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I am a Machine Learning Engineer and Researcher with a PhD in Electrical and Electronic Engineering, currently working as a Postdoctoral Researcher at the University of Birmingham. My background is in deep learning, computer vision, generative AI and 3D reconstruction, with hands-on experience building end-to-end Python/PyTorch pipelines from data generation and model development through to evaluation. I’ve also worked on Transformer-based models and agentic AI systems, and I’m particularly interested in turning advanced AI techniques into practical, reliable products.…I am a Machine Learning Engineer and Researcher with a PhD in Electrical and Electronic Engineering, currently working as a Postdoctoral Researcher at the University of Birmingham. My background is in deep learning, computer vision, generative AI and 3D reconstruction, with hands-on experience building end-to-end Python/PyTorch pipelines from data generation and model development through to evaluation. I’ve also worked on Transformer-based models and agentic AI systems, and I’m particularly interested in turning advanced AI techniques into practical, reliable products.

Jiaming Zhang

AI Engineer, Data Scientist, Software Engineer

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I am a Machine Learning Engineer and Researcher with a PhD in Electrical and Electronic Engineering, currently working as a Postdoctoral Researcher at the University of Birmingham. My background is in deep learning, computer vision, generative AI and 3D reconstruction, with hands-on experience building end-to-end Python/PyTorch pipelines from data generation and model development through to evaluation. I’ve also worked on Transformer-based models and agentic AI systems, and I’m particularly interested in turning advanced AI techniques into practical, reliable products.…I am a Machine Learning Engineer and Researcher with a PhD in Electrical and Electronic Engineering, currently working as a Postdoctoral Researcher at the University of Birmingham. My background is in deep learning, computer vision, generative AI and 3D reconstruction, with hands-on experience building end-to-end Python/PyTorch pipelines from data generation and model development through to evaluation. I’ve also worked on Transformer-based models and agentic AI systems, and I’m particularly interested in turning advanced AI techniques into practical, reliable products.

Available to hire

I am a Machine Learning Engineer and Researcher with a PhD in Electrical and Electronic Engineering, currently working as a Postdoctoral Researcher at the University of Birmingham. My background is in deep learning, computer vision, generative AI and 3D reconstruction, with hands-on experience building end-to-end Python/PyTorch pipelines from data generation and model development through to evaluation. I’ve also worked on Transformer-based models and agentic AI systems, and I’m particularly interested in turning advanced AI techniques into practical, reliable products.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Beginner

Work Experience

Engineer (Agentic AI / Recommendation Systems) at Gatewise

June 1, 2026 - June 30, 2026

Built an end-to-end agentic AI system using Gemini with tool calling, Trigger.dev, and ClickHouse to convert natural-language flight queries into structured inputs and data-backed airport arrival recommendations. Designed a deterministic recommendation engine and analytics pipeline over 2015–2025 U.S. flight data, combining airport congestion, delay/cancellation statistics, baggage, and TSA PreCheck information, with results delivered through an interactive Next.js/React interface.

Postdoctoral Researcher at University of Birmingham

April 1, 2026 - Present

Developing an end-to-end NeRF-based pipeline for multi-view 3D reconstruction from 2D radar observations, integrating physics-based simulation, synthetic data generation, model training, and quantitative evaluation. Built an automated Python/PyTorch pipeline generating large-scale simulated datasets (200 targets, 251 views per target; 50,000+ radar observations) to enable scalable 2D-to-3D reconstruction experiments on HPC. Owned the end-to-end workflow from data generation through NeRF development and 3D mesh reconstruction, achieving NMSE of 0.20 between reconstructed and ground-truth 3D target meshes.

Machine Learning Engineer at Sapper Intelligence GmbH

December 1, 2025 - March 1, 2026

Developed a scalable physics-based radar simulation pipeline generating 10,000+ synthetic images for training and benchmarking deep learning models. Designed and implemented a Transformer-based model with a learnable shrinkage module for noise suppression and target recognition from noisy radar measurements. Built an end-to-end Python/PyTorch workflow from simulation and dataset generation through model training, inference, and quantitative evaluation in a startup environment.

Researcher (Synthetic Data / Communications) at FinGAN – Synthetic Data Generation for Scalable Localization (Research project at Queen’s University Belfast)

October 1, 2024 - October 1, 2025

Designed and developed FinGAN, a generative model synthesizing signal measurements directly from spatial inputs, integrating data generation, training, evaluation, and downstream localization. Achieved RMSE 3.65 dBm and FID 4.08 while preserving downstream localization performance; published as first author at IEEE International Conference on Communications (ICC).

Researcher (Joint Reconstruction and Classification) at ClassiGAN – Joint Reconstruction and Classification with Deep Learning (Research project at Queen’s University Belfast)

October 1, 2023 - October 1, 2024

Developed a deep residual network for joint image reconstruction and target classification, replacing separate conventional imaging and classification stages with a unified learning-based pipeline. Achieved NMSE 0.019 and SSIM 0.979 for reconstruction and F1 0.981 for classification, validated on experimental measurements and published in IEEE Transactions on Radar Systems.