tianyu bai
Software Development Engineer at Amazon
software development engineer amazon
Amazon
https://www.linkedin.com/company/amazon
Working at the Supply Chain Optimization Technologies (SCOT) team.
Seattle, WA, United States
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Software Development Engineer
Master of Science
Computer Science
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University of California, San Diego
https://www.linkedin.com/school/ucsandiego/
Bachelor of Science
Computer Science
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Sichuan University
https://www.linkedin.com/school/%E5%9B%9B%E5%B7%9D%E5%A4%A7%E5%AD%A6/
Consortium for Mathematics and Its Applications (COMAP)
Honorable Mention in the Interdisciplinary Contest In Modeling
Tsinghua University School of Software
The Third Prize in the National College Competition on Internet of Things
Ministry of Education of The People's Republic of China
National Scholarship
Ministry of Industry and Information Technology of The People's Republic of China
The First Prize in the “Blue Bridge Cup” National Programming Contest Sichuan Division C/C++
• Developed a model that generates multi-track polyphony played by multiple instruments conditioned on a given genre vector
• Used MuseGAN as the base model, which trains multiple generators independently and only one discriminator
• Fused genre information into the model instead of a default genre as in MuseGAN
• Extracted genre information based on the artist term frequencies retrieved from the Million Song Dataset
• Built the data pipeline to convert the midi files into 4-bar phrases for training
Genre-specific Multi-track Polyphony Generation
• Developed a distributed file system with fault-tolerance with RPyC in Python
• Built BlockStore service for chunk storage and MetadataStore to maintain state and manage operations
• Implemented the leader election part of the RAFT protocol to ensure the MetadataStore is fault-tolerant
• Tested the system with different block placement algorithms using servers located in five data centers on AWS
SurfStore: a cloud-based file storage service
• Designed automatic methods to extract structured data from different kinds of announcements like stock exchanges and major contracts
• Discovered common patterns and positions for different fields from HTML files
• Designed and built corresponding regular expression extractors using LTP -- a platform for Chinese NLP
• Trained a BiLSTM-CRF model to help with extracting entity names
• Rank 25th / 1507 in this Tianchi competition
Information extraction from listed company announcements
• Parallelized the Power Mean SVM algorithm, an additive kernel SVM, using MPI
• Implemented two kinds of kernel and compared their speed and accuracy under various number of cores
• The training speed is 9 times faster for the Caltech 101 dataset and 6 times faster for the Indoor 67 dataset than the original one, tested on a 24-core node of SDSC's Comet Supercomputer
Parallel Power Mean SVM
• Used FaceNet and Semi-Supervised Learning methods for Unrestricted, Label-Free Outside Data Task
• Combined the labeled data from LFW and the processed unlabeled data from other datasets like the CASIA-WebFace Dataset
Face Recognition for Unrestricted, Label-Free Outside Data Task
• An expandable system based on Raspberry Pi including a controllable camera, a speaker and some sensors like temp and humidity sensors for monitoring surrounding environment
• Implemented a web interface for real-time surveillance
• Applied face detection and recognition using Face++ API
Home Alarm System based on Raspberry Pi
• Predicted whether a bidder is human or robot using a dataset from an online platform
• Cleaned and analyzed the bid and bidder datasets
• Extracted mainly time-related features from over 7.6 million bids
• Achieved 0.893 AUC using the random forest model
Detect robot bidders in online auctions
• Predicted whether a user would visit a business and people’s star ratings using a dataset containing ratings and reviews of local businesses
• Achieved 91.6% accuracy on the visit prediction task using a personalized feature
projection method
• Achieved 0.756 RMSE for rating prediction using the latent factor model
• Rank 4th / 668 students in the visit prediction
Visit and rating prediction on Google Local Dataset
• Used the python implementation of Faster R-CNN (an object detection framework based on CNN)
• Used two kinds of convolutional networks and the Caltech-UCSD Birds-200-2011 dataset
• Compared the speed and accuracy of different models
Object Detection Models for Birds based on Faster R-CNN
• A tourism website for the Jade Dragon Snow Mountain 
• Built the database and designed tests to ensure its stability and resilience
• Developed the core backend service of the website using SpringMVC and Mysql
Jade Dragon Snow Mountain Business Website
• Developed an Android application that allows users to communicate with each other during emergency when the Internet is not available
• Responsible for the whole system development cycle including design, implementation and
documentation
• Explored different peer-to-peer technologies on Android and managed to use Wifi Direct
Emergency Communication System Based On Wireless Multi-Hop Networks
Liked by Tianyu Bai
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During’s last month’s INFORMS 2021 annual meeting, members from Amazon’s Supply Chain Optimization and Technologies team held a virtual discussion on…
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I finally got my bachelor's degree in the mail! The truth is that it is more than just a degree. It represents 7 years of my life. Yes! It took me 7…
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Can't wait to share our work with the world!
https://cn.linkedin.com/in/tianyu-branson-bai-0999154b
Xicheng District
Tianyu (Branson) Bai
Trust Manager Assist at China Credit Trust Co., Ltd.
https://www.linkedin.com/in/viola-bai
Seattle, WA
Viola (Tianyu) Bai
Software Engineering Graduate Student | GHC 2021
https://hk.linkedin.com/in/tianyu-charlie-bai-503463119
Hong Kong SAR
Tianyu (Charlie) Bai
Research Associate at Jefferies
https://ca.linkedin.com/in/rihanna-tianyu-bai-368aa954
Toronto, ON
Rihanna (Tianyu) Bai
Manager - Flagship at Stuart Weitzman
Sichuan University Alumni Professional Network of North America
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https://www.linkedin.com/groups/8829538