QuyLe
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Quy Le

Computer Science Student | Software Engineer

quylm.work@gmail.com•github.com/minhquyminhquy•linkedin.com/in/quy-m-le

Experience

Undergraduate Research Trainee

Predictive Society and Data Analytics Lab, Tampere University

Jan 2025 - Present

  • Research project: "Physics-Informed Neural Networks: Parameter estimation of dynamical systems using Deep Learning," supervised by Prof. Frank Emmert-Streib.
  • Appling principles of Computational Physics to solve and model differential equations for simulating physical phenomena.
  • Developing and optimizing PINN models in PyTorch to enhance accuracy in dynamic system predictions.
  • Conducteing literature reviews on computational methods in physics-informed AI, synthesizing insights to guide model development.

CRM Data Scientist Intern

Abbott GmbH

July 2023 - August 2023

  • Preprocessed over 80,000 data points of e-commerce sales transaction from company’s Salesforce CRM database.
  • Developed and deployed regression models to forecast sales trends for Q4 2023, achieved a 35% improvement in RMSE from the baseline regressor.
  • Built insightful dynamic dashboards using PowerBI to track annual sales trends across 5 main products.

Education

Tampere University

B.S. Computing Sciences and Electrical Engineering

Expected May 2027

GPA: 4.9/5.0

Relevant Coursework:

Data Structures & Algorithms, Database Systems, Web Development, Machine Learning, Software Engineering, Data Analysis, Fine-Tuning LLM, Computer Vision

Technical Skills

Programming Languages

Python
C++
JavaScript
TypeScript
HTML/CSS

Frontend

React
Next.js
Tailwind CSS
Redux
Vue.js

Backend

Node.js
Express
Django
Flask
RESTful APIs
GraphQL

Databases

MongoDB
PostgreSQL
MySQL
Firebase

DevOps & Tools

Git
Docker
AWS
CI/CD
Agile/Scrum
Jira

Machine Learning

PyTorch
Tensorflow
Scikit-learn

Awards & Certifications