Lei Cheng
百人计划研究员
Works on statistical machine learning, statistical signal processing and tensor methods, with applications to ocean big data.
Lei Cheng's lab at Zhejiang works on learning theory & optimization, signal processing & information theory and data management & big data. 35 papers since 2023, 9 at top venues, mostly ICASSP and NeurIPS. Applications close .
At a glance
- papers, 2023–2026
- 9/ year
- at T1 venues
- 26%
- PhD students
- —
- MS students
- —
- alumni listed
- —
Papers by yearfrom DBLP, 2023–2026
- 6 papers2026 · T1 2 · collecting
- 12 papers2025 · T1 4
- 8 papers2024 · T1 1
- 9 papers2023 · T1 2
T1 venuesOtherVenues: ICASSP, NeurIPS, Pattern Recognition, ICC, KDD
Research focuspaper titles that use each topic's words
- Learning theory & optimization7 papers
- Data management & big data3 papers
- Signal processing & information theory1 paper
- statistical signal0 papers
- tensor methods0 papers
Paper list
From DBLP.
20266 papers
- KDD (T1)GRASP: Manifold-Aware Structural Guidance for Generative Atmospheric Super-Resolution (opens in a new tab)
- SAMLearning to Sense: Uncertainty-Aware Active Sensing for Ocean Physical Fields via Bayesian Tensor Completion (opens in a new tab)
- IEEE Trans. Signal Process.Radio Map Estimation via Latent Domain Plug-and-Play Denoising (opens in a new tab)
- IEEE Trans. Signal Process.Rank-Revealing Bayesian Block-Term Tensor Completion With Graph Information (opens in a new tab)
- TPAMI (T1)To Fold or Not to Fold: Graph Regularized Tensor Train for Visual Data Completion (opens in a new tab)
- Trans. Mach. Learn. Res.When VMP Meets CEP: An Algorithmic Equivalence Under Mild Conditions (opens in a new tab)
202512 papers
- ICASSP (T1)Basis Function Learning for Variable-Length and Continuous-Indexed Signals (opens in a new tab)
- IEEE Signal Process. Lett.Domain-Factored Untrained Deep Prior for Spectrum Cartography (opens in a new tab)
- IEEE Trans. Signal Process.FieldFormer: Self-Supervised Reconstruction of Physical Fields via Tensor Attention Prior (opens in a new tab)
- NeurIPS (T1)Functional Complexity-adaptive Temporal Tensor Decomposition (opens in a new tab)
- NeurIPS (T1)Generating Full-field Evolution of Physical Dynamics from Irregular Sparse Observations (opens in a new tab)
- ICASSP (T1)Radio Map Estimation via Latent-Domain Plug-and-Play Denoisers (opens in a new tab)
- Pattern RecognitionRevisiting trace norm minimization for tensor Tucker completion: A direct multilinear rank learning approach (opens in a new tab)
- ICCSensing Radio Maps via Bayesian Tensor Learning (opens in a new tab)
- IEEE Trans. Wirel. Commun.Tensor-Based Channel Estimation for Extremely Large-Scale MIMO-OFDM With Dynamic Metasurface Antennas (opens in a new tab)
- IEEE Wirel. Commun. Lett.Tensor-Based Channel Estimation for Near-Field Millimeter Wave XL-MIMO Systems (opens in a new tab)
- IEEE Trans. Commun.Triple IRS-Aided Communications: Row-Column Sparsity Enhanced Bayesian Tensor Learning for Channel Estimation (opens in a new tab)
- IEEE Trans. Signal Process.When Bayesian Tensor Completion Meets Multioutput Gaussian Processes: Functional Universality and Rank Learning (opens in a new tab)
20248 papers
- IEEE Trans. Signal Process.Activity Detection for Massive Connectivity in Cell-Free Networks With Unknown Large-Scale Fading, Channel Statistics, Noise Variance, and Activity Probability: A Bayesian Approach (opens in a new tab)
- ICASSP (T1)Bayesian Activity Detection for Massive Connectivity in Cell-Free IoT Networks (opens in a new tab)
- IEEE Wirel. Commun. Lett.Channel Estimation for Movable-Antenna MIMO Systems via Tensor Decomposition (opens in a new tab)
- IEEE Trans. Signal Process.Downlink Channel Covariance Matrix Reconstruction for FDD Massive MIMO Systems With Limited Feedback (opens in a new tab)
- IEEE Trans. Wirel. Commun.Enhancing Multi-Stream Beamforming Through CQIs for 5G NR FDD Massive MIMO Communications: A Tuning-Free Scheme (opens in a new tab)
- IEEE Signal Process. Lett.Estimating Channels With Hundreds of Sub-Paths for MU-MIMO Uplink: A Structured High-Rank Tensor Approach (opens in a new tab)
- IEEE Trans. Wirel. Commun.Integrated Sensing and Communication With Massive MIMO: A Unified Tensor Approach for Channel and Target Parameter Estimation (opens in a new tab)
- IEEE Trans. Signal Process.Overcoming Beam Squint in mmWave MIMO Channel Estimation: A Bayesian Multi-Band Sparsity Approach (opens in a new tab)
20239 papers
- Signal Process.Accelerating probabilistic tensor canonical polyadic decomposition with nonnegative factors: An inexact BCD Approach (opens in a new tab)
- Signal Process.Bayesian low-rank matrix completion with dual-graph embedding: Prior analysis and tuning-free inference (opens in a new tab)
- IEEE Trans. Signal Process.Bayesian Tensor Tucker Completion With a Flexible Core (opens in a new tab)
- EUSIPCOEnhanced Tensor Rank Learning in Bayesian PARAFAC2 for Noisy Irregular Tensor Data (opens in a new tab)
- IEEE Signal Process. Lett.Multipath Time-Delay Estimation With Impulsive Noise via Bayesian Compressive Sensing (opens in a new tab)
- ICASSP (T1)Output-Dependent Gaussian Process State-Space Model (opens in a new tab)
- ICASSP (T1)Overcoming Posterior Collapse in Variational Autoencoders Via EM-Type Training (opens in a new tab)
- ICC WorkshopTarget Sensing in Wideband Massive MIMO-ISAC Systems in the Presence of Beam Squint (opens in a new tab)
- Pattern RecognitionTensor train factorization under noisy and incomplete data with automatic rank estimation (opens in a new tab)
Where alumni went
Alumni are not listed on the lab homepage.
Apply to ZhejiangFall 2027
Computer Science PhD (international applicants)
- Round
- Self-funded
- Opens
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- GRE
- See program page
- English
- Per ZJU language requirements
- Fee
- RMB 800
Not yet confirmed for this intake.
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