Software Engineering Computer Science

Joseph Collins

978-***-**** ************@*****.*** linkedin.com/in/jcollins2021 github.com/Jcollins2021 Recent MS in Computer Science graduate with hands-on experience in full-stack web development and modern JavaScript frameworks. Skilled in building secure, user-focused applications. Developed dynamic front-end interfaces and robust back-end services for real-world applications. Passionate about creating clean, responsive web solutions and eager to contribute to impactful software engineering teams. Education

University of Massachusetts Amherst GPA 3.73/4.0

Masters of Science in Computer Science Sep. 2024 – May 2025 Relevant Coursework: Distributed and Operating Systems, Mobile and Wireless Networks, & Algorithms for Data Science

University of Massachusetts Amherst GPA 3.78/4.0

Bachelor of Science in Computer Science and Applied Mathematics Sep. 2021 – May 2024 Relevant Coursework: Programming Methodology, Software Engineering, & Algorithms Technical Skills

Languages: Java, JavaScript, Python, C++, C, SQL

Frameworks & Libraries: React, Node.js, Flask, Socket.IO, Apache Commons, TCP/IP Tools & Platforms: AWS, Git, Firebase, Docker, Linux, Microsoft Office, Agile, OOD Work Experience

Wireless and Sensor Systems Laboratory May. 2024 – Jun. 2025 Research Assistant - Wearable Healthcare Devices, Implantable Sensors, LiDAR Amherst, MA

• Worked extensively with diverse sensor systems for medical and defense applications, including LiDAR, EEG, pressure, thermal, and motion sensors, to collect, process, and analyze complex data from over 100 hours of multimodal recordings.

• Designed and 3D printed wearable medical devices using CAD software for project applications.

• Integrated sensor hardware with Python-based data acquisition pipelines, improving real-time signal stability and reducing data loss by over 15%.

• Built machine learning models (CNN, LSTM) to classify physiological signals, achieving up to 96% accuracy in seizure detection and over 98% accuracy in joint load prediction.

• Conducted field data collection using integrated sensor systems and ensuring data quality in novel environments. Publications

Hardware-Assisted Privacy-Preserving Multi-Channel EEG Computational Headwear [Paper] IEEE BSN 2024 - Abdul Aziz*, Bhawana Chhaglani*, Amirmohammad Radmehr, Joseph Collins, Jeremy Gummeson, Sunghoon Ivan Lee, Ravi Karkar, and Phuc Nguyen

• Introduces a novel Combined Privacy Metric to enhance data privacy in edge computing for wearable EEG-based medical devices and demonstrates an EEG-based seizure detection using a 1D CNN architecture, achieving accuracy of 96.25%

Projects

Drone Mapping Python, pandas, OpenCV, PyTorch Mar. 2025

• Contributed to a research initiative aimed at drone detection and tracking using LiDAR and thermal cameras, with applications in defense and entertainment.

• Led all field data collection efforts, including full hardware setup, sensor calibration, and synchronized data acquisition during on-site testing in Michigan.

• Calibrated and spatially aligned LiDAR and thermal sensors to ensure accurate mapping and sensor fusion.

• Contributed to the implementation of a neural network achieving 97.79% accuracy in drone detection from fused sensor data.

UMass Meal Builder JavaScript, Python, React, Node.js, Firebase, Git, SQL Feb. 2023

• Formulated a website that generates personalized meal plans based on user dietary restrictions using UMass dining options.

• Implemented a secure user login system using Google Firebase for authentication.

• Built user account pages with secure authentication, utilizing React, and integrating SQL for secure data management

• Developed a Python web scraping program to extract data from the UMass website on a daily basis.

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