Nick Singstock
Co-founder And CTO at Mana Battery, Inc.
Boulder, Colorado, United States
Summary
👤
Senior🎓
Top SchoolNick Singstock is a battery scientist, entrepreneur, and co-founder/CTO at Mana Battery, driving the commercialization of advanced sodium battery materials and cells for safe, low-cost grid storage and EVs. With a PhD and postdoctoral training in chemical engineering from the University of Colorado Boulder and eight years of R&D experience, he blends deep electrochemical expertise with hands-on product development and scaling. He has a track record of translating lab-scale innovations into practical solutions, informed by industry internships and process engineering roles. Nick also brings computational and algorithmic acumen from open-source contributions to Qiskit, where he implemented an Analytic Quantum Gradient Descent optimizer—an uncommon crossover between quantum optimization and battery materials research. Based in Boulder, he is focused on sustainable, equitable energy transitions and building teams that move breakthrough materials toward real-world impact.
8 years of coding experience
3 years of employment as a software developer
Doctor of Philosophy - PhD, Chemical Engineering, Doctor of Philosophy - PhD, Chemical Engineering at University of Colorado BoulderB.S. Chemical and Biomolecular Engineering, Chemical Engineering, 3.86, B.S. Chemical and Biomolecular Engineering, Chemical Engineering, 3.86 at The Ohio State University
Github Skills (10)
algorithm10
circuit10
quantum-computing10
qiskit10
optimisation10
optimizers10
python10
optimization10
numpy9
sdk9
Programming languages (2)
Github contributions (5)
qiskit-community/qiskit-aqua
Mar 2019 - Mar 2019
Quantum Algorithms & Applications (**DEPRECATED** since April 2021 - see readme for more info)
Role in this project:
Back-end Developer
Back-end DeveloperContributions:10 commits, 1 PR, 3 comments in 10 days
Contributions summary:Nick primarily contributed to the development of the `AQGD` (Analytic Quantum Gradient Descent) optimizer within the Qiskit-Aqua framework. Their work involved creating and updating the `AQGD` optimizer class, including its core functionalities for analytical gradient descent optimization. They also integrated the optimizer into the broader framework by updating the optimizer and benchmark modules, and created a benchmarking notebook to test the optimizer. This suggests a focus on implementing and integrating optimization algorithms within a quantum computing context.
aprilquantum-computingquantum-algorithmsmore-infoquantum-programming-language
Qiskit/qiskit
Mar 2019 - Mar 2019
Qiskit is an open-source SDK for working with quantum computers at the level of extended quantum circuits, operators, and primitives.
Role in this project:Back-end Developer / Data Scientist (Likely focused on Optimization within the Quantum Computing domain)
Back-end Developer / Data Scientist (Likely focused on Optimization within the Quantum Computing domain)Contributions:8 commits in 6 days
Contributions summary:Nick's primary contribution is the creation of the `AQGD` (Analytic Quantum Gradient Descent) optimizer class. This class implements a gradient descent optimization algorithm specifically designed for use with quantum circuits. The code involves calculating derivatives, updating parameters, and determining convergence within the context of an objective function evaluated by a quantum circuit. This suggests a focus on optimization techniques applicable to quantum algorithms and potentially related to machine learning applications in a quantum computing framework.
pythonquantum-circuitsquantum-computingcircuitsquantum-circuit
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