumder, Mark, Colby Banbury, Xiaozhe Yao, Bojan Karlaš, William Gaviria Rojas, Sudnya Diamos, Greg Diamos, et al. “DataPerf: Benchmarks for Data-Centric AI Development”. ICML workshop (Benchmarking Data for Data-Centric AI).
- Cedric Renggli, Xiaozhe Yao, Luka Kolar, Luka Rimanic, Ana Klimovic, Ce Zhang. “SHiFT: An Efficient, Flexible Search Engine for Transfer Learning”. To appear in International Conference on Very Large Data Bases (VLDB 2023).
- Yao, Xiaozhe. “MLPM: Machine Learning Package Manager” Workshop on MLOps, MLSys, 2020.
- Chen, Yingying, and Xiaozhe Yao. “CVTron Web: A Versatile Framework for Online Computer Vision Services” World Congress on Services. Springer, Cham, 2018.
- Yao, Xiaozhe, et al. “Face Based Advertisement Recommendation with Deep Learning: A Case Study” International Conference on Smart Computing and Communication. Springer, Cham, 2017.
In inverse chronological order:
- Yao, Xiaozhe, Neeraj Kumar and Nivedita Nivedita. Slides/Implementing learned indexes on 1 and 2 dimensional data (Master Project 2021).
- Yao, Xiaozhe. ModelDB: Machine Learning Model Management (2020).
- Yao, Xiaozhe. Implementation of Naive Bayes Classifier (2020).
- Yao, Xiaozhe. Implementing Deconvolution to Visualize and Understand Convolutional Neural Networks, supervised by Prof. Dr. Michael Böhlen and Qing Chen (2020).
- Chen, Yingying, and Xiaozhe Yao. Knowledge Graph Embedding and OpenKE (2019).
- Chen, Yingying, Weijie Niu and Xiaozhe Yao. Diversity in Open Source Software Community and its Impact on Software Quality (2019).
- Master Thesis: Implementation of Learned Cardinality Estimation in Database Contexts, supervised by Prof. Dr. Michael H. Bohlen, Prof. Dr. Anton Dignös, Qing Chen.
- Bachelor Thesis: Face Detection with Multi-Block Local Binary Pattern in OpenCV, supervised by Prof. Dr. Shiqi Yu.
- Innovation Fellow at the Library Lab, ETH Zürich. June 2021 - Feb 2022.
- Visiting Student at the Computer Vision Lab, Shenzhen University.
- Engineer and Associate Founder at AICAMP.co.,LTD. May 2018
- Data Scientist (Intern) at the Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences. March 2016 - March 2017.
- Master of Data Science (with a minor in Informatics), summa cum laude, at the Institut für Informatik, Universität Zürich. Sept 2019 to April 2022
- Bachelor in Computer Science at the College of Computer Science and Software Engineering, Shenzhen University, with an honour in high-performance computing. Sept 13 to June 2017.
I served as the teaching assistant at both Shenzhen University and Universität Zürich, for the following courses:
- Informatics II: Data Structures and Algorithms. Universität Zürich. Spring 2022. Cheatsheet.
- Foundations of Data Science. Universität Zürich. Fall 2021.
- Informatics II: Data Structures and Algorithms. Universität Zürich. Spring 2021. Cheatsheet.
- Informatics I: Introduction to Programming. Universität Zürich. Fall 2020.
- Professional English for Computer Science. Shenzhen University. Spring 2019.
- Web Programming (Java Web). Shenzhen University. 2016.
- Web Programming (Android). Shenzhen University. 2015.
- Data Structures and Algorithms. Shenzhen University. 2014.
If you are interested in the slides of the following talks, please contact me.
- Techno Hour: Learned Cardinality Estimation in Database Systems at SAP, hosted by Thomas Zurek. 5, April 2022.
- Tech Talk: AID - Towards Findable, Accessible and Usable AI at ETH Library, hosted by Koesling Sven. 15, Feb 2022.
- Co-funded Zhitan Technology under the support from Shenzhen Institute of Advanced Technology. Our goal is to create an algorithm (along with mobile application) that could learn and recommend prefered food combinations to users.
- Co-funded AICAMP under the support from Cyberport.
- Entrepreneurship and Innovation Training Programme, California State University, Long Beach.
Awards, Scholarships and Projects Grants.
- Cyberport Incubation Programme (500K HKD). Hong Kong. 2016.
- Excellent Youth Entrepreneur of Nanshan District, Shenzhen. 2017.
- Loongson Scholarship. 2015.
- Individual Makers Fund, Shenzhen Science and Technology Committee. (100K CNY) 2016.
- Cyberport Creative Micro Fund. Hong Kong. (100K HKD) 2016.
- Top Academic Scholarship and several university-wide scholarships during 2013~2017.
- Photographer, IAPR TC4 Winter School on Biometrics, Shenzhen. 13-17 Jan 2019