About me
Hi there :)
This is 李秉烜 ( Li , Bingxuan ) from Beijing, China & West Lafayette, IN.
Bingxuan is a senior undergrad student double majoring Computer Science and Data Science at Purdue University. Bingxuan is currently working as an undergraduate researcher for a large-scale data analysis project(Transfer Learning, Polygenic Risk Score related), and a machine learning project (CV, Active Learning, Neural-symbolic related). Prior to that, Bingxuan has three internship experiences: One data analyst internship, and two software engineer internships. Bingxuan is also a super foodie, a passionate cook, a dessert chef, and a barista.
Resume
Education
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Purdue University | West Lafayette , IN
August, 2019 - May, 2023Bachelor of Science in Computer Science & Bachelor of Science in Data Science | Dual Degree
- Related Coursework:
Object-oriented Programming, Data Structures, Algorithms, System Programming, Software Engineering, Computer Architecture, Applied Machine Learning, Statistical Theory, Probability, Large-Scale Data Analysis, Database, Information Retrieval.
- Selected Courses:
Experience
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Undergraduate Researcher
May, 2022 - Present- Preprocessed and analyzed large-scale high-dimension data.
- Built computational pipeline and software to assist data analysis and biomedical big data.
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Research Assistant
March, 2022 - Present- Discovery Park Undergraduate Research Internship Program
- Designed and implemented a digital platform to collect and analyze data for children in DR Congo, Africa.
- Prepared weekly reports and delivered presentations at weekly meetings. Conducted real-user testing.
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Data Analyst Intern
May, 2021 - August, 2021- JD.COM, Global Sales Department
- Performed large-scale sales data aggregating, cleaning and analysis.
- Developed automated software and application to augment data preprocessing and analysis.
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Software Engineer Intern
December, 2020 - March, 2021- Web development with React; Software development with C#.
- Developed pest detection and identification system with Ensemble learning.
Technical Stack
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Machine Learning
Experienced with Applied Machine Learning.
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Data analysis
Proficent in large-scale data analysis with R, Python, SPSS.
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Web development
Comfortable with React, Express, MongoDB, Flask, Figma.
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Mobile apps
Professional development of applications for Android.
Skills
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Java
88% -
Python
88% -
C
88% -
C#
66% -
R
88% -
SQL
70% -
HTML CSS JS(ES6)
70% -
Microsoft Office (Powerpoint, Word, Excel, Access)
88% -
Chinese(Mandarin)
Native -
English
Fluent
Selected Projects
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Neural-Symbolic Image Labeling
- A Machine Learning project aimed to build an automated image labeling tool.
- Designed and built a React-based frontend interface. Engineered backend with flask and MongoDB to store and process data.
- Tokenized the output of pre-trained neural networks, and exposed the symbolic logic to humans, combining Inductive Logic Programming, and Neuro-Symbolic Learning.
- Proposed and implemented Active Learning algorithm based on modAL to improve user labeling efficiency and accuracy.
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Task Information Platform
- A task information platform where users can post tasks - such as delivery, grocery shopping - and other users can take tasks to earn money.
- Designed UI with MUI in Figma. Developed web page based on React framework. Implement real-time map with Google Map API. Implemented authorization function and chatting function.
- Use express as server to interact with MongoDB cluster database. Configured redux store for data operation.
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Air Environment Monitoring System
- An IoT application to monitor and visualize air quality.
- Built air quality monitor device with Arduino. Use express as server to get and parse data of air quality, humidity, temperature and other data from monitor device using LeLian-Network API, classified data and calculating AQI values;
- Transfer data in real-time to a web page built with React and Android APP. Used BeautifulSoup to crawl pollution data, and utilized matplotlib and R shiny to visualize data with plots.
-
Student Enrollment Manage APP
-Designed and developed an Student information & enrollment data management Android App for children in Congo.
-Built SQLite database to record data locally, and connected to Google Firebase Realtime database for data synchronization. Logged all actions of users and upload to Google Firebase Firestone Storage for data analyzation.
-Created data download and analyze pipeline use Python: Automatically collect data and analyze in the backend.