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- Bo Li
-- - LIBO.TOM.MAIL@GMAIL.COM - -
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- ABOUT
-- Hi, I'm interested in the field of supervised learning and autonomous driving. - I am planing to work as software engineer after graduate. -
- Resume -- -
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- - EDUCATION -
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Master of Computer science
-University of Illinois Urbana-Champaign, Jan 2024 - May 2025
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B.S. Computer Science, Data Science
-University of Wisconsin-Madison, Sep 2019 - May 2023
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- - EXPERIENCE -
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Tharzen - Software Engineer Internship
-May 2024 - Aug 2024
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- Designed and developed a reversible PHP interpreter based on bidirectional evaluation, leading Test-Driven Development (TDD) to ensure robust feature implementation and comprehensive testing. -
- Implemented interpreter functionality using Rust classes and traits to enhance the core logic and maintainability of the reversible PHP interpreter. -
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Spark Education Group - Software Engineer Internship
-Aug 2023 - Dec 2023
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- Designed and developed a Python application utilizing longchain embedding, chat completion, and vector store, allowing users to interact with the project codebase effectively. -
- Led the deployment of a large language model platform using React, Node.js, Python, FastAPI, and PostgreSQL, integrating new features such as user statistics, top prompts display, and custom masks. -
- Drove database and API enhancements, contributing to a 30% increase in weekly active users and achieving a peak of 185 daily active users. -
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Amazon - Software Engineer Internship
-May 2022 - Aug 2022
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- Designed and implemented the backend API for the changelog function using Node.js and GraphQL, enhancing user interaction with changelog data based on permissions. -
- Created GraphQL schema, field resolver, and record resolver for seamless data mapping and CRUD operations, ensuring high performance and scalability. -
- Managed the end-to-end development cycle, from design documents and UI wireframes to code implementation, code review, and deployment. -
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- - RESEARCH -
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ClaimTrust – A Propagation-Based Trust Scoring Framework for Retrieval-Augmented Generation (RAG) Systems
-Professor: Heng Ji, Aug 2024 - Dec 2024
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- Developed a graph-based trust scoring algorithm to evaluate document reliability, improving RAG system response quality by 11.2%. -
- Processed 814 articles to extract claims and classify relationships for trust propagation. -
- Optimized claim extraction and relationship classification, reducing computational complexity from O(n²) to O(n). -
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Simulation of the Collaborative Automated Driving Systems
-Professor: Bin Ran, Feb 2022 - Dec 2022
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- working with the prediction group focusing on trajectory prediction of autonomous driving cars and investigating trajectory prediction methods for the project. -
- Generating status info of vehicles from Carla simulator in the format that can be used for future tasks as the data for fitting trajectory prediction models. -
- Contributed to the unification of simulator export data format and model input data format. -
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Offloading pushdown db onto SmartNIC based JBOF device
-Professor: Ming Liu , Oct 2021 - Dec 2021
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- Customize FlexPushdownDB developed based on C++ hybrid with caching and pushdown capabilities and weighted cache policy from AWS cloud to JBOF device. -
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- - PROJECTS -
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Auto parking with Gem e4 Vehicle
-algorithm developer
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- Designed and implemented image recognition and calibration transposition algorithms using lidar and camera sensors to enhance parking system accuracy. -
- Developed and deployed an MPC trajectory tracker and hybrid A* route planning for autonomous vehicle navigation. -
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Cloud-Based IoT Infrastructure for Vehicle Monitoring
-AWS developer
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- Designed and deployed scalable IoT infrastructure using AWS IoT Core, AWS GreenGrass, and AWS IoT Analytics to monitor data from a fleet of 120,000 simulated vehicles. -
- Implemented AWS Lambda functions to analyze CO2 emissions and return diagnostics, utilizing the publish-subscribe MQTT model for seamless device communication. -
- Built data visualization pipelines with AWS Firehose, AWS Glue, and AWS Athena, leveraging AWS Sagemaker Jupyter Notebooks for insights. -
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Farm data management system
-Java programmer
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- Designed the system and user interface using JavaFX and CSS. -
- Utilizing java packages processing data from csv documents for computing and visualizing. -
- Allows users to search data from the database on different categories, displaying the data by farm report, annual report, monthly report, and date Range report with percent of total weight. -
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Account holders household clustering with associate bank
-Python programmer
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- Custom distance functions based on address and joint account information using scikit-learn hierarchical clustering, and access data from Snowflake flatform. -
- The cost of the model using i7-9700 CPUis exponential 1.21 seconds for 1000 records and 43.09 seconds for 10,000 records, and the highest accuracy of the model is 96.6% with different distance threshold. -
- Write a distance clustering function to weight address clustering method, utilize shared account relationship columns in clustering function, and test functionality of the project. -
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Data research on undergraduate enrollment
-Data analysis
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- Utilized Python to develop web crawlers for collecting data from online databases. -
- Preprocessed data by slicing, reformatting, and implementing a pipeline with StandardScaler transformer. -
- Analyzed data using PCA and linear regression methods from the PyTorch library. -
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Website for Chinese Students and Scholars Association at UW-MADISON
-Web develope
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- Maintained and updated the website for the Chinese Students and Scholars Association at UW-Madison. -
- Implemented new features and functionality based on user requirements. -
- Collected and analyzed data from blog and tweet sources. Extracted relevant insights and trends from the data for further analysis. -
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