Gün Kaynar

Gün Kaynar

I am a Ph.D. student in the School of Computer Science at Carnegie Mellon University. I am fortunate to be advised by Carl Kingsford, the Herbert A. Simon Professor of Computer Science.

I am broadly interested in advancing machine learning theory and large language models. Currently, I am working on reasoning distillation and reinforcement learning (RL) training for diffusion language models. In collaboration with Arm, I also work on programmable cloud laboratories. This project addresses the orchestration, scheduling, error handling, and agentic supervision of automated labs, using a modular simulation framework as a foundation for RL policy learning and agentic AI development. Additionally, my research develops methods grounded in biological and physical principles to solve problems in computational biology, including translation regulation, genomics, and clinical decision-making.

Previously, I earned my M.Sc. in Computer Science at Bilkent University, advised by A. Ercument Cicek, where I worked on biologically informed neural networks, NMR modeling, metabolomics, and CNV calling. I earned my B.Sc. at Bogazici University and spent a semester as an exchange student at Universitat de Barcelona.

Outside of research, I enjoy climbing, playing blues on guitar, watching festival movies, and reading.

News

seq2ribo accepted to ISMB 2026 — April 2026
Accepted as a proceedings paper; will be published in Bioinformatics.

Awarded the Randy Bryant Endowed Fellowship Fund — April 2026
School of Computer Science, Carnegie Mellon University.

Two questions accepted to the Humanity's Last Exam dataset — April 2026
Two of my questions on computational biology were accepted into the Humanity's Last Exam dataset.

seq2ribo accepted to RECOMB 2026 — March 2026
seq2ribo has been accepted to be presented at RECOMB 2026.

CMLH 2025 Fellowship Applicant Reviewer — December 2025
I served as a reviewer for fellowship applicants at the Center for Machine Learning and Health, Carnegie Mellon University.

Started the Ph.D. Certificate in Ethics and Artificial Intelligence — August 2025
School of Computer Science and the Dietrich College of Humanities and Social Sciences, Carnegie Mellon University.

Completed the HPC & Data Science Summer Institute — August 2025
Attended the summer institute at the San Diego Supercomputer Center, UC San Diego.

LYCEUM accepted to ISMB 2025 — April 2025
Accepted as a proceedings paper and published in Bioinformatics.

Started my Ph.D. at Carnegie Mellon University — August 2024
Joined the School of Computer Science.

ECOLE featured in Nature Communications Editors' Highlights — July 2024
Selected among the 50 best papers in the Biotechnology and Methods category of Nature Communications.

Graduated from Bilkent University — July 2024
Earned my M.Sc. in Computer Science.

Blog Posts

Coming soon.

Publications

seq2ribo: Structure-aware integration of machine learning and simulation to predict ribosome location profiles from RNA sequences
Gün Kaynar, C Kingsford
bioRxiv, 2026

Augmenting Electronic Health Records for Adverse Event Detection
Gün Kaynar, Z You, RD Boyce, T Yakoh, C Kingsford
medRxiv, 2026

Models Know Their Shortcuts: Deployment-Time Shortcut Mitigation
J Li, S Tang, Gün Kaynar, S Du, C Kingsford
arXiv preprint arXiv:2604.12277, 2026

CodonRL: Multi-Objective Codon Sequence Optimization Using Demonstration-Guided Reinforcement Learning
S Du, Gün Kaynar, J Li, Z You, S Tang, C Kingsford
bioRxiv, 2026

LYCEUM: learning to call copy number variants on low-coverage ancient genomes
MA Yilmaz*, AA Ceylan*, Gün Kaynar*, AE Cicek
Bioinformatics 41 (Supplement_1), 2025
*Equal contribution

ECOLE: Learning to call copy number variants on whole exome sequencing data
B Mandiracioglu, F Ozden, Gün Kaynar, MA Yilmaz, C Alkan, AE Cicek
Nature Communications 15 (1), 2024

PiDeeL: metabolic pathway-informed deep learning model for survival analysis and pathological classification of gliomas
Gün Kaynar, D Cakmakci, C Bund, J Todeschi, IJ Namer, AE Cicek
Bioinformatics 39 (11), 2023

Targeted metabolomics analyses for brain tumor margin assessment during surgery
D Cakmakci*, Gün Kaynar*, C Bund, M Piotto, F Proust, IJ Namer, AE Cicek
Bioinformatics 38 (12), 2022
*Equal contribution

Teaching

02-750: Automation of Scientific Research
Teaching Assistant, Carnegie Mellon University, Spring 2026

02-613: Algorithms and Advanced Data Structures
Teaching Assistant, Carnegie Mellon University, Fall 2025