Anders Buvarp

About

My research lies at the intersection of statistical signal processing, information theory, robust inference, machine learning, and physically structured systems. I develop methods that exploit geometric, algebraic, and statistical structure to improve estimation, learning, coding, and decoding under noise, model uncertainty, and non-nominal operating conditions.

My current research focuses on quantum information and quantum technologies, including quantum-state geometry and distinguishability, geometric quantum error correction, robust quantum estimation and control, and structure-aware learning and decoding. I also work on wireless communications, complex- and quaternion-valued signal processing and neural networks, federated learning, and reconfigurable intelligent surfaces (RIS).

Research

My research spans statistical signal processing, information theory, robust inference, machine learning, and physically structured systems. Current topics include quantum information and quantum error correction, robust quantum estimation and control, quantum-state geometry and distinguishability, complex- and quaternion-valued signal processing and neural networks, federated learning, wireless communications, and reconfigurable intelligent surfaces.

Stefan Werner

CORRECT — Continuously Operating Geometric Quantum Error Correction for Bosonic Codes

CORRECT develops geometric and robust methods for continuous quantum error correction in bosonic systems, combining structured quantum-state representations, real-time inference, and geometry-aware decoding under realistic noise and hardware constraints.

QUARTZ

QUARTZ develops robust quaternion-valued receivers for polarization-diverse quantum communications, including dual-polarization CV-QKD, with emphasis on structured signal representations, blind equalization, robustness, and learning-based detection.

KVIST

KVIST develops assurance methods for autonomous systems, with emphasis on robust estimation, validation, uncertainty, and trustworthy decision support under model mismatch, environmental variation, and other non-nominal conditions.

BERG

BERG studies structured quantum-state manifolds, intrinsic quantum geometry, and local versus global distinguishability, with robust trajectory design and manifold-aware decoding under realistic quantum noise and open-system dynamics.

TORQ

TORQ develops robust geometric methods for quantum control, combining Hamiltonian identification, noise-aware estimation, and constrained pulse optimization to improve calibration and gate performance under model uncertainty and non-Gaussian disturbances.

VISTA

VISTA develops variational and structure-aware inference methods for robust signal estimation, combining latent-variable models, uncertainty quantification, and divergence-based diagnostics under noise, model mismatch, and non-nominal conditions.

PRIOR

PRIOR studies physics-informed variational estimation for quantum SATCOM, focusing on prior mismatch in polarization channels and how Rician, Gaussian, and other latent priors affect robust channel estimation under fading and polarization mixing.

PRISM

PRISM develops identifiable blind and semi-blind channel inference for RIS-assisted TDD Massive MIMO using structured phase probing, latent-data estimation, and geometry-aware models under partial observation and model uncertainty.

DISAC

DISAC studies disintegrated sensing and communications in adversarial electromagnetic environments, including Eisenstein-lattice repeater deployment, resilient Massive MIMO, interference-aware inference, and robust operation under hostile sensing.

Publications

Toward robust real-time bosonic decoding with geometry-aware neural networks

Geometry-aware neural decoding for bosonic quantum error correction, combining Riemannian structure, robust real-time inference, and structure-aware machine learning under realistic quantum noise and hardware constraints.

Constant Curvature Curve Tube Codes for Low-Latency Analog Error Correction

Introduces constant-curvature curve tube codes for low-latency analog error correction, using geometric signal representations to balance local sensitivity, global separation, and robustness under channel noise.

PEER-REVIEWED PUBLICATIONS

Journal articles

A. M. Buvarp, L. Mili, and J. Fishbone, “Robust Media-Based Modulation with an Eisenstein Constellation Generated by a Reconfigurable Intelligent Surface with Blind Equalization and Complex-Valued Neural Receivers,” IEEE Transactions on Wireless Communications, vol. 24, no. 5, pp. 3794–3804, 2025.
A. M. Buvarp, L. Mili, K. V. Mishra, and A. Zaghloul, “Polarization-Space Modulation with Reconfigurable Intelligent Surfaces, Robust Estimation, and Quaternion Neural Networks,” IEEE Transactions on Antennas and Propagation, vol. 73, no. 6, pp. 4038–4049, 2025.
A. M. Buvarp, L. Mili, and A. Zaghloul, “Robust Constant Curvature Curve Communications with Complex and Quaternion Neural Networks,” IEEE Transactions on Communications, vol. 72, no. 12, pp. 7787–7797, 2024.
A. M. Buvarp, L. Mili, K. V. Mishra, and A. Zaghloul, “Constant Curvature Curve Tube Codes for Low-Latency Analog Error Correction,” IEEE Transactions on Information Theory, vol. 69, no. 12, pp. 7738–7754, 2023.
S. E. Widmalm and A. M. Buvarp, “The need for improved standards of commonly used equipment for recording of EMG and TMJ Sounds in dental clinics,” Stomatology Edu Journal, vol. 10, no. 1–4, pp. 13–18, 2023.
Y. Dong, B. Li, J. Hu, S. E. Widmalm, T. Zhang, M. Lin, A. Buvarp, and D. Zhou, “Kurtosis, a new variable with possible diagnostic value in analysis of jaw muscle surface EMG,” Journal of Oral Rehabilitation, vol. 49, no. 2, pp. 170–176, 2022.
J. Hu, Y. Dong, S. E. Widmalm, A. Buvarp, T. Zhang, B. Li, M. Lin, and D. Zhou, “Is SEMG recorded ‘hyperactivity’ during mandibular rest a sign of dysfunctional jaw muscle activity and temporomandibular disorders (TMD)?,” Journal of Oral Rehabilitation, vol. 47, no. 8, pp. 930–938, 2020.

