Computer Science · Virginia Tech

Pinar Yanardag

Assistant Professor of Computer Science
Generative Models · Image & Video Synthesis · Interpretability

Building generative AI that's controllable, expressive, and accessible — from steering the latent space of diffusion models to long-horizon video generation. I direct GEMLAB at Virginia Tech.

Pinar Yanardag, Ph.D. Pinar Yanardag with her children in Harry Potter costumes on Halloween Me & my kids on Halloween
01 — About

Generative models can imagine almost anything: we make them controllable.

Modern generative models can synthesize nearly any image or video — yet steering them precisely, efficiently, and faithfully is still hard. Making these systems controllable, interpretable, and accessible is the key focus of my research.

I am a tenure-track Assistant Professor at Virginia Tech, in the Department of Computer Science, where I lead 💎 GEMLAB. I am also a member of the Sanghani Center for AI and Data Analytics.

Prior to joining Virginia Tech, I was a postdoctoral researcher at MIT. I received my Ph.D. in Computer Science from Purdue University, where I was advised by S.V.N. Vishwanathan. I completed my M.S. under the supervision of Ethem Alpaydın at Boğaziçi.

Beyond academia, I was CEO of AI Fiction, a creative design studio specializing in AI, and I co-founded GLITCH — the world's first generative-AI clothing line. At MIT, I launched the How to Generate (Almost) Anything project and Nightmare Machine.

In a past life — long before I worked on making models behave — I was a security researcher who broke software on purpose, and a core developer of a GNU/Linux distribution.

02 — Research Program

We leverage internal priors in diffusion and generative models to unlock hidden capabilities.

01

Discovering and Leveraging Latent Capabilities for Efficient Control

My research uncovers and exploits the internal representations of generative models to enable efficient, training-free control of image and video synthesis.

02

Integrating Cross-Modal Capabilities for Advanced Generation Tasks

My research bridges vision and language, unifying the reasoning of VLMs and LLMs with the generative priors of visual models to enable tasks beyond either modality alone.

03

Personalized, Human-Aligned, and Democratized Generative AI

My research moves beyond one-size-fits-all generative AI with methods for personalized content generation, and democratizes generative AI for creators.

Check out our work

Find papers, code, datasets, demos, and more on our website.

03 — News & Notes

What's new

Recent papers, awards, and recognition from the lab.

AwardMay 2026

Awarded a National Science Foundation CAREER Award

Honored to receive the NSF's CAREER award — its most prestigious recognition for early-career faculty — supporting our research and education in controllable, accessible generative AI. Award details ↗

ServiceMay 2026

Named an Outstanding Area Chair for CVPR 2026

Recognized for outstanding service on the program committee for #CVPR2026.

PapersMar 2026

Four papers accepted to CVPR 2026

The lab will present four papers at CVPR 2026, including ∞-RoPE for infinite, action-controllable video and DPP-GRPO for diverse video generation.

AwardJun 2025

ConceptAttention received Best Paper recognition

For concept-level interpretability in diffusion models, at the CVPR 2025 Visual Concepts Workshop.

PapersSept 2025

Four papers accepted at NeurIPS 2025

Including LoRAShop (Spotlight) and CREA, spanning efficient personalization and creative generation.

PapersFeb 2025

Three papers at CVPR 2025

Including FluxSpace and related work on controllable, interpretable generation.

PapersJuly 2025

Two papers accepted to ICCV 2025

Including CLoRA, selected as a Highlight.

PapersFeb 2024

Three papers accepted to CVPR 2024

Including NoiseCLR (Oral) and RAVE (Highlight).

04 — Selected Publications

Recent papers

A selection of recent peer-reviewed work.

2026
Infinity-RoPE: Action-Controllable Infinite Video Generation Emerges from Autoregressive Self-Rollout
Yesiltepe, H., Meral, T. H. S., Akan, A. K., Oktay, K., Yanardag, P.
CVPR 2026
View · arXiv ↗
2026
Diverse Video Generation with Determinantal Point Process-Guided Policy Optimization
Kazimi, T., Dunlop, C., Yanardag, P.
CVPR 2026
View · arXiv ↗
2025
CLoRA: A Contrastive Approach to Compose Multiple LoRA Models
Meral, T. H. S., Simsar, E., Tombari, F., Yanardag, P.
ICCV 2025 · Highlight
View · arXiv ↗
2025
LoRAShop: Training-Free Multi-Concept Image Generation and Editing with Rectified Flow Transformers
Dalva, Y., Yesiltepe, H., Yanardag, P.
NeurIPS 2025 · Spotlight
View · arXiv ↗
See all publications at our lab website Project pages, code, and demos for most papers at github.com/gemlab-vt.
05 — Recent Talks

Recent Talks & Keynotes

Recent keynotes and invited talks on generative AI.

Jul 2026Upcoming
Keynote · From Frames to Stories
ICML 2026
Jun 2026
Keynote · AI for Visual Arts Workshop
CVPR 2026
Jun 2026
Keynote · AI-assisted Long Video Creation Workshop
CVPR 2026
Jun 2026
Keynote · Personalization in Generative AI Workshop
CVPR 2026
Apr 2026
Invited Talk
University of Michigan · Department of Computer Science
Sep 2025
Invited Talk
Virginia Academy of Science, Engineering & Medicine · The Next Generation of Generative AI
06 — Teaching & Service

Teaching & Mentoring

Below are some of the courses I’ve recently taught.

Recent Teaching

Grad
Fantastic Generative AI Models and Where to Find Them
Diffusion, rectified flow, and modern generative AI
Grad
Computer Vision
Foundations and modern architectures
Ugrad
Creative AI Capstone
Project-based studio in generative & creative AI
Ugrad
Professionalism in CS
Ethics in AI

Recognition & Awards

  • Best Paper — CVPR Visual Concepts Workshop2025
  • Best Paper — NeurIPS CTRL-GEN Workshop2021
  • Best Paper Honorable Mention — ACM Creativity & Cognition2022
  • TÜBİTAK 2232 Outstanding Researcher Fellowship2019
  • Fulbright Fellow · Google Anita Borg Scholar2010

Professional Service

  • Area ChairCVPR · ICCV · ECCV

Let's talk generative AI.

Interested in collaboration, prospective graduate study, or industry partnership? I'd love to hear from you.

Office
Department of Computer Science
Virginia Tech
Blacksburg, VA 24061