Last updated April 2025. For a PDF version, click here.

Education

• Ph.D in Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA, USA, 2020 - present
• M.Sc. in Applied Mathematics, Faculty of Sciences, University of Novi Sad, Novi Sad, Serbia, 2018
• B.Sc. in Applied Mathematics, Faculty of Sciences, University of Novi Sad, Novi Sad, Serbia, 2016

Experience

• Aug 2020 - present: Graduate Research Assistant at Carnegie Mellon University, Pittsburgh, PA, USA
  • Advisor: Prof. Soummya Kar
• Sep 2019 - Dec 2019: Visiting Researcher at University of Pennsylvania, Philadelphia, PA, USA
  • Advisor: Prof. Alejandro Ribeiro
• Nov 2018 - Jun 2020: Junior Researcher at Faculty of Sciences, University of Novi Sad, Novi Sad, Serbia
  • Advisor: Prof. Dušan Jakovetić

• July 2018 - Oct 2018: Junior Researcher at BioSense Institute, University of Novi Sad, Novi Sad, Serbia

• Feb 2018 - July 2018: Visiting Researcher at Faculty of Computer and Information Science, University of Ljubljana, Ljubljana, Slovenia
  • Advisor: Prof. Blaž Zupan

Publications (in chronological order, * = equal contribution)

High-probability Convergence Bounds for Online Nonlinear Stochastic Gradient Descent under Heavy-tailed Noise

Armacki, A., Yu, S., Sharma, P., Joshi, G., Bajović, D., Jakovetić, D., & Kar, S. (2025). High-probability Convergence Bounds for Online Nonlinear Stochastic Gradient Descent under Heavy-tailed Noise. To appear in 28th International Conference on Artificial Intelligence and Statistics.

A Unified Framework for Gradient-based Clustering of Distributed Data

Armacki, A., Bajović, D., Jakovetić, D., & Kar, S. (2025). Distributed Center-Based Clustering: A Unified Framework. In IEEE Transactions on Signal Processing, vol. 73, pp. 903-918, doi: 10.1109/TSP.2025.3531292.

Distributed Gradient Clustering: Convergence and the Effect of Initialization

Armacki, A.*, Sharma, H.*, Bajović, D., Jakovetić, D., Chakraborty, M., & Kar, S. (2024). Distributed Gradient Clustering: Convergence and the Effect of Initialization. In 58th Asilomar Conference on Signals, Systems, and Computers.

Large Deviations and Improved Mean-squared Error Rates of Nonlinear SGD: Heavy-tailed Noise and Power of Symmetry

Armacki, A.*, Yu, S.*, Bajović, D., Jakovetić, D., & Kar, S. (2024). Large Deviations and Improved Mean-squared Error Rates of Nonlinear SGD: Heavy-tailed Noise and Power of Symmetry. In arXiv preprint, arxiv:2410.15637

A One-shot Framework for Distributed Clustered Learning in Heterogeneous Environments

Armacki, A., Bajović, D., Jakovetić, D., & Kar, S. (2024). A One-Shot Framework for Distributed Clustered Learning in Heterogeneous Environments. In IEEE Transactions on Signal Processing, vol. 72, pp. 636-651, doi: 10.1109/TSP.2023.3343561.

Communication Efficient Model-aware Federated Learning for Visual Crowd Counting and Density Estimation in Smart Cities

Armacki, A., Milošević, N., Bajović, D., Kar, S., Jakovetić, D., Bakhtiarnia, A., Esterle, L., Muscat, A., & Festi, T. (2023). Communication Efficient Model-aware Federated Learning for Visual Crowd Counting and Density Estimation in Smart Cities. In 31st European Signal Processing Conference, Helsinki, Finland.

Personalized Federated Learning via Convex Clustering

Armacki, A., Bajović, D., Jakovetić, D., & Kar, S. (2022). Personalized Federated Learning via Convex Clustering. In IEEE International Smart Cities Conference (ISC2), Pafos, Cyprus, pp. 1-7, doi: 10.1109/ISC255366.2022.9921863.

Gradient Based Clustering

Armacki, A., Bajović, D., Jakovetić, D., & Kar, S. (2022). Gradient Based Clustering. In proceedings of the 39th International Conference on Machine Learning, PMLR, 162:929-947.

Distributed Trust-region Method with First Order Models

Armacki, A., Jakovetić, D., Krejić, N., & Jerinkić, N. K. (2019). Distributed Trust-Region Method With First Order Models. In IEEE EUROCON 18th International Conference on Smart Technologies, Novi Sad, Serbia, pp. 1-6, doi: 10.1109/EUROCON.2019.8861739.

Awards

• IBM PhD Fellowship - Finalist. One of three nominees by the Electrical and Computer Engineering Department, Carnegie Mellon University, 2023
• Dean’s Fellowship - Electrical and Computer Engineering Department, Carnegie Mellon University, 2020
• Annual Award of the Mathematical Institute of the Serbian Academy of Sciences and Arts for M.Sc. Students in the Field of Computing - Finalist, 2019

Academic Service

• Conference reviewer: AISTATS, IEEE ISIT.

• Journal reviewer: IEEE TSP.

• Student supervision: Himkant Sharma, summer internship 2024. Work resulted in publication at Asilomar Conference on Signals, Systems, and Computers.

• Teaching: Linear Systems, Fall 2022 and 2023.

• Student council for faculty hiring, Electrical and Computer Enigneering Deparment, Carnegie Mellon University, 2023.