Biography: Sarit Khirirat is a postdoctoral fellow, advised by Professor Peter Richtárik, at King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia. Before joining KAUST, he was a postdoctoral fellow at Mohamed bin Zayed University of Artificial Intelligence (MBZUAI), Abu Dhabi, United Arab Emirates, in 2022. 

He received the Bachelor's degree in Electrical Engineering from Chulalongkorn University, Bangkok, Thailand, in 2013; the Master's degree in Systems, Control and Robotics from KTH Royal Institute of Technology, Stockholm, Sweden, in 2017; and the PhD in Electrical Engineering and Computer Science from the same institution under the supervision of Professor Mikael Johansson in 2022. His PhD program was funded by the Wallenberg AI, Autonomous Systems and Software program. He has received the best student paper award at the IEEE International Conference on Acoustics, Speech & Signal Processing (ICASSP) in 2018.

Research interests: Distributed optimization, machine learning, federated learning, and reinforcement learning. 

Accomplishments

• AI Rising Star (ranked top 20%), KAUST AI Initiative by Prof. Jürgen Schmidhuber, 2023.

• Best Student Paper Award, IEEE International Conference on Acoustics, Speech and Signal Processing, 2019.

• PhD Student, the Wallenberg AI, Autonomous Systems and Software program, 2017. 

• First-Class Honours, B.Sc. in Electrical Engineering, Chulalongkorn University, 2013. 

Selected Publications 

1. Khirirat, S., Sadiev, A., Riabinin, A., Gorbunov, E., & Richtárik, P. (2025).
   Error Feedback under (L_0,L_1)-Smoothness.
   In Advances in Neural Information Processing Systems (NeurIPS). (NeurIPS 2025)  

2. Vaishnav, S., Khirirat, S., & Magnússon, S. (2024).
   Communication-Adaptive Gradient Sparsification for Federated Learning with Error Compensation.
   IEEE Internet of Things Journal. (IEEE-IoT 2024) 

3. Khirirat, S., Wang, X., Magnusson, S., & Johansson, M. (2023).
   Improved step-size schedules for proximal noisy gradient methods.
   IEEE Transactions on Signal Processing, 71, 189-201. (IEEE-TSP 2023)  

4. Khirirat, S., Magnússon, S., Aytekin, A., & Johansson, M. (2021).
   A flexible framework for communication-efficient machine learning.
   In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 35, No. 9, pp. 8101-8109).  (AAAI 2021)

5. Khirirat, S., Magnusson, S., & Johansson, M. (2020).
   Compressed gradient methods with hessian-aided error compensation.
   IEEE Transactions on Signal Processing, 69, 998-1011. (IEEE-TSP 2020)  

6. Alistarh, D., Hoefler, T., Johansson, M., Konstantinov, N., Khirirat, S., & Renggli, C. (2018).
   The convergence of sparsified gradient methods.
   In Advances in Neural Information Processing Systems, 31. (NeurIPS 2018)