Resumé

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RESEARCH STATEMENT

Computer Science Ph.D. candidate specializing in generative AI with publications at top-tier conferences including CVPR 2024, ICML 2025 (Oral), and ICCV 2025 (Highlight). My research enhances image and video generative models with greater control and interpretability. I am seeking a Research Scientist internship for Summer & Fall 2026 to contribute to building the next generation of efficient and controllable generative AI tools.

EDUCATION

AUG 2023 - MAY 2027 Virginia Tech, Blacksburg, VA Ph.D. in Computer Science

SEP 2018 - JAN 2022 Boğaziçi University, Istanbul, Turkey M.S. in Computer Engineering

SEP 2012 - JUN 2017 Boğaziçi University, Istanbul, Turkey B.S. in Computer Engineering

PUBLICATIONS

2025 CLoRA: A Contrastive Approach to Compose Multiple LoRA Models ICCV 2025, Highlight Project Page

2025 ConceptAttention: Diffusion Transformers Learn Highly Interpretable Features ICML 2025, Oral Presentation arXiv

2024 MotionFlow: Attention-Driven Motion Transfer in Video Diffusion Models arXiv preprint arXiv:2412.05275 Project Page

2024 MotionShop: Zero-Shot Motion Transfer in Video Diffusion Models with Mixture of Score Guidance arXiv preprint arXiv:2412.05355 Project Page

2024 Conform: Contrast is all you need for high-fidelity text-to-image diffusion models CVPR 2024 Project Page

2024 Conditional Information Gain Trellis Pattern Recognition Letters, 184, 212-218 Publication Link

2022 Unsupervised Routing Strategies for Conditional Deep Neural Networks MSc Thesis. Boğaziçi University

2020 BURST: Software and Simulation Solutions of an Autonomous Vehicle 2020 28th Signal Processing and Communications Applications Conference (SIU) (pp. 1-4)

2018 Privacy-Preserving Intersection Management for Autonomous Vehicles Proceedings of the Tenth International Workshop on Agents in Traffic and Transportation (ATT 2018) (pp. 49-56)

RESEARCH EXPERIENCE

MAY 2025 - AUG 2025 Amazon AGI Foundations Applied Scientist Intern

• Contributed to a research project on next-scale prediction-based autoregressive generative models for high-fidelity image and video generation.
• Developed novel training-free and training-based methods to scale autoregressive models at inference time, enabling higher-quality generation without full retraining.

AUG 2023 - CURRENT Virginia Tech Research Assistant and Lab Lead

• Awarded FAL.ai research fellowship to work on image and video generation models.
• Collaborate with Google to implement research findings in closed-source diffusion-based image generation models, leading to publications at CVPR 2024 and ICCV 2025.
• Awarded Deloitte Research Fellowship to investigate mechanistic interpretability of LLMs; developed a method to discover and control implicit model behaviors by learning steering vectors that modify internal activations.
• Led research on generative models, enhancing diffusion text-to-image, text-to-video, and interpretability methods.

MAY 2024 - AUG 2024 Adobe Research Intern in Video Generative AI

• Engineered a data pipeline to leverage existing image-editing and synthetic datasets for training video models, overcoming the scarcity of labeled video data.
• Enabled a state-of-the-art video model to perform complex semantic edits by successfully adapting image-based training techniques for video generation tasks.

PROFESSIONAL EXPERIENCE

NOV 2022 - AUG 2023 Lyrebird Studio Machine Learning Engineer

• Developed and maintained image generation ML services handling 5 million daily requests.
• Architected CI/CD pipelines (GitHub Actions, AWS CDK) to deploy research models to production, serving thousands of daily requests on GPU instances.
• Led the design and deployment of diffusion-based model training and image generation services, effectively handling thousands of daily requests on GPU-accelerated instances with high performance and stability.
• Pioneered the mobile integration of state-of-the-art diffusion-based image generation and a novel personalization service, driving organic user adoption.

AUG 2021 - NOV 2022 Vispera Machine Learning Engineer

• Spearheaded the automation of deep learning model training using Python and TypeScript, resulting in a tenfold increase in daily model deployments, significantly reducing development time and costs.
• Launched a user-friendly VueJS front-end service empowering researchers to train and deploy new models by providing real-time monitoring of online and offline metrics, enhancing model observability and productivity.
• Worked as a full-stack machine learning engineer, using VueJS in frontend services; Python in machine learning services; TypeScript, NodeJS, Go, PostgreSQL, and MongoDB in backend services.

OCT 2019 - AUG 2021 Vispera Computer Vision Research Engineer

• Led research and development for deep learning image recognition models, utilizing Python, TensorFlow, and OpenCV, to solve challenging problems related to out-of-distribution recognition and hierarchical classification.
• Pioneered the formulation and implementation of a novel zero-shot learning-based image recognition model using PyTorch, which significantly reduced image annotation time by four times. This innovative approach recommends best matches without annotated data, optimizing the model development process.

AUG 2017 - OCT 2019 Idea Technology Solutions Computer Vision Research Engineer

• Developed novel tree-based deep learning architectures, improving performance in object detection.

HONORS & AWARDS

2025 FINALIST, Qualcomm Innovation Fellowship

2020 RUNNER-UP, Kaggle Anadolu Sigorta Datathon Challenge

2019 & 2020 FINALIST, Teknofest Autonomous Vehicle Competition

2019 & 2020 WINNER, Teknofest Autonomous Vehicle Competition - Simulation

2018 WINNER, Mercedes-Benz Hackathon

2017 WINNER, BSH Analytics for Production Excellence Hackathon

WORKSHOPS & OUTREACH

OCT 2025 ICCV 2025 - Personalization in Generative Models Organizer

• Co-organizing an international workshop and competition on personalization in generative AI at ICCV 2025.

JUN 2021 inzva - METU ImageLab AI Labs Joint Program Guide

• Conducted lectures of probability, statistics, and graphical models for the Deep Generative Models course, organized in collaboration with Prof. Gokberk Cinbis from METU.

JUL 2018 - DEC 2020 Boğaziçi University Autonomous Vehicle Team Founder

• Founded and led Boğaziçi University’s first R&D team and lab for autonomous vehicle development.