Baris Askin

Pittsburgh, PA, USA

baskin [at] andrew.cmu.edu

Hi, I am Baris 👋

I am a fourth-year PhD candidate in the Department of Electrical and Computer Engineering at Carnegie Mellon University. I am advised by Dr. Gauri Joshi and Dr. Carlee Joe-Wong. My research interests broadly lie in language models, federated/distributed learning, and their intersection.

I graduated as the valedictorian from my undergraduate studies in the Department of Electrical and Electronics Engineering at Bilkent University, where I was fortunate to work with Dr. Tolga Cukur on deep learning applications in medical imaging.

news

Jan 2026	Our paper Internal Planning in Language Models: Characterizing Horizon and Branch Awareness was accepted to ICLR 2026! [paper]
Sep 2025	Ravan: Multi-Head Low-Rank Adaptation for Federated Fine-Tuning was accepted to NeurIPS 2025! [paper]
Jun 2025	Started a research internship at NVIDIA (Herndon, VA) for Summer 2025, working on asynchronous federated learning algorithms with knowledge distillation.
Jan 2025	Federated Communication-Efficient Multi-Objective Optimization was accepted to AISTATS 2025! [paper] [code]
Apr 2024	FedAST: Federated Asynchronous Simultaneous Training was accepted to UAI 2024! [paper] [code]

selected publications

ICLR

Internal Planning in Language Models: Characterizing Horizon and Branch Awareness

M. Ustaomeroglu^*, B. Askin^*, G. Joshi, C. Joe-Wong, and G. Qu

In International Conference on Learning Representations (ICLR), 2026

arXiv Bib

@inproceedings{ustaomeroglu2026internal,
  title = {Internal Planning in Language Models: Characterizing Horizon and Branch Awareness},
  author = {Ustaomeroglu, M. and Askin, B. and Joshi, G. and Joe-Wong, C. and Qu, G.},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://arxiv.org/abs/2509.25260},
}

Federate the Router: Learning LM Routers with Sparse and Decentralized Evaluations

B. Askin^*, S. Patel^*, A. Nayak^*, A. Vigano, J. Woo, G. Joshi, and C. Joe-Wong

2026, Preprint, under review

arXiv Bib

@misc{askin2026federate,
  title = {Federate the Router: Learning LM Routers with Sparse and Decentralized Evaluations},
  author = {Askin, B. and Patel, S. and Nayak, A. and Vigano, A. and Woo, J. and Joshi, G. and Joe-Wong, C.},
  year = {2026},
  note = {Preprint, under review},
  url = {https://www.arxiv.org/abs/2601.22318},
}

Reviving Stale Updates: Data-Free Knowledge Distillation for Asynchronous Federated Learning

B. Askin, H. R. Roth, Z. Sun, C. Joe-Wong, G. Joshi, and Z. Xu

2026, Preprint, under review

arXiv Bib

@misc{askin2026reviving,
  title = {Reviving Stale Updates: Data-Free Knowledge Distillation for Asynchronous Federated Learning},
  author = {Askin, B. and Roth, H. R. and Sun, Z. and Joe-Wong, C. and Joshi, G. and Xu, Z.},
  year = {2026},
  note = {Preprint, under review},
  url = {https://arxiv.org/abs/2511.00655},
}

PubSwap: Public-Data Off-Policy Coordination for Federated RLVR

A. Nayak^*, B. Askin^*, M. Ustaomeroglu, C. Joe-Wong, and G. Joshi

2026, Preprint, under review

arXiv Bib

@misc{nayak2026pubswap,
  title = {PubSwap: Public-Data Off-Policy Coordination for Federated RLVR},
  author = {Nayak, A. and Askin, B. and Ustaomeroglu, M. and Joe-Wong, C. and Joshi, G.},
  year = {2026},
  note = {Preprint, under review},
  url = {https://arxiv.org/abs/2604.12160},
}

AISTATS

Federated Communication-Efficient Multi-Objective Optimization

B. Askin, P. Sharma, G. Joshi, and C. Joe-Wong

In Proceedings of the 28th International Conference on Artificial Intelligence and Statistics (AISTATS), May 2025

arXiv Bib Code Poster

@inproceedings{askin2025fedcmoo,
  title = {Federated Communication-Efficient Multi-Objective Optimization},
  author = {Askin, B. and Sharma, P. and Joshi, G. and Joe-Wong, C.},
  booktitle = {Proceedings of the 28th International Conference on Artificial Intelligence and Statistics (AISTATS)},
  pages = {4627--4635},
  year = {2025},
  volume = {258},
  series = {Proceedings of Machine Learning Research},
  month = may,
  publisher = {PMLR},
  url = {https://proceedings.mlr.press/v258/askin25a.html},
}

UAI

FedAST: Federated Asynchronous Simultaneous Training

B. Askin, P. Sharma, C. Joe-Wong, and G. Joshi

In Proceedings of the 40th Conference on Uncertainty in Artificial Intelligence (UAI), Jul 2024

arXiv Bib Code Poster

@inproceedings{askin2024fedast,
  title = {{FedAST}: Federated Asynchronous Simultaneous Training},
  author = {Askin, B. and Sharma, P. and Joe-Wong, C. and Joshi, G.},
  booktitle = {Proceedings of the 40th Conference on Uncertainty in Artificial Intelligence (UAI)},
  pages = {138--172},
  year = {2024},
  volume = {244},
  series = {Proceedings of Machine Learning Research},
  month = jul,
  publisher = {PMLR},
  url = {https://proceedings.mlr.press/v244/askin24a.html},
}