Jan 2025 – Present · 1 yr 4 mos · San Diego, California, United States · Hybrid

• Developed and optimized machine learning pipelines for fMRI image reconstruction using latent diffusion models.
• Designed and implemented data preprocessing pipelines for multi-modal fMRI datasets, ensuring robust model performance.
• Tuned hyperparameters and optimized neural networks to enhance image reconstruction fidelity.
• Validated model outputs using quantitative evaluation metrics, achieving 90% fidelity in reconstructed images.
• Collaborated with cross-functional teams to integrate computational neuroscience and AI-driven analysis.

Nov 2024 – Present · 1 yr 6 mos · San Diego, California, United States · On-site

• Established and launched a student-led initiative fostering meaningful connections between students and faculty through outdoor excursions, immersive hikes, and academic discussions.
• Led the development and structuring of the club, ensuring a strong foundation for intellectual exploration in nature’s classroom.
• Organized and facilitated curated outdoor experiences designed to promote engagement, dialogue, and interdisciplinary learning.

Nov 2024 – Mar 2026 · 1 yr 4 mos · San Diego, California, United States · Hybrid

• Conducted research and literature reviews to identify challenges and guide the development of tools for music production.
• Developed tools for audio production, modification, and parsing using deep learning techniques to enhance workflows.
• Built CNN models for audio analysis and separation, improving accuracy and usability in music production processes.
• Designed computer vision tools to convert scoresheet images into audio files, making music production more accessible.
• Collaborated in CV/ML and SWE teams to create tools, define frameworks, and address music production challenges.
• Created accessible tools to reduce barriers to music production and support diverse needs in audio and music analysis.

Jun 2024 – Sep 2024 · 3 mos · Hyderabad, Telangana, India · On-site

• Automated the extraction, processing, and analysis of test results, improving efficiency and simplifying workflows.
• Utilized Python and R to manage, clean, and analyze large datasets, creating visualizations that delivered accurate
• insights and identified key trends to support data-driven decision-making.
• Conducted computational analysis of NMR, hydrogen spectroscopy, and UPLC data to deliver valuable insights.
• Collaborated with diverse cross-functional team to ensure data integrity, optimize and streamline analysis processes.

Jan 2024 – Apr 2024 · 3 mos · San Diego, California, United States · Remote

• Analyzed Coursera dataset to uncover trends in university offerings, course duration, and top-rated
• skills.
• Developed advanced Python algorithms to calculate average reviews, optimizing the ranking of
• universities and skills.
• Employed Microsoft Excel, R, and image processing techniques for comprehensive data analysis,
• applying advanced statistical methods and visualizations to distill complex datasets into actionable
• insights.
• Extracted and sorted large-scale datasets using CSV modules, enhancing accuracy and efficiency in
• data analysis.
• Developed predictive models to analyze relationships between course difficulty, duration, and ratings,
• yielding actionable insights with an accuracy rate of 95%.

Sep 2022 – May 2023 · 8 mos · Hyderabad, Telangana, India · On-site

• Led an independent research project investigating the effects of varying caffeine concentrations on protein metabolism.
• Employed advanced techniques such as mass spectrophotometry and data pattern analysis to study metabolic variations.
• Leveraged computational tools like MS Excel and R for data analysis and visualization, to develop intuitive models.
• Developed comprehensive data visualizations and statistical models, reinforcing conclusions with secondary research.