Leveraged stochastic processes on networks using differential equations to determine disease susceptibility rates and recovery probabilities, employing sophisticated mathematical and epidemiological models for better analysis and modelling of infectious diseases spread.

Developed a Spectral Decomposition-based algorithm integrating filter-wrapper techniques with feature clustering, utilizing the Rand Index cluster metric for enhanced selection precision. Employing multi-processing and parallel programming for high performance computational efficiency, rendering it ideal for real-world predictive models.

Developed payload system for an automated radio frequency-enabled camera aboard a NASA USLI launch vehicle (sub-scale rocket, operating at an altitude of 6000 fts. Using demodulated telecommand signals from a SDR Receiver, the system efficiently executes image processing techniques with custom functions. A microcontroller, equipped with custom GPIO pin drivers, serves as the central processing unit, seamlessly integrating hardware components. The resulting camera system effectively utilizes radio frequency capabilities to trigger image processing algorithms, functioning reliably even at altitudes of 6,000 feet. Implementation involves signal demodulation within a UDP server architecture for streamlined data transmission and complex image processing operations in response to SDR receiver commands.

Developed algorithms for automated scheduling and coordination of advanced weapon systems in naval warfare by integrating Markov Chains and Naïve Bayesian Classification. The methods involve using a Markov chain to track variables and predict future states, and employing supervised learning and statistical classification to classify data and optimize weapon pairings.