Directed the design and deployment of control systems, embedded SW and algorithms across a diverse range of SharkNinja appliances, including coffee systems, beverage carbonation platforms, thermal cooking products, frozen treat makers, high-speed blenders, and Shark beauty products. Oversaw system architecture, algorithm development, and production integration to enable intelligent, consistent, and user-centric product performance.
Drove Claude Code and OpenAI Codex adoption across the SharkNinja Control Systems team. Same headcount now supports approximately 40% more concurrent projects. Also led an internal AI diagnostic tool that lets non-engineers ask product questions and analyze CSV telemetry to identify software or hardware issues.
Led development of barista assist technology, milk froth control algorithms, and temperature control systems for the Ninja Luxe Cafe series.
Designed and shipped controllers and embedded algorithms (cascade temperature control, flow control, failure detection, altitude calibration) into four Ninja coffee and tea products from prototype through mass production.
Led controls and algorithm development for the Ninja Thirsti carbonated beverage platform (two product generations shipped). Three patents pending covering CO₂ estimation, liquid-temperature detection, and carbonation system architecture.
Built the internal Python/Serial data-collection GUI and sensor profiler used across SharkNinja beverage and heated-product R&D — real-time MCU communication, CSV logging, live plotting. Early SharkNinja project (Senior Systems Engineer, 2022); still used across product lines today.
Externally-funded research (Assistant Professor, SUNY Poly): a low-cost IoT platform for wireless structural monitoring of asphalt pavement. Solar-powered edge nodes, LTE/4G uplink, AWS backend. Published at IEEE iThings 2021.
Distributed MPC and IoT platform for commercial-building HVAC, deployed on an 85-zone pilot at Nanyang Technological University. Delivered 12–13% measured energy savings in occupied space.
PhD dissertation research at Penn State (2010–2015): sparse and randomized system identification algorithms for noisy, incomplete data, with applied deployments across behavioral health, radar tracking, thermal modeling, and forecasting.
Cross-disciplinary research at SUNY Polytechnic Institute (Assistant Professor, 2018–2021), collaborating with CS colleagues in Research Group X∞ on anomaly and fault detection algorithms for cyber-physical systems and IoT.