About me

Lam Nguyen

Machine Learning Researcher located in New York

Experience as Machine Learning Researcher and Software Engineer working on multiple projects and expertise in the design, installation, testing, and maintenance of software systems.

Machine Learning: Strong grasp of ML technologies including Deep Learning and Neural Networks. My research centers on continuous user authentication using behavioral biometrics with models like SVM, Random Forest, KNN, GMM, CNN, RNN, and Manhattan Scaled Distance.

Front-End: Proficient in JavaScript, TypeScript, Python, and HTML/CSS. Experienced with React, Redux, MobX, and UI libraries like Material UI, Bootstrap, and Tailwind CSS.

Back-End: Skilled in NodeJS, ExpressJS, and Rails for backend architecture and routing. Experienced with ORMs like Mongoose and Active Record, using MongoDB and PostgreSQL for database management.

Testing: Minimizing unexpected errors and maintaining more than 85% test coverage by using Jest, and React Testing Library in TDD.

Git Version: Solid understanding of Git version to track for source control and branches, handle push, pull, and stash commits while maintaining the latest up-to-date version of the code without merge conflicts.

Environment & Tools: Experienced with Agile, Jira, GitLab, and GitHub. Collaborate with DevOps teams on CI/CD pipelines, with hands-on experience in Docker and AWS Cloud.

Most Recent Employment

Machine Learning Researcher at NYIT’s LAMP Lab

JANUARY 2024 - PRESENT

NYIT’s LAMP Lab, focusing on continuous authentication systems and behavioral biometrics under the mentorship of leading cybersecurity scholars.

My main research project involves developing a continuous user authentication system using behavioral biometrics such as keystroke dynamics and mouse dynamics.

Designing and implementing sophisticated authentication systems for mobile devices and telerobotics, with a focus on machine learning models such as Support Vector Machines (SVM), Scaled Manhattan Distance, Random Forest, K-Nearest Neighbors (KNN), and Gaussian Mixture Models (GMM) to enhance model accuracy and robustness.
Spearheading experiments to capture, analyze, and interpret data from accelerometers, gyroscopes, and 3D motion capture devices, developing robust methodologies for feature extraction and optimizing models to identify unique behavioral patterns.
Collaborating closely with an interdisciplinary team, fostering innovative approaches to bolster security across digital and mobile platforms.
Specializing in the optimization of gesture-based authentication, gait recognition, and other behavioral biometrics, driving developments in user-specific authentication mechanisms.
Contributing research findings to top-tier journals and presenting at major conferences, actively shaping discourse within the academic and professional communities.
Engaging with industry leaders to align academic research with practical cybersecurity applications, bridging the gap between theoretical development and industry relevance.
Providing mentorship and support to emerging researchers, fostering a collaborative learning environment within the lab and the broader academic community.
Practiced Integration testing to test different components of the application in combination to assess if they work correctly together, ensuring there are no new bugs generated during development.
Published Paper as Assistant Researcher: Posture and Body Movement Effects on Behavioral Biometrics for Continuous Smartphone Authentication. In IEEE Transactions on Biometrics, Behavior, and Identity Science (T-BIOM), vol. 10 pp. 1–1, 2024

To view more information about my employment and download, please visit Resume

Education

PhD in Computer Science at NYIT

JANUARY 2024 - PRESENT New York City, New York

Honors: summa cum laude (GPA: 3.70)

MS in Business Analytics at Adelphi University

JANUARY 2020 - DECEMBER 2020 Garden City, New York

CeDiD: 21TJ – IQ05 – HONG
Honors: summa cum laude (GPA: 3.59)

Software Engineering Certificate Program at Flatiron School

DECEMBER 2021 - APRIL 2022 Garden City, New York

Learned and built hand-on experience full stack software engineer with React, JavaScript, PostgreSQL, Ruby on Rails, and more.

To view more information about my employment, education, skills and download my resume, please visit Resume

About

Lam Nguyen

Machine Learning Researcher at NYIT’s LAMP Lab

PhD in Computer Science at NYIT

MS in Business Analytics at Adelphi University

Software Engineering Certificate Program at Flatiron School

Lam Nguyen

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