Innovative and seasoned technology leader with over 20 years of multifaceted experience in leading successful engineering initiatives and driving organizational growth interested in transitioning into a role that bridges the gap between quantum research and conventional tech paradigms, furthering the integration of quantum technologies into practical, real-world applications. Equipped with skills developed in graduate and doctoral level programs in Quantum Computing and AI/Deep Learning techniques. I’m seeking a challenging role where I can leverage my expertise in strategic planning, team management, and technology implementation to pushing the frontiers of Quantum Computing and further the integration of Quantum technologies into practical, real-world applications.
ECE 802 – 730
Quantum Sensor and
Research into quantum mechanics needed to engineer quantum systems for computation, communication, and sensing. Topics included: motivation for quantum engineering, qubits and quantum gates, rules of quantum mechanics, mathematical background, quantum electrical circuits and other physical quantum systems, harmonic and anharmonic oscillators, measurement, the Schrödinger equation, noise, entanglement, benchmarking, quantum communication, and quantum algorithms.
- Systems Architecture – Trapped Ion / Superconducting
- Quantum Computational Algorithms – Fourier Transform, Amplitude Amplification & Hybrid Quantum/Classical
- Python Software – Google Cirq
Analysis, modeling and verification in continuous and discrete dynamics of embedded cyber-physical systems (CPS). Design and implementation of CPS including sensors and actuators, embedded processors, Internet of Things (IoT), cloud IoT, multitasking, and scheduling.
- Hybrid Systems
- Composition of State Machines
- Concurrent Models of Computation
Concentration on the fundamental aspects of Evolutionary Computation including history, theory and application – with an emphasis on search & optimization. Focused study on the many aspects of evolutionary algorithms (EAs), in particular GA, GP, ES, and will concentrate on the basic concepts of representation, operators and overall control.
- Linear Genetic Algorithms & Programming
- Multi-objective Optimization
- Evolutionary Optimization Algorithms
- Search Methodologies
ECE 802 – 731
Research into the unique properties of diamond including: thermal conductivity, extreme hardness, wide band-gap, large electric field breakdown strength, electron mobility, radiation hardness, electrochemical performance, and chemical inertness. State-of-the-art diamond applications and potential areas for expansion in electronics, optics, sensors, MEMS, wear/cutting, quantum computing, and thermal management.
- Diamond Growth
- Superconducting Transmon Qubits
- Lab Engineered Nitrogen-Vacancy Diamond
Elements of deep neural networks. Adaptive and learning processes. Deep Feedforward and Convolutional Neural Networks. Recurrent Neural Networks and their variants (e.g. LSTMs, GRUs). Formulations of Reinforcement learning. Implementation and Deployment.
- Multilayer Perceptrons
- Convolutional and Recurrent Neural Networks
- Training Deep Neural Networks
- Generative Probabalistic Modeling
Applications of quantum mechanics and statistical mechanics in solids: Lattice dynamics, energy bands, equilibrium/non-equilibrium properties, charge scattering and transport in semiconductors.
- Atomic Bonding
- Crystalline Structures
- Energy Bands – 1D, 2D, 3D Lattices
- Infinite/Finite Well
- Thermal Conductivity & Heat Capacity
- Onsagar Relations