Serlab

Major applications of our research are navigation, radar, joint radar-communication, smart phones, large-scale data analysis and data mining, information fusion, image processing, and statistical/machine learning.

Welcome

Serlab is the signal and information processing research lab at the Department of Signal Processing and Acoustics at Aalto University. It is part of a larger unit – Signal Processing Laboratory. 

Our research is organised around these topics:

  • Multiantenna/multisensory systems. In this topic, Serlab is closely linked to the labs leaded by professors Visa Koivunen, Esa Ollila, and Risto Wichman.
  • Optimisation algorithms and applications in signal processing.
  • Data science. In this topic, Serlab is closely linked to the labs leaded by profs. Visa Koivunen and Esa Ollila.
  • Radar signal processing. In this topic, Serlab is closely linked to the lab leaded by prof. Visa Koivunen.
  • Wireless signal processing. In this topic, Serlab is closely linked to the labs leaded by profs. Visa Koivunen and Risto Wichman.

The major applications are navigation, radar (automotive radar), joint radar-communication, smart phones, large-scale data analysis and data mining, information fusion, image processing, and statistical/machine learning as well as other applications.

Dear Colleagues

Thanks for visiting! This website provides easy access to our group’s research. Please visit our research page: Dr. Sergiy Vorobyov (aalto.fi) for more details. If you are looking for a specific paper please refer to the list of publications: PUBLICATIONS (aalto.fi) or the Google scholar profile: ‪Sergiy A. Vorobyov - ‪Google Scholar.

Dear Students

Thanks for visiting! If you are currently enrolled in one of the courses taught by Sergiy A. Vorobyov, please use Aalto systems to access the corresponding Mycourse’s website.

If you are thinking of applying for a position in the group we are honored by your consideration. Please look at the list of publications: PUBLICATIONS (aalto.fi) to gain a better idea of what we do and how we do it. If you are still interested after reading, please send email to Sergiy A. Vorobyov: [email protected].

Contact infromation

Group members

Latest publications

Tensorial Hankel Reconstruction for Coherent DOA Estimation with Sensor Failure

Fei Cheng, Hang Zheng, Zhoubin Teng, Zhiguo Shi, Chengwei Zhou 2024 2023 IEEE 23rd International Conference on Communication Technology

AdaBoost-Based Efficient Channel Estimation and Data Detection in One-Bit Massive MIMO

Majdoddin Esfandiari, Sergiy A. Vorobyov, Robert W. Heath 2024 IEEE Transactions on Wireless Communications

Noise Reduction in Automotive Pulse Radar using Signal Subspace and Presumed Ambiguity Function

Luoyan Zhu, Yinsheng Liu, Sergiy A. Vorobyov, Danping He, Ke Guan, Zhangdui Zhong, Liang Chang 2024 IEEE Transactions on Vehicular Technology

A new accelerated gradient-based estimating sequence technique for solving large-scale optimization problems with composite structure

E. Dosti, S. A. Vorobyov, T. Charalambous 2023 2022 IEEE 61st Conference on Decision and Control (CDC)

A new class of composite objective multistep estimating sequence techniques

Endrit Dosti, Sergiy A. Vorobyov, Themistoklis Charalambous 2023 Signal Processing

Twenty-Five Years of Advances in Beamforming: From convex and nonconvex optimization to learning techniques

Ahmet M. Elbir, Kumar Vijay Mishra, Sergiy A. Vorobyov, Robert W. Heath 2023 IEEE Signal Processing Magazine

ADMM-Based Solution for mmWave UL Channel Estimation with One-Bit ADCs via Sparsity Enforcing and Toeplitz Matrix Reconstruction

Majdoddin Esfandiari, Sergiy A. Vorobyov, Robert W. Heath 2023 ICC 2023 - IEEE International Conference on Communications

Efficient approximate online convolutional dictionary learning

Farshad Ghorbani Veshki, Sergiy Vorobyov 2023 IEEE Transactions on Computational Imaging

Efficient Online Convolutional Dictionary Learning Using Approximate Sparse Components

Farshad Ghorbani Veshki, Sergiy A. Vorobyov 2023 Proceedings of the International Conference on Acoustics, Speech, and Signal Processing

Robust Adaptive Beamforming Via Worst-Case SINR Maximization With Nonconvex Uncertainty Sets

Yongwei Huang, Hao Fu, Sergiy A. Vorobyov, Zhi Quan Luo 2023 IEEE Transactions on Signal Processing
More information on our research in the Aalto research portal.
Research portal
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