Utkarsh Singh

WORK HISTORY

EDUCATION

ABOUT UTKARSH SINGH

Welcome to my LinkedIn profile! I am a dedicated physicist, an entrepreneur, and a passionate advocate for the transformative field of quantum machine learning. Currently, I am deep into my Ph.D. journey, focusing on developing advanced algorithms and models that harness the intersection of quantum computing and machine learning. My work has led to significant achievements, including filing two patents and being honoured with a Student Award from Deep Tech Canada in partnership with the National Research Council of Canada for my presentation on \"A Resource Efficient Quantum Kernel\" at the Quantum Days 2024 Conference. This recognition underscores my commitment to advancing the frontier of quantum research. Professionally, I am a Qiskit Advocate and an IBM Certified Quantum Developer. I also serve part-time as a Senior Manager/Consultant in the quantum machine learning team of G2Q Computing, where I apply my expertise to solve real-world challenges and fuel innovation in quantum technologies. Beyond academia and corporate roles, I am an entrepreneur at heart. I founded an e-commerce startup, which sharpened my skills in managing time, people, and resources—experience that I now bring to the quantum machine learning domain. I offer consultancy, project building, mentorship, and extensive support to startups navigating the complexities of quantum technologies. My research interests span quantum ML/AI, data encoding in quantum machine learning, quantum simulation, and exploring quantum reservoir computing. I am particularly excited about the potential of quantum technologies to revolutionize space exploration. I envision quantum computing enhancing exoplanet discovery, optimizing deep space communication, and advancing navigation systems. Thank you for connecting here. I look forward to exploring how we can leverage quantum breakthroughs to solve complex, real-world problems together. Feel free to reach out if you’re interested in learning more or discussing potential collaborations in quantum machine learning and its applications in various domains.