I received my bachelor’s degree from Fujian Normal University and my Ph.D. from the Research Center for Discrete Mathematics (离散数学研究中心), Fuzhou University, under the supervision of Zheng Peng (彭拯). I subsequently conducted postdoctoral research at the Beijing International Center for Mathematical Research (BICMR，北京国际数学研究中心), Peking University, under the supervision of Zaiwen Wen (文再文).

Academic Appointments & Education

Recent News

• 2026.09NEWOne paper accepted by Mathematics of Operations Research.
• 2026.02One paper accepted by Applied Mathematical Modelling.
• 2026.01One paper accepted by IMA Journal of Numerical Analysis.
• 2025.12One paper accepted by Applied Numerical Mathematics.
• 2025.09One paper accepted by SIAM Review.
• 2025.09Two papers accepted by NeurIPS 2025.
• 2025.09One paper accepted by Journal of Optimization Theory and Applications.
• 2025.09One paper accepted by Numerische Mathematik.

Preprints

• A Single-loop Stochastic Riemannian ADMM for Nonsmooth Optimization
  Jiachen Jin, Kangkang Deng, Hongxia Wang, 2025.
• Single-loop $\mathcal{O}(\epsilon^{-3})$ stochastic smoothing algorithms for nonsmooth Riemannian optimization
  Kangkang Deng, Zheng Peng, Weihe Wu, 2025.
• Stochastic Momentum ADMM for nonconvex and nonsmooth optimization with application to PnP algorithm
  Kangkang Deng, Shuchang Zhang, Boyu Wang, Jiachen Jin, Juan Zhou, Hongxia Wang, 2025.
• Improving the communication in decentralized manifold optimization through single-step consensus and compression
  Jiang Hu, Kangkang Deng, 2024.

Publications

Selected links to papers and code are provided below. Publication years follow the journal/conference year (rather than the acceptance year) whenever a final publication year is available.

Forthcoming

• An efficient primal dual semismooth Newton method for semidefinite programming
  Zhanwang Deng, Jiang Hu, Kangkang Deng, Zaiwen Wen. Mathematics of Operations Research, accepted / forthcoming.

2026

• SAM-DNN: Bilevel Convergent Sequential Averaging Methods with Denoising Neural Network
  Shuchang Zhang, Kangkang Deng, Hui Zhang, Hongxia Wang. Applied Mathematical Modelling, 2026.
• A cut-and-project perspective for linearized Bregman iterations
  Yu-Hong Dai, Kangkang Deng, Hui Zhang. IMA Journal of Numerical Analysis, 2026.
• The Augmented Lagrangian Methods: Overview and Recent Advances
  Kangkang Deng, Rui Wang, Zhenyuan Zhu, Junyu Zhang, Zaiwen Wen. SIAM Review, 2026.
• Stochastic ADMM with batch size adaptation for nonconvex nonsmooth optimization
  Jiachen Jin, Kangkang Deng, Boyu Wang, Hongxia Wang. Applied Numerical Mathematics, 2026.
• A Novel Riemannian Conjugate Gradient Method with Iteration Complexity Guarantees
  Juan Zhou, Kangkang Deng, Hongxia Wang, Zheng Peng. Journal of Applied Analysis and Computation, 2026.
• Anderson acceleration of derivative-free projection methods for constrained monotone nonlinear equations
  Jiachen Jin, Hongxia Wang, Kangkang Deng. Journal of Optimization Theory and Applications, 2026.

