Kian Izadpanah — Computer Vision Researcher

01 — Publications

Publications

Peer-reviewed and preprint contributions in computer graphics, computer vision, and multimedia systems.

2026

SIGGRAPH Asia 2026 · Image Editing · Generative Models

SIA: Selective Image Analogy

Amirhossein Alimohammadi*, Kian Izadpanah*, Bardiya Kariminia, Yiorgos Chrysanthou, Ali Mahdavi-Amiri

* Equal contribution

Image Analogy Image Editing Diffusion Models SIGGRAPH Asia

2026

Computer Vision · Robotics · Dataset

JRDB-Pose3D: A Multi-person 3D Human Pose and Shape Estimation Dataset for Robotics

Sandika Biswas, Kian Izadpanah, Hamid Rezatofighi

3D Human Pose SMPLX Robotics Dataset

2026

Autonomous Vehicles · VANETs · Multimedia

CITRON: Collaborative Image Stitching and Redundancy Elimination for Energy-Efficient Multimedia Offloading in VANETs

Kian Izadpanah, Mohammad Hossein Soheilian, Bardia Safaei

Image Stitching VANETs Energy Efficiency Multimedia

02 — About

Research Profile

I am Kian Izadpanah, a Computer Vision researcher specialising in how machines understand and manipulate visual content. I completed my BSc in Computer Engineering at Sharif University of Technology in September 2025, during which I pursued research across several international laboratories.

I am currently pursuing graduate studies in Computer Science at the University of Cyprus (UCY), with an active research collaboration at the Gruvi Lab, Simon Fraser University (SFU). My primary research focus is on Generative Models, with an emphasis on image synthesis and controlled editing.

Since June 2026 I have also been a Research Scientist at the CYENS Centre of Excellence in Nicosia, where I work on Generative AI, Video Generation, and their applications in industry.

My research is supervised by Ali Mahdavi-Amiri and Daniel Cohen-Or at SFU, and by Yiorgos Chrysantou and Andreas Aristidou at UCY.

Location
Nicosia, Cyprus

Email
kianizadpanah@gmail.com

Focus
Generative AI & Video

GitHub
KianIzadpanah

Things I care about

Computer Vision

Representation learning and visual scene understanding from image and video data.

Generative Models

Diffusion models and flow-based architectures for image synthesis and controlled editing.

Deep Learning

Neural architectures, optimisation methods, and large-scale model training.

03 — Education

Academic Background

Current

🇨🇾

University of Cyprus (UCY)

Computer Science

Feb. 2026 — Present

Pursuing graduate research in generative models and computer vision, with a focus on image synthesis, editing, and deep generative architectures.

Supervisors: Y. Chrysantou & A. Aristidou

Collaboration

🇨🇦

Gruvi Lab @ Simon Fraser University

Research Collaboration

Feb. 2026 — Present

Active research collaboration on image editing and generative model research, working alongside leading researchers in computer vision and computational graphics.

Supervisors: A. Mahdavi-Amiri & D. Cohen-Or

Completed — Sep. 2025

Sharif University of Technology

BSc in Computer Engineering

Sep. 2021 — Sep. 2025

Completed the undergraduate programme in Computer Engineering with a strong focus on machine learning and computer vision. Enrolled in graduate-level courses in Machine Learning and 3D Computer Vision alongside the core curriculum.

3D Computer Vision ★ Machine Learning ★ Artificial Intelligence Linear Algebra Probability & Statistics Computer Simulation Game Theory Automata Theory Database Design

★ Graduate-level course

04 — Industry

Industry Experience

Applied research and development roles in industry.

Jun. 2026 — Present

CYENS Centre of Excellence

Research Scientist

Generative AI Video Generation Industry Applications

Conduct applied research in Generative AI, developing and adapting generative models for real-world visual content creation.
Work on video generation, with a focus on controllable synthesis and temporal consistency in generated sequences.
Translate generative models into industry applications, bridging research prototypes and deployable systems alongside industrial partners.

05 — Academic

Academic Research Experience

Research positions and laboratory affiliations in academia.

Jul. 2024 — Dec. 2024

CORE Lab, Cambridge University

Research Assistant (Summer Internship)

Supervisor: Prof. Cengiz Öztireli

Investigated methods for generating and editing 3D human poses, addressing challenges in multi-joint articulation and spatial consistency.
Implemented and evaluated 3D body frameworks including Joint2Human, FOF, SMPLX, STAR, and SPIN.
Applied text-driven generation models including CLIP, CLIP-PAE, and CLIP-Forge to guide pose synthesis.

Nov. 2023 — Jun. 2024

VL4AI Lab, Monash University

Research Assistant

Supervisor: Prof. Hamid Rezatofighi

Contributed to the JRDB dataset, with a focus on improving 3D human pose estimation and annotation quality at scale.
Utilised SMPLX for 3D mesh generation and quaternion representations for rotation parameterisation.

Jul. 2023 — Dec. 2023

Robust/Interpretable ML Lab, Sharif University

Research Assistant

Supervisor: Prof. Mohammad Hossein Rohban

Investigated cross-domain generalisation for medical object detection, addressing distribution shift in domain adaptation across imaging devices and clinical sites.
Proposed a pipeline combining diffusion-based data augmentation with a VAE-based out-of-distribution detector to improve RetinaNet performance on the MIDOG benchmark.

Mar. 2023 — Jun. 2023

Google

Research Assistant

Supervisor: Dr. Hossein Mobahi

Developed AGSAM (Adaptive-Gradient SAM), an extension of Sharpness-Aware Minimisation that adapts perturbation magnitude to the local geometry of the loss landscape.
Extended the optimisation formulation to incorporate both first-order gradient information and second-order curvature of the objective function.

Feb. 2023 — Apr. 2023

Robust/Interpretable ML Lab, Sharif University

Research Assistant

Supervisor: Prof. Mohammad Hossein Rohban

Studied anomaly detection and backdoor attack mechanisms, with an emphasis on detection and defence strategies for deep neural networks.
Applied out-of-distribution scoring techniques to video surveillance scenarios.

06 — Skills