About Me

I am Minh Duc Hoang (Duc), a Software Engineer & Graduate Data Science Student at the School of Engineering & Applied Sciences at the University of Pennsylvania. In 2023, I graduated the Department of Computer Science at the University of Toronto. I’m originally from Hanoi, Vietnam

Professional Experience:

• Software Engineer at Amazon
  • Developed edge AI orchestrations on the classic TTS-NLU stack and LLM stack on Alexa Automotive
• Quantitative Analyst at Squarepoint Capital
  • Researched statistical learning models for optimal executions for high-touch trades
  • Monitored, maintained, and developed execution features and products for traders

Internships

• Data Engineer Intern at Meta
  • Built data transformation features, data pipelines, analysis metrics, … to improve integrity enforcements on Meta Ads
• Research Associate at Harvard
  • Conducted quantitative finance and computational social science research at collaboration projects between Laboratory of Innovation Science at Harvard and UofT RiskLab
• Software Engineer Intern, Machine Learning at Huawei Technologies Canada
  • AI Engine Team at Toronto Distributed Scheduling and Data Engine Lab, working on optimizations for OpenLookEng
• Research Intern at VinAI Research (the division is now part of Qualcomm AI)
  • Research Topic: Face Parsing
• Research Assistant at Sargent Group
  • Research Topic: Using NLP to mine perovskites’ fabrication data and produce a semantic graph for Inverse Design
• Software Engineer Intern at FPT AI
  • Vision team, worked on OCR platform

Extracurricular Activities

• One of 6 representatives of UofT at Project X 2020, using AI to tackle problems in climate-influenced infectious diseases.
• Founder and Leader of Windchimes Project, a non-profit community project to raise awareness of our cultural values

Research and Publications

During 2022, I involved in different research projects in collaboration with Harvard in Computational Social Science and Quantitative Finance.

In late 2020/early 2021, I had the valuable experience to research on time-series prediction for infectious disease modelling using Neural Network. Inspired by Neural ODE structure, we produced interesting results in Black Sigatoka prediction. Our work won Project X 2020, a international research competition for undergraduate with the theme this year being ‘Climate Change’ and was awarded $20000. It is proudly presented on University of Toronto’s website, UofT Department of Computer Science’s website, and the school largest student run newspaper - The Varsity. Our work is presented at ICML 2021 Climate Change AI Workshop

Forecasting Black Sigatoka Infection Risks with Latent Neural ODEs - International Conference in Machine Learning (ICML) 2021