I am currently working as a research assistant at the Mortimer B. Zuckerman Mind Brain and Behavior Institute at Columbia University, supervised by Professor Tom Maniatis and Dr. Erin Flaherty.
- Workflow Automation: Improve bio-imaging analysis efficiency by 95% by automating computationally demanding tasks using Python, resulting in a significant reduction in analysis time.
- Dry Lab Research: Advance understanding of neurological developmental disorders by using statistical and machine learning techniques to correlate genetic variants with protocadherin protein variants, setting the foundation for future in-depth research.
- Wet Lab Research: Accomplish a 15% increase in experimental throughput by investigating the impact of gene deletion on cell adhesion, employing DNA cloning and gel electrophoresis techniques.
I worked as a research assistant at the RCS Lab at Columbia University, supervised by Professor Junfeng Yang and Dr. Yaniv David.
- Computational Research and Open Source Contributions: Strengthened the Python Upgradvisor research project by implementing two graph visualizations and four feature updates, helping open-source communities on GitHub to update package dependencies, which resulted in the delivery of comprehensive reports to three GitHub projects.
- Data Analysis and Automation: Reduced manual effort by 90% by automating and optimizing data processing in Python, transforming system output into insightful and human-readable tables.
Software Engineering Intern
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echo3DMay 2022 - Aug 2022
- Web Development: Improved rendering speed by 30% and reduced data storage by 70% by developing a web-based augmented reality game for company promotions using JavaScript and Python.
- iOS Development: Enhanced interactivity in educational applications for pharmaceutical and biotechnological research by building an iOS augmented reality app that allows exploration of neuroscience models, using Unity, C#, and the echo3D API.
- Front-end Chrome Extension: Achieved a 40% improvement in extension loading time by deploying user-friendly technologies like Svelte framework, JavaScript, and Python. Additionally, implemented 5+ new user-centric features, such as displaying overall ratings and recommendations on unsupported brand websites.
- Back-end Web Development: Reduced computing time and resources by 30% and added 10+ new features with minimized errors and bugs and improved code maintainability, developing the website using Python, JavaScript, and PostgreSQL.