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Brandeis University, Waltham, MA
B.S. in Computer Science and Biology, Aug 2022 - May 2026
GPA: 3.74 / 4.00, Dean’s List Spring 2023 - Present

Computational Neuroscience Research, Van Hooser Lab, Brandeis University, Waltham, MA
Sept 2024 - Present
- Architected high-performance scientific computing APIs to process 100GB+ 2-photon microscopy datasets, accelerating ROI extraction by 90% and reducing end-to-end processing latency.
- Engineered automated signal denoising pipelines that translated neural activity into structured vector fields.
- Contributed core data schemas to the open-source Neural Data Interface to help bridge raw neuroscience acquisition with downstream analysis.
Machine Learning and Data Engineering Intern, Noah AI, Shanghai, China
May 2024 - Aug 2024
- Engineered ETL pipelines for large-scale, high-dimensional single-cell RNA sequencing data.
- Optimized sparse matrix operations and memory allocation strategies, reducing RAM usage and accelerating downstream machine learning workflows by 50%.
Computational Biology Research, Kadener Lab, Brandeis University, Waltham, MA
Sept 2024 - Dec 2024
- Implemented the SCENIC workflow in R to infer gene regulatory networks from single-cell metadata.
- Performed high-dimensional clustering with Seurat objects to identify distinct cellular subpopulations.

Deep Learning Framework Benchmarking and Optimization, Academic Project
Developed a benchmarking framework to evaluate deep learning models, including Bi-LSTM and PyTorch neural networks, against statistical baselines on high-dimensional sequence classification tasks.
2D Isometric Simulation Engine, Independent Project
Designed a scalable Entity-Component System for a survival simulation and implemented decision trees and state machines to manage unit and environment interactions.

Programming: Python, Java, C, C#, R, MATLAB, Git, Linux, Bash and shell scripting
AI and ML: PyTorch, NumPy, Pandas, scikit-learn, SciPy
Coursework: Machine Learning, Data Structures, Linear Algebra, Theory of Computation, Natural Language Processing, Computational Neuroscience, Automation, Probability and Statistics