Engineering leader building intelligent physical systems. I built and lead the Control Systems Engineering team at SharkNinja, a cross-functional group shipping sensing, control, and embedded intelligence into 30+ globally distributed consumer products. Inventor on 12+ patents (4 granted), author of 40+ peer-reviewed publications, reviewer for multiple IEEE journals and Technical Program Committee member for IEEE conferences. Previously Assistant Professor (SUNY Poly), Research Scientist (NTU Singapore), and Postdoctoral Researcher (Penn State). Ph.D., Penn State (2015).

Leadership & Impact

• Built the Control Systems Engineering function at SharkNinja from a single hire into a cross-functional team supporting 20+ product lines. Established the promotion ladder, code review culture, on-call rotations, and technical review process from scratch
• Delivered algorithms and embedded software into 30+ globally shipped products across coffee, beverage carbonation, thermal cooking, frozen treat, and Shark beauty systems (full portfolio)
• Built internal engineering platforms: Python-based MCU communication service, Raspberry Pi / Arduino HIL infrastructure, and evaluation frameworks used across product lines (portfolio)
• Driving AI-assisted engineering adoption: Claude Code, OpenAI Codex, and LLM workflows integrated into code generation, R&D ideation, data-analysis pipelines, and MCP-integrated Confluence documentation. Same headcount supports approximately 40% more concurrent projects (portfolio)
• Cut development cycle time by roughly 20% through modular software architectures and engineering process design, in a fast-paced consumer-products environment where product cycles are already short

AI-Assisted Engineering

Two initiatives at SharkNinja that together let the same team support approximately 40% more concurrent projects:

• Team-wide LLM adoption: standardized Claude Code and OpenAI Codex across the Control Systems team for code generation, R&D ideation, data-analysis pipelines, code review, changelog automation, and MCP-integrated Confluence documentation
• Internal AI product-diagnostic tool that lets non-engineers (product managers, QA, customer-support) ask product-specific questions and upload unit CSV telemetry to identify software or hardware issues, freeing controls-engineering bandwidth

See portfolio for details.

IEEE Editorial & Community Service

Reviewer for multiple IEEE journals and Technical Program Committee member for IEEE conferences. Author across IEEE journals and conference proceedings. Active IEEE member; publications in IEEE Transactions on Automatic Control, IEEE TAES, Applied Energy, Knowledge-Based Systems (Google Scholar).

Selected Prior Roles

• Assistant Professor & Principal Investigator, SUNY Polytechnic Institute (2018–2021). Led externally funded research; taught graduate and undergraduate courses; deployed IoT pavement monitoring on Raspberry Pi + AWS (IEEE iThings 2021; portfolio). Also collaborated with CS colleagues on anomaly/fault detection research (portfolio). Co-founded Ocean Dynamex.
• Research Scientist, Nanyang Technological University, Singapore (2016–2018). Green Building Innovation Cluster. Distributed HVAC control platform (server plus Raspberry Pi edge fleet) achieving 12–13% energy savings in occupied buildings (Applied Energy; portfolio).
• Postdoctoral Researcher, The Methodology Center, Penn State (2015–2016). Control-theoretic methods applied to behavioral health interventions.
• Ph.D., Penn State (2010–2015). From Data to Interventions: Using System Identification and Robust Control Algorithms to Design Effective Treatments. Advisor: Prof. Constantino Lagoa. Minor Ph.D., Industrial Engineering (Convex Optimization). (Portfolio: 10 papers linked.)
• M.S., Northeastern University (2008–2010). Vision Based Control of an Autonomous Blimp with Actuator Saturation. Advisors: Profs. Mario Sznaier and Bahram Shafai.

Expertise

Control: MPC • Distributed MPC • Robust & Adaptive Control • Nonlinear Control • Real-time Optimization • System Identification • Motion Control • Robotics & Computer Vision-Based Control (research and applied) Systems: System Identification • Sensor Fusion • Embedded Systems • IoT & Edge Computing • HIL Testing • Electromechanical Actuation Leadership: Team building • Roadmap & strategy • Cross-functional delivery • AI-assisted engineering (Claude Code, Codex)