Xiaozhe Yao (姚晓哲)
Xiaozhe Yao is a master student majoring in Data Science at the University of Zurich. With interests spanning from machine learning systems to self-learning databases, his long-term goal is to make machine learning automatic and accessible.
Xiaozhe Yao gained his Bachelor’s degree at Shenzhen University in Computer Science. 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.
In the past few years, he has been working on IndustryAI and CVTron, two end-to-end toolkits for computer vision. He witnessed the difficulties encountered while applying machine learning and grew his motivation to tackle these challenges.
He is currently working on the project AID as an Innovator Fellow at ETH Zurich Library Lab. The objective of AID is to support the application of machine learning algorithms by imitating a library. It provides a digital library for searching, filtering and inspecting machine learning models. It also enables developers to easily install and run machine learning algorithms within a few unified steps.
Outside of the current project, he is also interested in machine learning in database systems.
- Machine Learning Model, Data and Application Management AID.
- Learned Indexes and its application in databases EurusDB (in progress).
- Machine Learning in Social Sciences, Computer Vision and other applications.
In inverse chronological order:
- 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 (Not available yet)], 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 - Present.
- 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 Mathematics) at the Institut für Informatik, Universität Zürich. Sept 2019 to March 2022 (ca.).
- Micromaster (online) in Statistics and Data Science at Massachusetts Institute of Technology, Sept 2020 to December 2021 (ca.).
- 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.
- 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