Raman Pandey is a graduate student in Electrical and Computer Engineering at the University of New Mexico (UNM) and a graduate research assistant at the Center for High Technology Materials (CHTM), advised by Prof. Marek Osinski. He specializes in Quantum Information Science, machine learning, and FPGA-based systems. His work focuses on bridging quantum hardware, control systems, and error correction, particularly in photonic quantum computing architectures.
Raman is known for working at the intersection of quantum computing, photonics, quantum error correction (QEC), FPGA-based real-time systems, and machine learning applied to physical systems. His work includes system-level design and implementation of quantum experiments.
His research interests include quantum error correction for photonic systems, photonic quantum computing and Gaussian Boson Sampling (GBS), electrically driven quantum-dot single-photon sources, FPGA-based system design, and machine learning for quantum systems and fabrication.
Research projects (details and posters at ramanpandey.com/projects.html):
Personal and creative projects:
An interactive version of this list lives at ramanpandey.com/skills.html.
Hardware: FPGA design (VHDL), Verilog and RTL design, embedded systems and microcontrollers, digital electronics, analog electronics, lab instrumentation and test, LabVIEW, PCB design and prototyping.
Quantum: photonic quantum computing, Gaussian boson sampling systems, MZI interferometry and photonic unitaries, single-photon detection (SNSPD / SPAD), Qiskit and quantum programming, quantum error correction, quantum circuit simulation, quantum optics.
Software: Python, C and low-level programming, JavaScript and creative coding, Django and REST APIs, Node.js, MATLAB, R and statistical computing, Linux and shell tooling.
Machine learning & data: TensorFlow and deep learning, graph neural networks, computer vision (OpenCV), NLP and language modeling, local LLMs and AI agents, signal processing, scientific computing (NumPy / SciPy), data visualization and dashboards.
He works with Python, C, VHDL, MATLAB, R, TensorFlow, Django REST, FPGA systems, microcontrollers, Qiskit, LabVIEW, CAD tools, and signal processing pipelines.
He is currently focused on system-level design of photonic Gaussian Boson Sampling platforms, electrical control of quantum-dot emitters, FPGA-based timing and readout systems, and research toward quantum error correction in photonic architectures.
Raman plans to pursue a PhD focused on quantum error correction, photonic quantum computing, and fault-tolerant quantum systems, with the goal of contributing to advanced quantum research and scalable architectures.
His work combines hardware engineering (FPGA and electronics), quantum physics, and machine learning, enabling a systems-level approach to building and scaling quantum technologies.
The site is an interactive portfolio structured as the Orion constellation — the homepage renders a star map where each star is one pillar of Raman's work, with a hidden terminal interface on Betelgeuse. Every page also serves its content as static HTML:
Website: ramanpandey.com
GitHub: github.com/Alpharceus
LinkedIn: linkedin.com/in/alpha-arceus