Melis Ilayda Bal

^{^{mbal [at] tuebingen [dot] mpg [dot] de}}

Hello!

I am a second-year PhD student jointly affiliated with the Max Planck Institute for Intelligent Systems (MPI-IS), in Tübingen, Germany, and the EPFL-EDEE doctoral program.

I conduct my research within the Learning and Dynamical Systems (LDS) group at MPI-IS and LIONS lab at EPFL, under the supervision of Michael Muehlebach and Volkan Cevher. My PhD is supported by the Amazon-MPI Science Hub doctoral fellowship.

I hold an M.Sc. in Operations Research and a B.Sc. in Industrial Engineering, with a minor in Computer Engineering, from Middle East Technical University (METU), Turkey.

My research focuses on optimization for machine learning, specifically aimed at developing techniques that enhance the robustness and training efficiency of machine learning models. Previously, I delved into the intersection of algorithmic decision-making and multi-agent systems, examining the intricate interplay between game theory and stochastic optimization. This exploration spanned various contexts, including reinforcement learning, Bayesian optimization, and protein design.

– If you are interested in doing internship/MSc thesis on the topics mentioned above at the LDS group, I am always open to potential collaborations. Feel free to reach out via email—I’d be happy to discuss possible projects!

news

Jul, 2025	I have received honorary mention for the MPI-IS Outstanding Female Doctoral Student Prize!
May, 2025	New preprint is out: ESLM: Risk-Averse Selective Language Modeling for Efficient Pretraining
Jan, 2025	ICLR 2025: Two papers accepted! I will present our work on Adversarial Training for Defense Against Label Poisoning Attacks and Optimistic Games for Combinatorial Bayesian Optimization with Application to Protein Design, see you in Singapore!
Jan, 2024	Passed my PhD Qualifying Exam! Thanks to committee members Dr. Michael Muehlebach, Prof. Andreas Krause and Dr. Manuel Gomez Rodriguez.
Dec, 2023	Joined Learning and Dynamical Systems Group (LDS) at MPI Intelligent Systems led by Dr. Michael Muehlebach.
Mar, 2023	Joined Learning and Adaptive Systems (LAS) - Interactive Learning Group at ETH Zurich & MPI Intelligent Systems led by Prof. Andreas Krause.
Sep, 2022	Started CS@maxplanck doctoral program at the Max Planck Institute for Software Systems

selected publications

2025

ArXiv

ESLM: Risk-Averse Selective Language Modeling for Efficient Pretraining

Melis Ilayda Bal, Volkan Cevher, and Michael Muehlebach

arXiv:2505.19893 [cs.LG], May 2025

Bib HTML

@article{mib-eslm,
  author = {Bal, Melis Ilayda and Cevher, Volkan and Muehlebach, Michael},
  title = {ESLM: Risk-Averse Selective Language Modeling for Efficient Pretraining},
  journal = {arXiv:2505.19893 [cs.LG]},
  year = {2025},
  month = may,
}

ICLR 2025

Adversarial Training for Defense Against Label Poisoning Attacks

Melis Ilayda Bal, Volkan Cevher, and Michael Muehlebach

In International Conference on Learning Representations, May 2025

Bib HTML

@article{mib-floral,
  author = {Bal, Melis Ilayda and Cevher, Volkan and Muehlebach, Michael},
  title = {Adversarial Training for Defense Against Label Poisoning Attacks},
  journal = {In International Conference on Learning Representations},
  year = {2025},
}

ICLR 2025

Optimistic Games for Combinatorial Bayesian Optimization with Applications to Protein Design

Melis Ilayda Bal, Pier G. Sessa, Mojmir Mutny, and Andreas Krause

In International Conference on Learning Representations, May 2025

Preliminary version presented at NeurIPS 2023 ReALML Workshop, [Best paper award finalist*, Spotlight talk*]

Bib HTML

@article{mib-gameopt,
  author = {Bal, Melis Ilayda and Sessa, Pier G. and Mutny, Mojmir and Krause, Andreas},
  title = {Optimistic Games for Combinatorial Bayesian Optimization with Applications to Protein Design},
  journal = {In International Conference on Learning Representations},
  year = {2025},
  note = {Preliminary version presented at NeurIPS 2023 ReALML Workshop, [Best paper award finalist*, Spotlight talk*]},
}