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| Bachelor's in Computer Science | |
| Atlanta, GA | |
| Courses: Data Structures \& Algos, Linear Algebra, Design \& Analysis of Algorithms, Computer Organiz \& Program, Objects $8 \mathcal{G}$ Design Certificates/Achievements: Deep Learning Specialization by DeepLearning.AI | |
| Software Eng. Virtual Experience by J.P. Morgan (Forage) | |
| Work Experience | |
| Faculty Honors Award Spring 2022, Dean's List Fall 2022 \& Spring 2023 | |
| Accelerating Materials Discovery with AI | |
| Undergraduate Researcher | |
| August 2023 - Present | |
| Atlanta, GA | |
| - Applied graph neural networks to accelerate the discovery of next-generation catalysts, batteries, and solar cells, reducing time-to-discovery by \%$ compared to traditional methods. | |
| - Developed innovative data-driven algorithms for atomic-level inverse design with a goal of achieving chemical accuracy, resulting in a \%$ improvement in model reliability through the incorporation of domain-specific physical constraints. | |
| - Engineered a scalable testing platform integrated with big data analytics and data visualization capabilities, setting new benchmarks for materials discovery research. | |
| Big Data Big Impact @ Georgia Tech | |
| August 2022 - May 2023 | |
| Frontend Developer | |
| Atlanta, GA | |
| - Developed the front end of a web application to visualize data collected from neural network-based damage cost estimation of US hurricanes | |
| - Created UI from scratch utilizing Figma and React, integrating Google API for a geo-mapping service to plot paths \& track the progress of hurricane patterns | |
| - Developed interactive data visualizations using React and D3.js to display complex data in an easily understandable format, resulting in a boost in user engagement with the application | |
| - Worked closely with the team to integrate the neural network model for estimating damage costs into the app, resulting in a \%$ decrease in damage cost estimation time. | |
| Georgia Tech Off-Road - Baja SAE | |
| Jan 2022 - May 2022 | |
| Data Acquisition Engineer | |
| Atlanta, GA | |
| - Designed \& maintained data acquisition subsystem for efficient collection, storage \& manipulation of test data, critical to team's R\&D efforts and successfully resulting in yearly design improvements of up to $5 \%$ | |
| - Developed real-time system for the integration of collected and processed data yielding a $20 \%$ improvement in testing cycle times, delivering reliable insights into the car's design | |
| - Enhanced continuous quality assurance framework that enabled daily validation/testing process \& improved accuracy by \%$, paving the way for timely product releases | |
| TransData | |
| Web Developer | |
| Aug 2021 - Dec 2021 | |
| - Created four engaging web applications for businesses, increasing user engagement and efficiency by \%$ | |
| - Designed and developed UI/UX features with client feedback in mind, resulting in a \%$ rise in customer ratings | |
| - Utilized innovative strategies to increase application scalability and guarantee data security through Penetration Testing | |
| Project Experience | |
| Full Stack Threads App | Next.js, Clerk, Tailwind CSS, MongoDB, Shadcn, Figma, Zod | |
| Jun 2023 - Present | |
| - Designed an intuitive UI using Figma, Next.js, and Tailwind CSS, enhanced with custom shades via Shadcn. | |
| - Engineered a secure user authentication and profile management system leveraging Clerk for robust backend functionality. | |
| - Utilized MongoDB for data storage, accommodating complex schemas and efficient data population. | |
| - Integrated UploadThing for file management and employed Zod for robust data validation, enhancing overall user experience. | |
| Face Recognition System | TensorFlow | |
| May 2023 - Jun 2023 | |
| - Implemented a high-performance ConvNet-based face verification and recognition system, utilizing FaceNet's state-of-the-art one-shot learning and triplet loss algorithms to compute 128-dimensional face encodings. | |
| - Tuned model parameters to enhance prediction accuracy, achieving $98 \%$ precision and recall. | |
| - Developed a verification mechanism that leverages L2 distance calculations to determine identity authenticity, ensuring secure access for verified individuals with an impressive accuracy threshold of 0.7. | |
| - Applied Neural Style Transfer techniques to augment the capabilities of the face recognition system, providing not only identity verification but also real-time artistic rendering of detected faces. | |
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| Leadership Experience | |
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| Effective Altruism at Georgia Tech | |
| Organizer | |
| August 2023 - Present | |
| Atlanta, GA | |
| - Completed AI Safety Fundamentals Fellowship, culminating in a capstone, new approaches to Myopic Decision Theory | |
| - Plan to develop updates to the AI Safety Fundamentals Fellowship, along with developing new materials to raise interest for it at Georgia Tech |