AI Consulting
Overview
Our AI consulting team helps faculty, students, and research groups apply artificial intelligence (AI) to academic research. Led by experienced researchers and supported by graduate and undergraduate consultants, we assist with project scoping, data preparation, method selection, model evaluation, troubleshooting, training, and access to computing resources. The team brings expertise in biomedical imaging, multi-omics, generative AI, large language models (LLM), computer vision, high-performance computing (HPC), distributed learning, and machine learning (ML). Through advising, workshops, demonstrations, templates, and small prototypes, we help research teams move from early ideas to practical, responsible AI solutions.
Table of Contents
Statement of Purpose
Our mission is to make AI more accessible, useful, and responsible in academic research. We work with faculty, students, and technical teams to clarify research goals, identify appropriate AI approaches, and support projects at the right level of complexity. Our consulting philosophy is to listen first, recommend the simplest effective path, and strengthen each team’s ability to continue the work independently.
Services
We provide AI consultation for academic teams exploring, developing, or improving AI enabled projects. Services include project scoping, data preparation, exploratory analysis, feature engineering, model selection, model development, evaluation, troubleshooting, and code review.
We also support workflow automation, reproducible research pipelines, technical documentation, responsible AI guidance, small prototype development, and limited grant or project planning support. Through workshops, tutorials, demonstrations, and one-on-one consultations, we help researchers build practical skills they can apply beyond a single project.
Areas of Expertise
Our team brings technical expertise across artificial intelligence, data science, and research computing. We support work involving ML, deep learning (DL), generative AI, LLM, natural language processing (NLP), computer vision, biomedical AI, and data driven analysis. Additional strengths include HPC, cloud platforms, distributed learning, scalable data processing, workflow automation, whole-slide image (WSI) analysis, tissue segmentation, single-cell and multi-omics analysis, transformer based models, efficient machine learning, randomized learning methods, dataset compression, fast inference, and responsible AI practices.
Research Domains Supported
We support researchers across disciplines where AI, data science, and computational methods can advance discovery. Areas of experience include biomedical research, precision medicine, nephrology, medical imaging, digital pathology, single-cell sequencing, multi-omics analysis, over all healthcare, computer science, engineering, and data intensive STEM and NON-STEM research.
We also work with projects involving scientific text analysis, network analysis, software engineering, computer vision, and computational workflows that depend on GPUs, cloud platforms, distributed systems, or high-performance computing.
Meet the Consultants
Jose L. Agraz, Ph.D., Lead Researcher AI Consultant
Dr. Agraz helps researchers apply AI methods and translate scientific questions into practical AI workflows. His expertise includes biomedical imaging, whole-slide image (WSI) analysis, tissue segmentation, single-cell sequencing, multi-omics analysis, precision nephrology, HPC, and AI enabled biomedical discovery. His publications include work on H&E WSI stain normalization, computational pathology, glioblastoma survival prediction, MRI instrumentation, and single-cell approaches to kidney disease.
Links: Contact | Website | CV | Bio | LinkedIn | Google Scholar
Reza Gheibi, Ph.D., Lead Researcher AI Consultant
Dr. Gheibi supports researchers working with ML, generative AI, biomedical AI, transformer based models, HPC, and GPU enabled workflows. His experience includes building AI pipelines for healthcare applications, fine-tuning biomedical language models, developing generative and transformer models with Hugging Face and PyTorch, analyzing COVID-19 networks, and mentoring students in programming and research development.
Links: Contact | CV | LinkedIn | Google Scholar
Shayan Shafaei, Lead Researcher AI Consultant
Shayan Shafaei helps research teams select appropriate AI and machine learning tools, design implementation strategies, and use computational resources efficiently. His research focuses on efficient machine learning, randomized learning methods, dataset compression, fast inference, k-nearest neighbor classification, and distributed machine learning. He also has experience in computer vision, face recognition, object detection, and autonomous navigation. His recent papers address distributed kNN, randomized least squares, random features, and efficient data-dependent projection methods.
Links: Contact | CV | LinkedIn | Google Scholar
How to Work With Us
The consultation process begins with a conversation about your research question, available data, timeline, and technical challenges. We first clarify what you want to accomplish and whether AI is the right approach. Then, we suggest a practical path forward, which may include recommended methods, tools, computing options, training materials, documentation, demonstrations, or a small prototype.
Users can expect collaborative guidance tailored to their experience level. Our goal is to provide useful direction without overcomplicating the project or creating long-term dependency.
Request a Consultation
To request an AI consultation, contact AI Consulting Director David Akin or Research Computing Director Dr. Henry Neeman at support@oscer.ou.edu. In your request, include your name, department, project title, research goals, current technical challenges, timeline, and any tools or methods you have already tried. This information helps the team understand your needs and prepare for a productive consultation.
