Work with thought leaders and academic experts in acoustics ultrasonics

I am dedicated and passionate about inspiring and engaging my students in an effective learning process to generate new knowledge, do innovations, engage in technology transfer, and enhance human capital through interdisciplinary and collaborative research for the well-being of academia, industry, and society.

I have over 20 years of engineering and R&D experience in sensors and MEMS including physical modeling, transduction, design, optimization, fabrication, characterization/test, and algorithm development, as well as 10 years of technical management/executive experience in operations, product development, R&D, business development, marketing and technical sales. I have a track record of success in taking early stage R&D concepts through to full products, and developing and growing businesses based on those products. I hold a PhD in Electrical Engineering from the University of Florida, where I focused on sensor and instrumentation development, leading to 20 years of academic/industry experience in research, modeling, optimization, microfabrication, and testing of scientific instruments that requires in-depth knowledge of multidisciplinary physical systems (mechanical, electrical, acoustic, fluidic, thermal, and optical). I am well versed in MATLAB and LabVIEW, as well as first-principles development of lumped element modeling (LEM) for physical systems of all kinds. As the former CEO of an innovation-driven startup, my most important roles were defining the long-term vision and strategy, and building the teams and the people to make it all happen.

I am passionate about solving big problems with scientific and computational tools. A highly experienced applied mathematician working in academia (faculty) and industry (consulting), with 15+ years of research and teaching expertise in inverse problems, signal processing, and data science. A highly-skilled software engineer and analyst/architect with 6+ years of experience as a technical lead in professional software development.

I am a lecturer at the University of California, Davis, teaching undergraduate students in physics and engineering basic and advanced physics. I also collaborate with several experimental and theory groups in condensed matter physics all over the globe focussing on critical phenomena, quantum magnetism, topological materials, transport properties, and driven quantum systems. My current interests lie in Hilbert Space fragmentation and associated critical phenomena for systems with subsystem symmetries. Additionally, I use the numerical linked cluster expansion to study heavy fermion compounds of interests to groups in John's Hopkins and Princeton Universities.

As a PhD in Materials Sciences with a robust background in project management and research, I specialize in nanotechnology, particularly in renewable energy and semiconductors. My career spans across significant roles , where I have led cross-functional global teams, managed substantial research projects, and developed innovative technologies. I have a proven track record of securing funding, crafting compelling business cases, and forging strategic partnerships. I am fluent in English, French, and Spanish, and am adept at engaging diverse stakeholders. My passion lies in leveraging my expertise to drive groundbreaking research and innovation in the clean energy sector. My commitment to sustainability and technical acumen align perfectly with the collaborative goals of NotedSource.

Dr. Troy Trottier is an experienced principal research scientist and director of luminescent materials. He has over 20 years of experience in materials science and engineering, electrical engineering, and semiconductor devices. He holds a PhD in Materials Science and Engineering from the University of Florida, and a B.S in Electrical Engineering from Western New England University. He currently works as a Principal Research Scientist at Kyocera SLD Laser and Director of Luminescent Materials at Soraa LED. Dr. Trottier is an expert in the area of materials science, specializing in semiconductor material systems. He is also experienced in the development of LED and laser-based products for the lighting and display markets.

I am a applied physicist, including an MS and a PhD. My expertise encompasses a distinctive skill set that encompasses artificial intelligence, deep learning, machine learning, generative AI, quantum optimization, and quantum artificial intelligence. With 4+ years of experience (post PhD) in leading the research and development teams, my focus has primarily been on utilizing machine learning and deep learning to address various scientific and business problems. I also possess hands on experience with IBM's Quantum Qiskit Runtime, and D-Wave's quantum optimizers with QUBO and Leap.

Worked for First Solar LLC, Intel Co, various universities, studied device physics and reliability problems

Retiring physics professor looking to maintain professional activity

**Professional Profile**           ·         160+ of published works, including granted patents, journal articles, and one sci-fi novel ·         Expert in a wide range of technologies: automotive and architectural glazing; photovoltaics; 5G compatibility; information displays; semiconductors; TFTs; materials and devices; Intellectual Property ·         Product conceptualization, design, modeling, development, and industrialization ·         Formal training in Intellectual Property and experience of working in an IP company ·         Knowledge of innovation, R&D, and industrial methodologies ·         Solid experience in presenting at technical workshops and scientific symposia

I am interested in all things quantum. My research interests lie in and around the following * Quantum Information * Condensed Matter * Quantum Optics Particularly, I find myself fascinated by problems at the intersection of two or more of these fields. I also quite like quantum machine learning, and topics revolving around that. I enjoy thinking about problems in quantum dynamics which hold information/coding theortic aspects as well. This has led to a natural inclination towards many-body physics and quantum error correction. <br> <br>