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PhD in Computer Science

University of Maryland at College Park

MS in Computer Science

Georgia Institute of Technology

Specialization in Computational Perception & Robotics

BS in Physics

University of North Carolina at Chapel Hill

Specialization in Astrophysics

Summer Graduate Research Intern

National Consortium for the Study of Terrorism and Responses to Terrorism (START)

Co-authored From Protest to Proxy War: A Socio-Technical Overview of the Evolution of Hacktivism, a white paper examining ideologically motivated cybercrimes and their intersection with modern conflict, psychology, and state involvement.

• Analyzed cyber-attack patterns in the 21st century, including major hacktivist operations during the 2025 Iran-Israel conflict and earlier campaigns following the 2022 Mahsa Amini protests in Iran.
• Modeled pathways state involvement in hacktivist cells, including state-encouraged 'proxy hacktivism' exemplified by Russia's KillNet and Ukraine's IT Army where governments covertly guide or seed target lists for semi-independent hacktivist collectives.
• Assessed emerging cyber threats such as AI-assisted social engineering/phishing, ransomware-as-a-service (e.g., GhostSec's GhostLocker), deepfake-enabled social engineering, and drone hijacking of cyber-physical systems.

Machine Learning & Hardware Engineer Science Collaborator

NASA Goddard Space Flight Center

Collaborated with NASA researchers to develop a unique Linux build and testing platform to evaluate communications-limited deep learning algorithms on Xilinx’s Zybo.

• Performed benchmark analysis to cross-compare the FPGA performance with other development boards and application specific integrated circuits with regards to accuracy, speed, memory usage, and performance.
• Trained a new classified hyperspectral dataset to develop a TFLite model integrable with the Zybo platform.

Autonomy & Robotics Rotational Researcher

U.S. Naval Research Laboratory, Department of the Navy

Collaborated with NRL researchers on a cross-organizational project focused on herding of non-cooperative robots in complex environments.

• Simulated and experimentally validated a previously proposed approach for a pursuer-evader strategy involving navigation around convex obstacles to a goal location.

Operations Research Analyst / Autonomous Systems Scientist

NAWCAD Patuxent River, Department of the Navy

Project lead for three internal multi-agent autonomous systems development projects.

• Explored centralized vs distributed coordination architectures to evaluate how communication constraints affect multi‑agent task allocation and collaboration efficiency.
• Built a modular autonomous systems framework and conducted large‑scale simulation experiments (hardware testing paused amidst COVID restrictions); findings were presented at three internal Navy conferences.
• Extended the framework to handle dynamic environments through moving‑obstacle navigation, multi‑task optimization, and collaboration planning to minimize path conflicts.

Dean's Fellowship

The Graduate School at UMD College Park

A Framework for Black-Box Controller Design to Automatically Satisfy Specifications Using Signal Temporal Logic

2025 International Conference on Unmanned Aircraft Systems (ICUAS)

We present a framework for including human readable specifications in the design of black-box autonomous systems, or systems whose construct are prohibitively complex to analyze or intuit.

Onboard Hyperspectral Image Classification via Transfer Learning for Communication-Limited Spacecraft

2022 IEEE Aerospace Conference (AERO)

This research explores building robust classification models for onboard data processing where training data is highly limited using transfer-learning techniques. Here, we focus on the use case of hyperspectral imaging for remote sensing, a domain where the high dimensionality of the data from the sensor can rapidly saturate the downlink bandwidth.

η Geminorum: An Eclipsing Semiregular Variable Star Orbited by a Companion Surrounded by an Extended Disc

Monthly Notices of the Royal Astronomical Society

We report 11 yr of spectroscopic monitoring of the M-type asymptotic giant branch star η Gem, a semiregular variable and a known spectroscopic binary with a period of 8.2 yr. We combine our radial velocities with others from the literature to provide an improved spectroscopic orbital solution, which we then use to predict past times of eclipse.