2025

One paper was accepted to NeurIPS 2025. I authored the article, titled "Error Feedback under (L_0,L_1)-Smoothness", accepted to NeurIPS 2025.
One paper was accepted to ECML 2025. I co-authored the article, titled "Collaborative Value Function Estimation Under Model Mismatch: A Federated Temporal Difference Analysis", accepted to ECML 2025.
One paper was accepted to IEEE-TCNS 2025. I co-authored the article, titled "Parallel Momentum Methods Under Biased Gradient Estimations", accepted to IEEE-TCNS 2025.

2024

I was one of the committee members of the KAUST Research Conference: Rising Stars in AI Symposium 2025.
One paper was accepted to IEEE-IoT 2024. I co-authored the article, titled "Communication-Adaptive Gradient Sparsification for Federated Learning with Error Compensation", accepted to IEEE-IoT 2024.
One paper was accepted to IEEE-Big Data 2024. I co-authored the article, titled "On the convergence of federated learning algorithms without data similarity", accepted to IEEE-Big Data 2024.
One paper was accepted to ECML 2024. I co-authored the articled, titled "Compressed federated reinforcement learning with a generative model", accepted to ECML 2024.
One paper was accepted to IEEE-FLTA 2024. I co-authored the articled, titled "Balancing Privacy and Performance for Private Federated Learning Algorithms", accepted to IEEE-FLTA 2024.
On 1st Feburary 2024, I joined King Abdullah University of Science and Technology (KAUST) as Postdoctoral Fellow in Computer Science.

One paper was accepted to IEEE-TSP 2023. I authored the article, titled "Improved Step-size Schedules for Proximal Noisy Methods", accepted to IEEE-TSP 2023.
One paper was accepted to IFAC 2023. I co-authored the article, titled "Revisiting the Curvature-aided IAG: Improved Theory and Reduced Complexity", accepted to IFAC 2023.
I went to KAUST to participate in the KAUST Research Conference: Rising Stars in AI Symposium 2023, and presented my AAAI article titled "A Flexible Framework for Communication-Efficient Machine Learning"

On 1st August 2022, I joined Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) as Postdoctoral Fellow in Machine Learning.
On 9th March 2022, I defended my PhD thesis titled “First-Order Algorithms for Communication Efficient Distributed Learning ” with Tong Zhang (HKUST) as the opponent, and with Anders Hansson (Linköping University), Martin Jaggi (EPFL) and Clarice Poon (University of Bath) as the evaluation committee.

I presented the work titled "A Flexible Framework for Communication-Efficient Machine Learning" at the Federated Learning One World (FLOW) Seminar chaired by Prof. Peter Richtárik.
One paper was accepted to AAAI 2021. I authored the article, titled "A Flexible Framework for Communication-Efficient Machine Learning", accepted to AAAI 2021.

One paper was accepted to IEEE-TSP 2020. I authored the article, titled "Compressed gradient methods with hessian-aided error compensation", accepted to IEEE-TSP 2020.

On 6th December 2019, I defended my Licentiate thesis titled “First-Order Algorithms for Communication Efficient Distributed Learning ” with Martin Jaggi from EPFL, Lausanne, Switzerland as my thesis opponent.
I received the best student paper award at IEEE-ICASSP 2019 by the article titled "Convergence Bounds for Compressed Gradient Methods with Memory Based Error Compensation".

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