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I'm Amogh Panhale, a Computer Science student at the University of Alberta with hands-on experience building research software and data pipelines. I've developed tools to collect and analyze attention data, automate data capture, and refactor legacy Matlab workflows to support scientific studies. I thrive in collaborative teams, enjoy turning complex problems into reliable systems, and I love exploring AI-powered solutions for healthcare and education. When I'm not coding, you can find me tinkering with side projects or helping lab members troubleshoot.…I'm Amogh Panhale, a Computer Science student at the University of Alberta with hands-on experience building research software and data pipelines. I've developed tools to collect and analyze attention data, automate data capture, and refactor legacy Matlab workflows to support scientific studies. I thrive in collaborative teams, enjoy turning complex problems into reliable systems, and I love exploring AI-powered solutions for healthcare and education. When I'm not coding, you can find me tinkering with side projects or helping lab members troubleshoot.

Amogh Panhale

Web Developer, Programmer, Full Stack Developer, +2

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I'm Amogh Panhale, a Computer Science student at the University of Alberta with hands-on experience building research software and data pipelines. I've developed tools to collect and analyze attention data, automate data capture, and refactor legacy Matlab workflows to support scientific studies. I thrive in collaborative teams, enjoy turning complex problems into reliable systems, and I love exploring AI-powered solutions for healthcare and education. When I'm not coding, you can find me tinkering with side projects or helping lab members troubleshoot.…I'm Amogh Panhale, a Computer Science student at the University of Alberta with hands-on experience building research software and data pipelines. I've developed tools to collect and analyze attention data, automate data capture, and refactor legacy Matlab workflows to support scientific studies. I thrive in collaborative teams, enjoy turning complex problems into reliable systems, and I love exploring AI-powered solutions for healthcare and education. When I'm not coding, you can find me tinkering with side projects or helping lab members troubleshoot.

Available to hire

I’m Amogh Panhale, a Computer Science student at the University of Alberta with hands-on experience building research software and data pipelines. I’ve developed tools to collect and analyze attention data, automate data capture, and refactor legacy Matlab workflows to support scientific studies.

I thrive in collaborative teams, enjoy turning complex problems into reliable systems, and I love exploring AI-powered solutions for healthcare and education. When I’m not coding, you can find me tinkering with side projects or helping lab members troubleshoot.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Language

English

Fluent

Work Experience

Undergraduate Research Assistant at University of Alberta - VASP Lab

January 1, 2025 - December 1, 2025

Built research software and data collection systems for visual attention and social cognition studies. Developed Kotlin TikTok clone to collect user attention data from 50+ participants for short-term attention analysis. Created a Swift camera application that uses Optical Mark Recognition to convert paper data into a spreadsheet. Automated collection of 1000+ clips for the TikTok study by writing a Python Playwright scraper with a user-friendly Streamlit interface. Refactored legacy Matlab programs and developed new scripts for studies. Presented a streamlined methodology for troubleshooting software issues in a 20-minute talk to 30+ lab members.

Software Developer at Wound 3

June 1, 2024 - January 1, 2025

Built HIPAA-compliant software as a medical device solution for measurement and tracking of chronic wounds. Developed wound segmentation pipeline using PyTorch and OpenCV with sub-500ms latency, deployed via Docker and integrated with production backend. Improved 3D wound reconstruction quality by deploying an edge-preserving filter in C++, reducing noise by 2.4 dB. Delivered real-time protein slide capture processing system using OpenCV that eliminated ML cloud infrastructure costs. Implemented 6-point image quality checks in Swift to ensure data integrity. Compressed large ML models to 30% of their original size, enabling 3x faster offline deployment on mobile devices with comparable accuracy. Provided 24/7 on-call support for healthcare providers in mission-critical clinical scenarios.