Conference papers

A. Buvarp and S. Werner, “Toward robust real-time bosonic decoding with geometry-aware neural networks,” IEEE International Conference on Quantum Computing and Engineering (QCE), Toronto, Canada, 2026.
D. K. Redie, R. Arablouei, A. Buvarp, and S. Werner, “Enhancing efficiency and privacy in federated learning via partial model sharing,” Asilomar Conference on Signals, Systems, and Computers, 2025.
A. M. Buvarp, L. Mili, K. V. Mishra, and A. Zaghloul, “Quaternion-Neural-Networks-Based Decoder for RIS-Aided Polarization-Space Modulation,” IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, pp. 985–986, 2023.
A. M. Buvarp, D. J. Jakubisin, W. C. Headley, and J. H. Reed, “Probability-Reduction of Geolocation using Reconfigurable Intelligent Surface Reflections,” IEEE Wireless Communications and Networking Conference, Glasgow, United Kingdom, pp. 1–6, 2023.

MANUSCRIPTS SUBMITTED AND IN PREPARATION

A. M. Buvarp and S. Werner, “Adversarial Sensing and Acquisition Denial with Eisenstein-Lattice Repeater Deployment,” manuscript in preparation for IEEE Transactions on Aerospace and Electronic Systems, Special Issue, 2026.
A. M. Buvarp and S. Werner, “Identifiable Blind Channel Inference for RIS-Assisted TDD Massive MIMO with DFT-Structured Phase Probing,” manuscript in preparation for IEEE Transactions on Wireless Communications, 2026.
A. M. Buvarp and S. Werner, “Physical Prior Mismatch in Variational Dual-Polarization Quantum SATCOM Channel Estimation,” manuscript in preparation for IEEE Transactions on Communications, 2026.
A. M. Buvarp and S. Werner, “Variational Blind Equalization for Dual-Polarization Free-Space Quantum Communications,” manuscript submitted to IEEE Transactions on Signal Processing, 2026.
A. M. Buvarp and S. Werner, “Robust Quaternion Neural Receivers for Dual-Polarization Free-Space Quantum Communications,” manuscript submitted to IEEE Transactions on Communications, 2026.
A. M. Buvarp and S. Werner, “Robust Fusion with Source Trust Scoring under Sparse Corruption and Coherent Subnetwork Shift,” manuscript submitted to IEEE Transactions on Signal and Information Processing over Networks, 2026.
A. M. Buvarp and S. Werner, “Low-Latency Joint Source-Channel Coding with Multiple Constant Curvature Curves,” manuscript submitted to IEEE Transactions on Information Theory, 2026.
A. M. Buvarp and S. Werner, “Robust Complex-Valued Federated Learning for Secure Wireless Communications,” manuscript submitted to IEEE Internet of Things Journal, 2026.
A. M. Buvarp, D. Jenkins, W. C. Headley, J. D. Gaeddert, and collaborators, “A Hierarchical RF Machine Learning Architecture for Spectrum Situational Awareness in Congested Radar and Communications Environments,” manuscript in preparation for IEEE Transactions on Aerospace and Electronic Systems, 2026.

Teaching

Teaching experience includes graduate-level instruction in robust estimation and statistical signal processing. At Linköping University, I taught the PhD course Introduction to Robust Estimation Theory (6 ECTS, Fall 2024).

Supervision

Evaluation of master's theses, and participation in thesis grading and examination.

Outreach

Communications with Quaternions

Animation for the IEEE Transactions on Antennas and Propagation article “Polarization-Space Modulation with Reconfigurable Intelligent Surfaces, Robust Estimation, and Quaternion Neural Networks,” featured on the IEEE TAP homepage in Fall 2025.

Introduction to Reconfigurable Intelligent Surfaces

Invited IEEE Pikes Peak Section presentation: “Introduction to Reconfigurable Intelligent Surfaces” (2023), covering RIS fundamentals, applications, and emerging research directions in wireless communications.

Språkvelger

Anders Buvarp

Anders Buvarp

About

Competencies

Research

CORRECT — Continuously Operating Geometric Quantum Error Correction for Bosonic Codes

QUARTZ

KVIST

BERG

TORQ

VISTA

PRIOR

PRISM

DISAC

Publications

Toward robust real-time bosonic decoding with geometry-aware neural networks

Constant Curvature Curve Tube Codes for Low-Latency Analog Error Correction

Teaching

Supervision

Outreach

Communications with Quaternions

Introduction to Reconfigurable Intelligent Surfaces