👨💻 Double major in Computer Science and Data Science at the University of Wisconsin-Madison; transferred from B.S. in AI at the Autonomous University of Barcelona, with 4 years of continuous ML research experience.
- T-Few: Engaged in the study and application of transfer learning techniques using few-shot learning, focusing on tasks that benefit from minimal labeled data.
- Raman Spectrum Analysis: Developed ML models using CNNs and ordinal classification to detect Raman spectrum peaks, achieving high accuracy in separating PAHs and pesticides for chemical identification.
- Low-Light Image Enhancement: Benchmarked deep learning models to improve image quality in low-light laboratory conditions.
🌟 Passionate about building scalable ML integrated Physical/Software systems.
- Mindy: A flashcard generator and storage system based on your notes, enhanced with LLM integration to augment your notes and merge them with external sources such as PDFs, audio, and video links.
- American Battery Solutions SDE Co-op: Developing an enterprise-level AI agent for real-time C code topological graph and documentation generation code generation by RAG and the analysis of AST.
- NodeTree.io：System that dissects problem into manageable subproblems and addresses each one with help of Multimodal AI, delivering clear, step-by-step problem solutions with branches of subproblem nodes using reactflow to visualize the mindmap.
- Writing HPC with C++: Creating public notes on developing high-throughput, CUDA & parallel systems by referencing my progress in CS557 taught by Prof. Eftychios Sifakis - (scientist at NVIDIA), and resources on HPC/Scientifc Computing from NVIDIA.Developer.
- Got AWS Solutions Architect Associate.
- Now preparing for Machine Learning Specialty to build scalable AI-integrated cloud systems.
- Coding at the gym, of course!
- Language Exchange: Catch me at www.free4talk.com, where I sometimes host rooms for Spanish, Chinese and English conversations.
- Biking & Hiking