AI Researcher & Engineer
I am an AI researcher and engineer working on multimodal machine learning, generative AI, medical imaging and AI for Science. My work ranges from generating radiology reports from 3D chest CT and physics-informed Earth observation to real-time speech-to-speech systems for embodied AI, with a particular interest in models that work well under limited compute and data.
AI Research Engineer at IQAI. MSc in AI for Science (Overall Distinction), AIMS South Africa, Google DeepMind Scholar.
Research
How can models learn jointly from images, volumes, speech and text, and ground what they generate in what they perceive?
How can large generative models be trained, adapted and deployed efficiently, extended to low-resource languages, and used reliably as reasoning components in larger systems?
How can AI make medical imaging and clinical documentation more accurate and more accessible, particularly where specialist expertise and compute are scarce?
How should learned models and scientific models be combined so that predictions respect known physics and transfer from simulation to real observations?
How can we build models whose representations and uncertainties can be understood, inspected and trusted?
What representations and training signals let a model reason over heterogeneous inputs and act on them under real-world constraints?
Selected research
Medical imaging · Vision-language
Generating expert-level radiology reports directly from volumetric chest CT by adapting a RadImageNet-pretrained ResNet-50 to 3D data with axial-coronal-sagittal convolutions and decoding with GPT-2 through cross-attention, trained on a single 24 GB GPU and a fraction of the CT-RATE dataset.
Lead author · MSc thesis research, AIMS South Africa / UWC (2024)
AI for Science · Scientific machine learning
Retrieving vegetation biophysical variables from Sentinel-2 imagery by inverting the PROSAIL radiative transfer model with neural networks that use the physical model as a differentiable decoder, trained only on simulated data.
AI Research Engineer Fellow, InstaDeep (Nov 2024 – May 2025) · Co-author of the preprint
Generative AI · Reasoning in complex systems
A vision for embedding large language models in the 6G radio access network control loop, with a formal framework aligned to the O-RAN architecture and results on policy expressiveness and convergence.
Co-author · Workshop paper, NeurIPS 2025 AI4NextG
Selected publications
2027
Pelumi Victor Aderinto, Mehrdad Ghaziasgar
PAAISS 2025 · Springer LNICST vol. 697
2025
Oluwaseyi Giwa, Michael Adewole, Tobi Awodumila, Pelumi Aderinto
AI4NextG Workshop @ NeurIPS 2025
2025
Prince Mensah, Pelumi Victor Aderinto, Ibrahim Salihu Yusuf, Arnu Pretorius
arXiv preprint
Latest
2 August 2026
Talk
Tutorial, Deep Learning Indaba 2026
Deep Learning Indaba 2026 · Pan-Atlantic University, Lagos, Nigeria · Co-presented with Catherine Essuman
October 2025
Award
4th Pan-African Artificial Intelligence and Smart Systems Conference (PAAISS 2025)
PAAISS 2025, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
2024
Fellowship
InstaDeep
InstaDeep