David J. Edelist

I'm

About

I’m an aspiring computer engineer passionate about the intersection of software, hardware, and artificial intelligence. At Massachusetts General Hospital's Martinos Center for Biomedical Imaging, I gained hands-on experience in Deep Learning and image processing. This summer, I completed an electrical engineering internship at Textron Aviation, where I designed a convertible avionics trainer for the Garmin G3000 and G5000 Avionics Suites. Combined with my coursework in logic design, computer organization, HDLs, and FPGA development, my diverse expertise across electrical engineering, deep learning, and software bridges the gap between hardware and software.

Current Education: Bachelor of Science
Major: Computer Engineering

Cumulative GPA: 3.77/4.0
Phone: +1 (857) 328-3986

City: Boston, MA & Toronto, ON
Email: jedelist@bu.edu

Interests

Software Engineering

Machine Learning

Computer Vision

FPGA Development

Digital Logic Design

Visualization

Algorithms

Image Processing

Education

Bachelor of Science in Computer Engineering

September 2022 - Present

Relevant Coursework

Machine Learning
Computer Organization
Algorithms & Data Structures in C++
Digital Logic Design
AMD/Xilinx FPGA Development
Software Engineering

International Baccalaureate (IB) Diploma

September 2017 - May 2022

Relevant Coursework

IB Higher-Level Physics, Chemistry, Math
41/45 IB Diploma Total; 96% OSSD Average

Skills

Experience

TRU Simulation - Textron Aviation

June 2024 - August 2024

Electrical Engineering Intern

Designed novel flight desktop trainer systems using the Garmin G3000, and G5000 Avionics Suites.
Collaborated with a peer to design all official system schematics, system prints, wiring diagraoms, parts lists, and cable drawings to support the modular design and future scalability.
Interfaced Garmin avionics systems with UEI Data Acquisition Cards, avionics computers, host computers, and cockpit input/output distributions, ensuring efficient communication and integration across all components.
Designed printed circuit boards, circuitry and solutions for annunciator panels and cockpit input/output distributions.

Massachusetts General Hospital Athinoula A. Martinos Center for Biomedical Imaging & The Boston University Bio Optical & Acoustic Spectroscopy (BOAS) Lab

June 2023 - May 2025

Undergraduate Researcher & UROP Grantee

Awarded the Undergraduate Research Opportunity Program Grant from Boston University for three semesters.
Trained several U-NET (CNN) configurations on real and synthesized PS-OCT images to iteratively improve performance.
Maximized vessel and enlarged perivascular spaces (EPVS) segmentation accuracy when used on post-mortem PS-OCT brain images of diseased tissue.
Achieved 87% testing accuracy by leveraging several training, optimization, fine-tuning and data augmentation techniques. Outperformed human labels on testing volumes, as verified by EPVS and vessel pathology expert.
Wrote functions to convert the U-NET segmentation predictions to 3D graph structures, then used the graph structures to compare brain tissue affected with neurodegenerative diseases to control cases using machine learning techniques and statistical analyses. Used known disease staging to validate pathological conclusions drawn using my segmentation and analysis methods.
Implemented the Fast Fourier Transform (FFT) algorithm using Nvidia CUDA to leverage GPU acceleration and reduce imaging and data acquisition overhead by 75%.

Axiom Learning

July 2023 - May 2024

Pre-calculus, math, and ISEE Tutor

Tutored student on the verbal reasoning and reading comprehension sections in preparation for the ISEE.
Taught calculus fundamentals to a high school student and assisted with the university application process.