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Click here or scroll down to respond to this candidateCandidate's Name
Computer Engineer Graduate from the University of Maryland, College Park
Ellicott City, MD, Street Address
PHONE NUMBER AVAILABLE
EMAIL AVAILABLE
During my studies and work experience I developed my keen eye for detail and a
strong understanding of computer science technology, important practical skills
needed for any software profession.
At the University of Maryland, I was involved in an intensive research and development
project in which I used machine learning to significantly improve object recognition
algorithms. Using data gathered from the National Oceanic and Atmospheric
Administration (NOAA) and their GOES-16 satellite, I was able to create a remote
sensing Neural Network capable of taking in sequences of cloud satellite imagery and
outputting accurate predictions for the next hour. This project importantly shows that I
can apply my learnings across various different backgrounds; even without any
previous meteorological experience, I was still able to create a predictive
Convolutional Neural Network for cloud forecasting.
In addition to my coursework, I also have more practical experience. I worked under
Professor Rajeev Barua to assist in the implementation of a new cybersecurity detection
model, where I implemented Google Chrome web extensions to track various user
metrics to assist in threat identification in systems. In this venture, I was able to hone my
backend programming skills by implementing database management for the
data-scraping extension tools. I am comfortable with practical web-development
applications as a result of my internship's learnings.
Currently, I am working on a SVM Classifier that will try to diagnose breast cancer tumors
as malignant or benign based on physical attributes of the tumor such as its area,
perimeter, concavity, etc. Afterwards, I will look towards combining the model with a
CNN built for identifying such metrics off an image alone. Together, they will hopefully
be able to assist in tumor classification through image mediums alone.
Thank you for considering my application. I look forward to the opportunity to discuss in
depth how my background, skills and interests align with the needs of your team. I am
available for an interview at your convenience and can be contacted at PHONE NUMBER AVAILABLE
or by email at Candidate's Name 5108@gmail.com.
Sincerely,
Candidate's Name
Candidate's Name (He/Him)
Ellicott City, MD | 312-933-9622 | EMAIL AVAILABLE | https://github.com/Jonathan5108
EDUCATION
University of Maryland College Park, MD
B.S., Computer Engineering, GPA: 3.27 May 2024
Honors College, University Honors May 2020
SKILLS
Software Languages:
Proficient in Java, C/C++ (Assembly), Python, JavaScript, HTML, SQL
Adequate in OCaml, Ruby, Rust, Android Studio
Certifications: HTML, Deep Learning ML Models
Noted Interests: Artificial Intelligence/Machine Learning models specialized in object detection,
classification, and learning. Cybersecurity threat detection. App development.
TECHNICAL EXPERIENCE
Endpoint Detection Cybersecurity Research May. 2023 Jan. 2024
University Sponsored Research Intern
Worked under Professor Rajeev Barua at the University of Maryland to implement an innovative
take on the standardized Endpoint Detection and Response (EDR) cybersecurity approach.
Personally responsible for the creation of chrome-extension tools through primarily JavaScript
and HTML that allow for data collection of user browser history and behavior, all of which are
integrable in other projects
Project Experience
Cloud Analysis and Tracking using GeoStat Satellite Imagery Feb 2024 May 2024
Utilized various Machine Learning Convolution Neural Network based models (CNN,
LSTMConv) to detect & track cloud, creating visualized predictions of future cloud
movements.
Created image interpolation model to simulate possible cloud movements between NOAA
satellite images, filling in missing data between the 15 min snapshot intervals of the
2016 NOAA satellite
geekOS Operating Systems Project, University of Maryland CMSC412 Aug. 2023 Dec. 2023
Implemented functionalities necessary of a Linux-based operating system in C including but not
limited to forking, piping, filesystems, paging, per-CPU variables, and signaling
Created tests capable of analyzing aforementioned functionalities across various scenarios and
edge cases.
Pac-Man Computer Vision Focused AI Project Jan. 2023 May. 2023
Engineered intelligent AI algorithm in Python to enhance Pac-Man s decision-making when
confronted with different game states
Applied machine learning techniques for dynamic adaptation to game strategies throughout
different runs, including but not limited to natural language processing, search algorithms,
reinforcement learning, and classification algorithms.
ACTIVITIES/AFFILIATIONS
UMD Cybersecurity Club, Member Aug. 2022 Present
Pickleball Club, Member Aug. 2023 Present
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