Neurosurgeon · Physician-Scientist · Clinical AI · Global Health

During neurosurgical residency I was already building computer-vision models for intracranial hemorrhage on CT. By late 2022, early language models began extending what I could do in clinical research without a dedicated computational team.

One project grew into a reusable quantitative pipeline that offered a new way to examine normal-pressure hydrocephalus. It remains in use as new patients enter the study in Turkey, and global collaborators independently extended both the dataset and the method into new Hydrocephalus Society work, including an award-winning project.

My neurosurgery thesis on normal-pressure hydrocephalus (NPH) developed quantitative MRI analysis of the brain and its cerebrospinal-fluid spaces. That work provided the anatomical foundation for Cistern, an interactive 3D modeling and simulation project. International collaborators subsequently extended the NPH methods and dataset into Hydrocephalus Congress presentations, including an award-winning project.

I built the browser application to bring ventricular and cisternal geometry, anatomical sections and an exploratory CSF-flow model into one workspace. The later simulation extension uses a lattice-Boltzmann fluid solver and advection–diffusion tracers, with configurable catheter inlets, outlets and drainage. Users can change an experiment and inspect tracer arrival and retention across compartments.

This is a research demonstration for exploring model behavior, rather than a validated prediction of an individual patient’s CSF physiology.

With Netanel Ben-Shalom at Lenox Hill Hospital, whose work includes transcranioplasty ultrasound through sonolucent implants, I built a rapid ultrasound annotation and segmentation tool. It trains random forests from sparse annotations, designed around the limited input a clinician could realistically provide in the operating room.

My contribution was hands-on implementation: turning the annotation workflow and machine-learning approach into a usable research tool. The manuscript has been submitted, and a medRxiv preprint is planned. I also contribute to the group’s broader transcranioplasty-ultrasound research.

I built an interactive imaging workspace that brings registered MRI and intraoperative ultrasound into a shared 3D scene, alongside reference white-matter pathways and cortical regions. Linked views let researchers inspect the ultrasound window in its wider anatomical context.

The example below combines RESECT MRI/ultrasound with mapped population-reference tractography and HCP-MMP cortical regions. The pathways and regions provide anatomical context; they are not structures directly measured by ultrasound.

In 2024, I co-authored a Clinical Neurology and Neurosurgery study evaluating ChatGPT on brain-tumor diagnosis and treatment planning. I built the API-based system that sent clinical questions to the model and captured its answers for independent assessment by practicing neurosurgeons.

With Randy D’Amico, I later moved from benchmarking performance to a harder question: what happens when AI becomes part of the clinical cognitive system? That became our 2026 Neurosurgery letter on the extended mind and the uneven frontier of clinical AI.

It also led to an invited Neurosurgery review on how AI studies should handle data quality, leakage, validation, interpretability, reproducibility and clinical meaning.

With A. Gabriella Wernicke and Netanel Ben-Shalom, I built BrachyAtlas to combine anatomy, imaging, implant geometry and radiation dose in one patient-specific intracranial brachytherapy workflow.

It integrates those inputs with an AI agent that helps the clinician work through voluminous connectomic and expected radiation-damage reports, surfacing the anatomy, likely network effects and treatment tradeoffs that matter most for planning.

During my PhD at the Feinstein Institutes, working with Stavros Zanos and Eric H. Chang, I built a human peripheral-nerve imaging platform with AI as part of the process. Over three years, it grew to span tissue clearing, light-sheet microscopy, molecular anatomy, image analysis and single-fiber reconstruction.

AI also helped overcome physical constraints: I designed and iterated custom holders, access tools and medical-device concepts, then 3D-printed and tested them experimentally. Some concepts became the basis for provisional patent work—bridging ideas, code and physical tools.

The work led to invited presentations at Rockefeller University and the Center for Pain Studies at UT Dallas.

From the same program came the human vagus atlas: we turned thousands of anatomical branch observations into a standardized, surgically relevant map, a Brain Stimulation paper, open data and analysis, and an interactive explorer. NIH SPARC invited a dedicated seminar; Kevin Tracey called it “a major advance in the field of vagus nerve science,” noting the question had persisted “ever since the time of Galen.”

With Randy D’Amico’s brain-tumor group, I build systems that turn dense patient-specific connectomic data into interpretable phenotypes and longitudinal trajectories.

The Disconnectome Explorer is the quickest to try: place a tumor in a 3D brain and it returns the tracts it would disrupt. What began as analysis code has grown into tools the team can use directly—small analytical capabilities that can be called, combined and reused through increasingly agent-integrated workflows.

With Netanel Ben-Shalom, we converted visual cranial-deformity judgment into an automated 3D quantitative step. The work was presented orally at CNS and is accepted in Operative Neurosurgery.

The collaboration led to my involvement with the Society for Neuroplastic Surgery and tools its members can use. I built Neuroplastic Anatomy for publication-quality, reusable AI anatomy illustrations; outputs are entering Society educational supplements. I am a member of the Society for Neuroplastic Surgery and presented my quantitative cranial-shape measurement work at its event at Lenox Hill Hospital in New York. Our ongoing collaboration also includes Ben-Shalom’s transcranioplasty-ultrasound research through sonolucent implants.