Xinjue Wang

xjw [at] ieee.org

Google Scholar GitHub

Hi!

I obtained my Ph.D. in Electrical Engineering in 2026 at Aalto University, advised by Professors Esa Ollila and Sergiy A. Vorobyov. I received my M.Sc. in Acoustics from Aalto University in 2022, and my B.Eng. in Information Engineering from Northwestern Polytechnical University, Xi'an, China, in 2020.

My research lies at the intersection of signal processing, optimization, and machine learning. I am broadly interested in:

  • Robust statistical inference in high-dimensional and heavy-tailed regimes.
  • Low-rank and tensor methods for structured signals and modern ML models.
  • Riemannian and manifold optimization, with applications from wireless to large language models.

Publications

Preprints & Under Review

  1. Parallel Robust Covariance Learning with Algorithm Unfolding for Activity Detection

    X. Wang, S.A. Vorobyov, and E. Ollila. Aug. 2026.

  2. Zeroth-Order Riemannian Optimization on Fixed-Rank Manifolds for LLM Fine-Tuning

    X. Wang, X. Wang, Y. Zhang, S.A. Vorobyov, and E. Ollila. May 2026.

  3. A Majorization-Minimization Framework for Activity Detection in Mixed Near-and-Far-Field Random Access

    X. Wang, Z.-Y. Wang, S.A. Vorobyov, E. Ollila, G.A.A. Baduge, and M. Vaezi. Apr. 2026.

Journal Papers

  1. Generalized Nonnegative Structured Kruskal Tensor Regression (arXiv) (code)

    X. Wang, E. Ollila, S.A. Vorobyov, and A. Mian. Signal Processing, vol. 240, 110338, Mar. 2026.

  2. Robust Activity Detection for Massive Random Access (arXiv) (code)

    X. Wang, E. Ollila, and S.A. Vorobyov. IEEE Transactions on Signal Processing, vol. 73, pp. 3513–3527, Aug. 2025.

  3. Tracking the Occluded Indoor Target with Scattered Millimeter Wave Signal

    Y. Xu, X. Wang, J. Kupiainen, J. Sae, J. Boutellier, J. Nurmi, and B. Tan. IEEE Sensors Journal, vol. 24, no. 22, pp. 38102–38112, Nov. 2024.

  4. Graph Convolutional Neural Networks Sensitivity under Probabilistic Error Model (arXiv)

    X. Wang, E. Ollila, and S.A. Vorobyov. IEEE Transactions on Signal and Information Processing over Networks, vol. 10, pp. 788–803, Oct. 2024.

Conference Papers

  1. GeoMix: Descriptor-Free Visual Localization via Global Context and Multi-Detector Training (arXiv)

    Y. Zhang, X. Wang, Z. Wang, E. Rahtu, and J. Kannala. ECCV 2026, Malmö, Sweden, Sept. 8–12, 2026, pp. 1–20.

  2. Covariance-Aware MM-PGD for Mixed Near/Far-Field Activity Detection

    X. Wang, Z.-Y. Wang, S.A. Vorobyov, E. Ollila, G.A.A. Baduge, and M. Vaezi. SPAWC 2026, Athens, Greece, Sept. 7–9, 2026.

  3. Finer Parameter Steps for Low-Rank PEFT: A Controlled Study with CP Tensor Adapters (arXiv)

    X. Wang, X. Wang, Y. Zhang, S.A. Vorobyov, E. Ollila, and Z.-Y. Wang. ICML 2026 Workshop CoLoRAI, Seoul, South Korea, July 10, 2026, pp. 1–8.

  4. Anisotropic Tensor Deconvolution of Hyperspectral Images (arXiv) (code)

    X. Wang, X. Wang, E. Ollila, and S.A. Vorobyov. ICASSP 2026, Barcelona, Spain, May 2026, pp. 706–710.

  5. Robust Activity Detection for Massive Access Using Covariance-Based Matching Pursuit

    X. Wang, E. Ollila, and S.A. Vorobyov. ICASSP 2025, Hyderabad, India, Apr. 2025, pp. 1–5.

  6. Nonnegative Sparse Kruskal Tensor Regression

    X. Wang, E. Ollila, and S.A. Vorobyov. CAMSAP 2023 (invited paper), Herradura, Costa Rica, Dec. 2023, pp. 441–445.

  7. Correlation-Based Graph Smoothness Measures in Graph Signal Processing

    J. Miettinen, S.A. Vorobyov, E. Ollila, and X. Wang. EUSIPCO 2023, Helsinki, Finland, Sept. 2023, pp. 1848–1852.

  8. Graph Neural Network Sensitivity under Probabilistic Error Model

    X. Wang, E. Ollila, and S.A. Vorobyov. EUSIPCO 2022, Belgrade, Serbia, Aug. 2022, pp. 2146–2150.

  9. Distributed Principal Component Analysis Based on Randomized Low-Rank Approximation

    X. Wang and J. Chen. ICSPCC 2020, Macau, China, Aug. 2020, pp. 1–5.

Academic Service

Journal referee: IEEE Trans. Inf. Theory, IEEE Trans. Wireless Commun., IEEE Trans. Mach. Learn. Commun. Netw., Scand. J. Stat.

Conference reviewer: ICASSP 2025, 2026, IJCNN 2025, ITW 2024

Education