2025

• Rethinking Gradient Step Denoiser: Towards Truly Pseudo-Contractive Operator
  Shuchang Zhang, Yaoyun Zeng, Kangkang Deng, Hongxia Wang. NeurIPS 2025, 2025.
• Adaptive Riemannian ADMM for Nonsmooth Optimization: Optimal Complexity without Smoothing
  Kangkang Deng, Jiachen Jin, Jiang Hu, Hongxia Wang. NeurIPS 2025, 2025. Code Code
• Decentralized projected Riemannian gradient method for smooth optimization on compact submanifolds embedded in the Euclidean space
  Kangkang Deng, Jiang Hu. Numerische Mathematik, 2025.
• Oracle complexities of augmented Lagrangian methods for nonsmooth manifold optimization
  Kangkang Deng, Jiang Hu, Jiayuan Wu, Zaiwen Wen. Mathematics of Operations Research, 2025. Code Code
• Inexact Riemannian Gradient Descent Method for Nonconvex Optimization with Strong Convergence
  Juan Zhou, Kangkang Deng, Hongxia Wang, Zheng Peng. *Journal of Scientific Computing, 2025.
• Decentralized Riemannian Natural Gradient Methods with Kronecker Product Approximations
  Jiang Hu, Kangkang Deng, Quanzheng Li. *Journal of the Operations Research Society of China, 2025.
• Decentralized Projected Riemannian Stochastic Recursive Momentum Method for Nonconvex Optimization
  Kangkang Deng, Jiang Hu. AAAI 2025, 2025.
• LDPP-MIG Detectors in Sample-Starved Nonhomogeneous Clutter
  Xiaoqiang Hua, Chuanfu Xu, Zhenghua Wang, Weijian Liu, Kangkang Deng, Alfonso Farina, Danilo Orlando. IEEE Transactions on Aerospace and Electronic Systems, 2025.
• An augmented lagrangian primal-dual semismooth newton method for multi-block composite optimization
  Zhanwang Deng, Kangkang Deng, Jiang Hu, Zaiwen Wen. Journal of Scientific Computing, 2025. Code Code
• Achieving local consensus over compact submanifolds
  Jiang Hu, Jiaojiao Zhang, Kangkang Deng. *IEEE Transactions on Automatic Control, 2025.
• Decentralized Douglas-Rachford splitting methods for smooth optimization over compact submanifolds
  Kangkang Deng, Jiang Hu, Hongxia Wang. Journal of Computational Mathematics, 2025.

2024

• New vector transport operators extending a Riemannian CG algorithm to generalized Stiefel manifold with low-rank applications
  Xuejie Wang, Kangkang Deng, Zheng Peng, Chengcheng Yan. *Journal of Computational and Applied Mathematics, 2024.
• Trace lasso regularization for adaptive sparse canonical correlation analysis via manifold optimization approach
  Kangkang Deng, Zheng Peng. Journal of the Operations Research Society of China, 2024. Code Code
• A projected semismooth Newton method for a class of nonconvex composite programs with strong prox-regularity
  Jiang Hu, Kangkang Deng, Jiayuan Wu, Quanzheng Li. *Journal of Machine Learning Research, 2024. Code Code
• High-performance placement engine for modern large-scale FPGAs with heterogeneity and clock constraints
  Ziran Zhu, Yangjie Mei, Kangkang Deng, Huan He, Jianli Chen, Jun Yang, Yao-Wen Chang. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2024.

2023

• Riemannian Smoothing Gradient Type Algorithms for Nonsmooth Optimization Problem on Compact Riemannian Submanifold Embedded in Euclidean Space
  Zheng Peng, Weihe Wu, Jiang Hu, Kangkang Deng. *Applied Mathematics & Optimization, 2023.
• An entropy-regularized ADMM for binary quadratic programming
  Haoming Liu, Kangkang Deng, Haoyang Liu, Zaiwen Wen. Journal of Global Optimization, 2023.
• A decomposition augmented Lagrangian method for low-rank semidefinite programming
  Yifei Wang, Kangkang Deng, Haoyang Liu, Zaiwen Wen. SIAM Journal on Optimization, 2023. Code Code
• A manifold inexact augmented Lagrangian method for nonsmooth optimization on Riemannian submanifolds in Euclidean space
  Kangkang Deng, Zheng Peng. IMA Journal of Numerical Analysis, 2023. Code Code

2020

• A Discriminative Projection and Representation-Based Classification Framework for Face Recognition
  Kangkang Deng, Zheng Peng, Wenxing Zhu. SIAM Journal on Imaging Sciences, 2020. Code Code

Honors & Awards

• 2025.12 · 湖南省计算数学应用软件学会青年优秀论文一等奖
• 2025.11 · 中国运筹学会数学与智能分会青年理事
• 2025.08 · 湖南省芙蓉计划青年托举
• 2025.04 · 湖南省运筹学会理事

Invited Talks

• 2025.08 · Iteration Complexity of Riemannian ADMM, The First Youth Scholars Conference of the Operations Research Society, Taiyuan.
• 2025.05 · Nonsmooth Optimization on Riemannian Manifold, Annual Meeting of the Mathematical Programming Society of the Operations Research Society, Shanghai.