Researcher at Huawei Cloud R&D · Helsinki, Finland
Pioneering Generative AI for Autonomous Driving
I am a Computer Vision and Generative AI researcher at Huawei Cloud R&D in Helsinki, Finland, where I push the boundaries of what machines can see, understand, and generate.
My research journey began with a PhD in Biometrics at the University of Biskra (Algeria), where I specialized in kinship verification and facial analysis using deep learning. Since joining Huawei in 2023, I've pivoted to large-scale industrial AI, working across OCR systems, Visual Language Models, Large Language Models, and most recently, Generative AI for Autonomous Driving.
Today, my primary focus spans Video Generation for Autonomous Driving — pushing the boundaries of 4D LiDAR video synthesis to create photorealistic, controllable, and temporally consistent sensor simulations for next-generation autonomous vehicles. I am currently working on a novel approach to multi-sensor Dual-Modality (LiDAR + Camera) video generation that is under active development and review.
Beyond autonomous driving, I am deeply passionate about Artificial General Intelligence — exploring abstract reasoning, program synthesis, and the path toward human-level AI. I actively engage with ARC-AGI v2 & v3 challenges, particularly the interactive variants, as a rigorous testbed for generalization and compositional reasoning.
CV Researcher @ Huawei
Helsinki, FIVideo Generation for Autonomous Driving
Artificial General Intelligence
From biometric recognition to large-scale generative AI systems
Developing controllable 4D Dual-Modality (LiDAR + Camera) video generation with diffusion models and transformer architectures. Enabling multi-sensor joint simulation for autonomous vehicle testing and development.
Research on VLLMs and LLMs for document understanding, complex visual reasoning, and multimodal representation learning at scale.
Generative models for high-fidelity image synthesis and controllable video generation, with applications in synthetic data creation for autonomous systems.
Deep learning for kinship verification, personality trait estimation from facial imagery, and robust face recognition using local and global descriptors.
Optical character recognition systems and intelligent document processing pipelines for industrial-scale document understanding workflows.
Applied research on LLMs for reasoning, natural language understanding, and integration within multimodal AI pipelines.
An efficient encoder-based approach for the QIAS 2025 Shared Task on Islamic Inheritance Reasoning, demonstrating strong performance on legal reasoning benchmarks.
A novel multi-level pyramid co-variance operator framework for automatic estimation of personality traits and job screening scores from visual data, achieving state-of-the-art results.
Leveraging deep convolutional neural network features for kinship verification from facial images, demonstrating robust family relationship detection across varied conditions.
Combining Local Phase Quantization (LPQ) and Local Directional Pattern (LDP) descriptors with machine learning for robust kinship verification.
Conducting industrial research across multiple advanced AI domains, progressing from perception to full generative AI systems.
Researching controllable Dual-Modality (LiDAR + Camera) 4D video generation with diffusion transformers and multi-sensor architectures for autonomous vehicle simulation.
Generative models for synthetic image/video data creation and controllable generation for simulation pipelines.
Multimodal language models for document understanding and complex visual reasoning at industrial scale.
Optical character recognition pipelines for large-scale document processing applications.
Doctoral research focused on biometric recognition systems, kinship verification, face analysis, and personality computing using deep learning. Published peer-reviewed work in IEEE conferences and international journals.
Master's degree in Advanced Automatics, building a strong foundation in control systems, signal processing, and applied mathematics.
I'm always open to research collaborations, discussions, and opportunities.