Elisha Siddiqui Matekole, Ph.D., is a patent agent at Young Basile, where she works with clients developing quantum technologies, including quantum optics, quantum error correction, and quantum algorithms. Her technical focus also extends to physics, chemistry, and machine learning. She brings more than ten years of research experience in quantum information science and works with inventors whose technology sits at the edge of what the field can currently build.
Dr. Siddiqui Matekole joins the firm from the Federal Judicial Center, where she served as a Science and Technology Fellow and focused on generative AI and its impact on minors. Previously, at Riverlane, she worked to improve quantum error correction decoder performance by implementing more detailed noise models and developing informed hypergraph decoders. As a research associate at Brookhaven National Laboratory, she developed low-level programming models for optimizing noisy intermediate-scale quantum (NISQ) devices, with a focus on pulse-level control and machine learning assisted quantum error correction.
Dr. Siddiqui Matekole earned her Ph.D. in quantum optics from Louisiana State University in 2020 and holds a B.Sc. in Physics with honors from St. Stephen’s College, University of Delhi. Her research has been published in Physical Review Letters, Nature Communications, and Quantum Science and Technology, and she has contributed to a textbook on quantum error correction.
Her work spans the theoretical and experimental sides of quantum information, allowing her to engage fluently with clients across the quantum computing stack.
Publications
- Elisha S. Matekole, Savannah L. Cuozzo, Nikunjkumar Prajapati, Narayan Bhusal, Hwang Lee, Irina Novikova, Eugeniy E. Mikhailov, Jonathan P. Dowling, and Lior Cohen, “Quantum-Limited Squeezed Light Detection with a Camera,” Physical Review Letters 125, 113602 (2020).
- Lior Cohen, Elisha S. Matekole, Yoad Sher, Daniel Istrati, Hagai S. Eisenberg, and Jonathan P. Dowling, “Thresholded Quantum LIDAR: Exploiting Photon-Number-Resolving Detection,” Physical Review Letters 123, 203601 (2019).
- J. Majaniemi and Elisha S. Matekole, “Reducing quantum error correction overhead using soft information,” Quantum Science and Technology 11, 025024 (2026).
- “Demonstrating real-time and low-latency quantum error correction with superconducting qubits,” Nature Communications (2026).
- Deltakit Quantum Error Correction Textbook.