Radiology Building, 1st Floor, Room RA-126
20 Shattuck Street, Boston, MA 02115
Surgical Imaging and Mechatronics Lab
3D liver reconstruction

3D Liver Reconstruction

Intraoperative liver surface reconstruction from stereo laparoscopy using non-rigid SLAM.

Ear surface reconstruction

Trackerless Skull Base Navigation

Surface reconstruction from 3D endoscopy registered to CT, now evaluated in anterior and lateral skull base surgery.

Hand-held concentric tube robot prototype held in hand

Concentric Tube Robots for PCNL

Patient-specific planning of the puncture site, trajectory, and robot design for kidney stone access.

Image-guided VATS

Image-Guided Lung Surgery

Localizing lung nodules and measuring resection margins in real time during video-assisted thoracoscopic surgery.

Breast deformation

Breast Deformation During Surgery

Supine and prone MRI registered to quantify tumor displacement between diagnostic imaging and surgery.

Tendon-driven robotic catheter with tendon actuation unit, force sensor and motion controllers

Robotic Catheter Manipulation

A robotic manipulator that guides intracardiac echocardiography catheters during cardiac ablation.

News & Events

  • Oct 2026

    Two postdoctoral positions open: SLAM and neural scene reconstruction, and tissue deformation modeling. Details

  • Sep 2026

    New NIH R01 on intraoperative fluorescence lifetime navigation for oral cancer, with Dr. Anand Kumar.

  • Aug 2026

    NIH R21 awarded for biomimetic palpation of lung nodules.

  • Jun 2026

    Navid Feizi presented few-shot physics-informed shape reconstruction of concentric tube robots at ICRA 2026 in Vienna.

  • Jun 2026

    Paper on friction dynamics in Cosserat models published in IEEE/ASME Transactions on Mechatronics.

  • Nov 2025

    Trackerless navigation for exoscopic trans-mastoid surgery published in Otolaryngology–Head and Neck Surgery.

  • Oct 2025

    Compact concentric tube robot for PCNL published in IEEE Transactions on Medical Robotics and Bionics.

  • Sep 2025

    Pilot clinical trial of real-time margin assessment in VATS published in JTCVS Techniques.

  • Sep 2025

    SLAM-based fluorescence lifetime imaging paper presented at MICCAI 2025.

  • Apr 2024

    Skull base navigation using 3D endoscopy published in JAMA Otolaryngology–Head & Neck Surgery.

  • Jul 2022

    Paper on concentric tube robot planning for PCNL accepted to MICCAI 2022.

  • May 2022

    Our research on image-guided surgery featured in Harvard Magazine.

Welcome

The Surgical Imaging and Mechatronics (SIM) Lab at Brigham and Women's Hospital and Harvard Medical School develops technology that improves the surgeon's ability in the operating room. Our work covers three areas: surgical navigation to improve the surgeon's visualization, robotics to improve dexterity, and machine learning to improve computational ability.

We work closely with surgeons in thoracic surgery, otolaryngology, urology, breast surgery, and cardiac electrophysiology, and many of our systems are evaluated in the Advanced Multimodal Image-Guided Operating (AMIGO) suite and in clinical studies.

We are recruiting postdoctoral fellows in surgical SLAM and neural scene reconstruction, and in tissue deformation modeling and simulation. See Open Positions for details.

Research

Our research spans three connected areas.

Surgical Navigation

Navigation systems that register preoperative CT and MRI to the surgical field and compensate for tissue deformation.

  • Rigid and non-rigid surface reconstruction (SLAM)
  • Image-guided surgical navigation
  • Mixed and augmented reality for surgery

Robotics

Continuum robots and robotic instruments that reach targets beyond the range of straight tools.

  • Concentric tube robots for PCNL
  • Tendon-driven continuum manipulators
  • Robot-assisted catheter insertion and cardiac ablation
  • Robot-assisted tumor palpation

Machine Learning

Learning methods for surgical images and robot models where labeled data is limited.

