Tushar Nayak

computer vision focused biomedical engineer turned roboticist working in robotic surgery

biomedical vision / robotic intervention

Recovering structure from incomplete clinical data.

I am a scientist at the SurgBioMech / Pocivavsek Lab at the University of Chicago. After completing my master's in Biomedical Engineering at Carnegie Mellon University, I continue working across medical imaging, geometric vision, and physics-aware learning to turn sparse measurements into useful anatomy, motion, and deformation estimates for surgical workflows.

Current work: endovascular robotics, fluoroscopy-to-CTA deformable registration, sparse-view 3D reconstruction, and clinically grounded biomedical vision.

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Abbott Memorial Hall · Chicago, IL

research directions

Intervention

Image-guided robotic intervention, intra-operative deformation, and tele-operated surgical systems.

Vision

Geometric vision, registration, 3D reconstruction, and learning models that stay tied to measurement and physics.

Biomedical ML

Segmentation, multimodal learning, and clinically grounded modeling for noisy biomedical data.

What I work on

My work spans surgical robotics, medical imaging, 3D reconstruction, and computational pathology.

Surgical Robotics

Vision systems for endovascular robotics, tool tracking, and deformable operative scenes.

Medical Imaging

Learning-based analysis of MRI, CT, and other clinical scans for diagnosis and planning.

3D Vision & Reconstruction

Geometry recovery from sparse views, point clouds, and neural scene representations.

Computational Pathology

Histopathology models for cancer grading, subtype detection, and slide-level reasoning.

Vision-Language Models

Open-vocabulary querying and semantic grounding for surgical and biomedical scenes.

Physics-Informed Neural Networks

Models that bake in deformation, dynamics, and other physical constraints when the data alone is not enough.

featured research

Physics-Informed Endovasculature Deformation Estimation And Registration
ongoing Surgical Robotics Medical Imaging

Physics-Informed Endovasculature Deformation Estimation And Registration

Research at CERLAB (master's thesis)
Spatiotemporal Glioblastoma Evolution Visual Prediction
paused Medical Imaging Neural ODEs

Spatiotemporal Glioblastoma Evolution Visual Prediction

Research at The ∀ Lab & Image Science Lab

featured projects

Open-Vocabulary Surgical Tool Detection and Tracking
active prototype Surgical Robotics Tool Tracking

Open-Vocabulary Surgical Tool Detection and Tracking

A real endoscopy pipeline that turns text prompts into surgical tool boxes, masks, tracking overlays, and evaluation metrics using Grounding DINO and SAM2.
Gaussian Occupancy Cardiac Reconstruction
active extension 3D Vision Medical Imaging

Gaussian Occupancy Cardiac Reconstruction

A sparse-view echocardiography project that recovers 3D cardiac anatomy with Gaussian occupancy fields, differentiable slice supervision, and mesh evaluation.
Attention-augmented Dual-View Mammogram Alignment for Enhanced BI-RADS Classification
completed Medical Imaging Mammography

Attention-augmented Dual-View Mammogram Alignment for Enhanced BI-RADS Classification

Course project for Projects in Biomedical AI
Few-Shot 2D Echo to 3D Cardiac Reconstruction via Neural Implicit Priors
completed 3D Vision Medical Imaging

Few-Shot 2D Echo to 3D Cardiac Reconstruction via Neural Implicit Priors

Course Project for Learning for 3D Vision

During my master's at Carnegie Mellon University, I worked on the vision subsystem of a haptically enabled endovascular robotic tele-surgical platform with doctoral candidate Rishi Basdeo. My work investigated physics-informed neural networks and neural ordinary differential equations for quantifying deformation from 2D fluoroscopy angiograms and registering it to pre-operative computed tomography angiograms.

Before Pittsburgh, I completed my undergrad at Manipal Institute of Technology with a major in Biomedical Engineering, focusing on pattern recognition and image processing, and a minor in Data Science. Over the second half of my undergrad, I worked under Professor Niranjana S and Dr. Krishnaraj Chadaga at the Biomedical Computing Lab on projects ranging from skin lesion image-based viral infection detection to multi-stage and multi-modal cancer detection.

Between my bachelors and masters, I also spent a year as a researcher at IIT Hyderabad working on motion-capture & electromyography analysis for exercise and the Indian Council of Medical Research where I worked on an ultrasound-based fetal anomaly system.

Besides lab work, I am also usually giving/boring people with my usual spiel as one of the BME department's ambassador, going trailbiking, playing the piano or continuing work on this website!

news

Jul 20, 2026 After graduating from Carnegie Mellon University, I am excited to be starting as a Scientist at the SurgBioMech / Pocivavsek Lab at the University of Chicago, led by Dr. Luka Pocivavsek.
Jun 10, 2026 Visiting the Massachusetts Institute of Technology & Worcester Polytechnic Institute this week! At WPI, I’ll be delivering a seminar session based on my master’s thesis and recent projects, focusing on the real-time registration and 3D reconstruction of medical imaging data from 2D space.

latest posts

May 27, 2026 sparse-view clinical reconstruction: explicit vs implicit representations
May 26, 2026 how teaching courses changed how i think about machine learning systems

selected publications

  1. lung-2024
    Automated histopathological detection and classification of lung cancer with an image pre-processing pipeline and spatial attention with deep neural networks
    Tushar Nayak, Nitila Gokulkrishnan, Krishnaraj Chadaga, and 3 more authors
    Cogent Engineering, 2024 · journal
    Abs DOI PDF