AI Researcher and Engineer

ai.lead@erisinnovate.ai

CV

Taneem Ullah Jan

I am currently the AI Lead at Eris AI, where I drive research and engineering in multimodal and generative modeling to build foundation models for agentic AI applications. I oversee model design, system architecture, and deployment of next-generation interactive agents. Previously, I was an AI Researcher at VOLV AI and a Research AI Engineer at BHuman AI.

Research Work

My work spans the intersection of multimodal learning, generative modeling, and computational neuroscience, advancing neural avatars, virtual humans, systems that move from pattern recognition toward causal understanding of intelligent behavior.

tldr: An embedding-driven approach combines audio encoders with multimodal projectors to enable direct speech-to-text processing, achieving significant performance while training minimal parameters through block optimization.

tldr: An interactive 3D body modeling system that allows real-time manipulation of human body shapes through intuitive measurement sliders with immediate visual feedback in a fully navigable 3D environment.

tldr: VMVLM enhances vision-language models by using dual visual pathways, combining Q-Former queries with direct ViT feature injection for improved multimodal instruction following.

tldr: A self-improving AI system that uses LLMs and evolutionary algorithms to autonomously enhance code across multiple quality dimensions.

tldr: A unified framework for 3D virtual try-on that transforms simple 2D images into realistic 3D representations, by efficiently integrating clothing with the human body in a pose-adaptive manner.

tldr: A two-stage unified audio-driven talking face generation framework, which can render high-fidelity, lip-synchronized videos with improved inference speed.

tldr: Current image inpainting techniques are too heavy; this paper introduces a Row-wise Flat Pixel LSTM, a small hybrid model for the efficient and high-quality restoration of small images.

tldr: A robust and efficient talking face generation model with highly accurate lip synchronization and full facial expressiveness with more extended audio and high-quality video resolutions.

tldr: An unsupervised one-shot talking head video generation model using neural rendering and motion transfer techniques with non-linear transformation to animate static images.

tldr: Innovative face-swapping model that preserves the source identity features accurately while seamlessly adapting target attributes applicable to images and videos.

tldr: An accurate deep learning model converting GUI mockups into HTML code, streamlining web development for non-programmers.

Thanks to Jon Barron for this template.