  • Medical image segmentation and registration
  • Ultrasound and elastography tumor segmentation
  • Data-driven modeling of continuum robots

Current Projects

Selected projects from 2023 to 2026 with their key publications.

Surgical Navigation

Ear surface reconstruction with inner-ear structures

Trackerless Navigation and Augmented Reality

SLAM reconstructs the tissue surface from 3D endoscope or exoscope video and registers it to preoperative imaging, removing the need for an external tracker. The system has been evaluated in anterior and lateral skull base surgery, trans-mastoid surgery, partial nephrectomy, and liver surgery. In otology, augmented reality overlays inner-ear structures segmented from CT on the surgical view and has been compared with standard-of-care imaging for identifying temporal bone anatomy.

Image-guided VATS

Real-Time Margin Assessment in Lung Surgery

A tumor marker and an EM-sensorized surgical stapler measure the distance to the nodule during resection. In a pilot clinical trial, measurements agreed closely with pathology. Licensed to Navigation Sciences.

Breast MRI deformation

Breast Surgery Guidance

Intraoperative supine breast MRI to assess residual tumor, and a SLAM system that reconstructs the breast from a low-cost camera for reconstructive surgery.

Mouse model, stacked top to bottom: SLAM surface with fluorescence lifetime signal, CT segmentation, and combined SLAM, FLT and CT overlay

Fluorescence Lifetime Imaging with SLAM

Real-time SLAM correction and 3D visualization for fluorescence lifetime imaging, so that lifetime maps stay registered to the tissue as the camera and anatomy move. This work is being extended to navigated imaging of oral cancer with co-registration to MRI and CT.

Robotics

Hand-held concentric tube robot: cutaway design showing tube carriages, motors and motion controller, and the prototype held in hand

Concentric Tube Robots for PCNL

Patient-specific planning of the access path and tube set from CT, delivered by a compact concentric tube robot, with learned shape reconstruction.

Tendon-driven catheter robot with tendon actuation unit, force sensor and motion controllers, and the bending section tracked by an EM sensor

Continuum Robots and Robotic Catheters

Cosserat-rod models with friction, deep Koopman dynamics, and model predictive path integral control for tendon-driven continuum robots, applied to robotic intracardiac echocardiography catheters and machine-learning force estimation for steerable ablation catheters.

Robot-held ultrasound transducer pressing on an artificial phantom over a force sensor, with the ultrasound scanner showing B-mode and elastography images

Robotic Palpation and Ultrasound Elastography

Robot-assisted tumor localization that fuses B-mode ultrasound and strain elastography, extended to biomimetic palpation of lung nodules.

Publications

Publications and patents from 2022 to 2026. For the complete list, see Google Scholar.

2026

  1. Pedrosa FC, Feizi N, Arefinia E, Jayender J, Patel RV. On integrating friction dynamics into Cosserat models for tendon-driven continuum manipulators. IEEE/ASME Transactions on Mechatronics, 2026.
  2. Feizi N, Pedrosa FC, Patel RV, Jayender J. Few-shot physics-informed neural network for shape reconstruction of concentric-tube robots. IEEE International Conference on Robotics and Automation (ICRA), pp. 10107–10114, 2026.
  3. Abkhofte S, Naidu AS, Patel RV, Jayender J. Multimodal cross-attention fusion of B-mode ultrasound and strain elastography for tumor segmentation in robotics-assisted surgery. IEEE Transactions on Medical Robotics and Bionics 8(2):679–690, 2026.
  4. Arefinia E, Feizi N, Pedrosa FC, Patel RV, Jayender J. Error-state model predictive path integral control of tendon-driven continuum robots using Cosserat rod dynamics with strain parametrization. IEEE Robotics and Automation Letters 11(3):3867–3874, 2026.
  5. Bartholomew RA, Zhou H, Mital K, Haleem A, Montigny DJ, Smith TR, Guenette JP, Jayender J, Corrales CE. Integration of trackerless surface reconstruction-based surgical navigation with exoscopic trans-mastoid surgery. Otolaryngology–Head and Neck Surgery 174(1):219–229, 2026.
  6. Huang EY, Zhou H, Platonov J, Clinton TN, Dall CP, Mossanen M, et al., Jayender J. Evaluation of a trackerless surgical navigation system for partial nephrectomy using 3D laparoscopy-based surface reconstruction. The Journal of Urology 215(5S):e1507, 2026. [Abstract]
  7. Jayender J, Bueno R, Lucas AD, Robinson TW, Roth LA. System and method for percutaneous deployment of sensors. US Patent 12,708,332, 2026. [Patent]
  8. Bueno R, Jayender J, Lucas AD. System and method for a tissue resection margin measurement device. US Patent 12,544,105, 2026. [Patent]
  9. Bueno R, Jayender J, Lucas AD. System for a tissue resection margin measurement device. US Patent 12,527,599, 2026. [Patent]
  10. Bueno R, Jayender J, Lucas AD, Roth L, Robinson T. System and method for a tissue resection margin measurement device. US Patent 12,514,497, 2026. [Patent]

2025

  1. Feizi N, Pedrosa FC, Zhang R, Sacco D, Patel RV, Jayender J. Design and validation of a compact concentric-tube robot for percutaneous nephrolithotomy. IEEE Transactions on Medical Robotics and Bionics 7(4):1739–1754, 2025.
  2. Jayender J, Lobo S, Lucas A, Barlow J, Sadek A, Alam ZS, Mukherjee R, Schmidlin EJ, Jaklitsch MT, Sholl LM, Bueno R, Swanson SJ. Real-time margin assessment for video-assisted thoracic surgery: a pilot clinical trial. JTCVS Techniques 34:207–218, 2025.
  3. Shah B, Xu W, Bartholomew RA, Ben-Shlomo N, Zhang A, Fan G, Unadkat P, Ziaei A, Zhou H, Guenette JP, Corrales CE, Jayender J. Augmented reality for identification of temporal bone anatomy and comparison to conventional imaging. Annals of Otology, Rhinology & Laryngology 134(11):828–836, 2025.
  4. Jirarayapong J, Portnow LH, Jayender J, Kwait DC, Lan Z, Barbie TU, Mallory MA, Kim L, Golshan M, Gombos EC. Intraoperative supine breast MRI for residual tumor assessment after breast-conserving therapy in early-stage breast cancer. Radiology: Imaging Cancer 7(2):e240158, 2025.
  5. Feizi N, Pedrosa FC, Jayender J, Patel RV. Deep Koopman approach for nonlinear dynamics and control of tendon-driven continuum robots. IEEE Robotics and Automation Letters 10(3):2926–2933, 2025.
  6. Krishnamoorthy M, Zhou H, Frazee K, Pal R, Jayender J, Kumar ATN. Real-time SLAM-based correction and 3D visualization for fluorescence lifetime imaging. MICCAI 2025, LNCS 15970:488–497.
  7. Pedrosa FC, Feizi N, Sacco D, Patel RV, Jayender J. Image-guided surgical planning for percutaneous nephrolithotomy using CTRs: a phantom-based study. IEEE International Conference on Robotics and Automation (ICRA), pp. 4494–4500, 2025.
  8. Abkhofte S, Naidu AS, Patel RV, Jayender J. Deep learning-based segmentation for autonomous robot-assisted tumor localization using ultrasound B-mode and strain elastography imaging. International Symposium on Medical Robotics (ISMR), pp. 30–36, 2025.
  9. Bartholomew RA, Zhou H, Gerstl J, Boreel M, et al., Jayender J. Clinical evaluation of SLAM-based trackerless surgical navigation in the lateral skull base. Journal of Neurological Surgery Part B: Skull Base, 2025. [Abstract]
  10. Zhou H, Jayender J. System for and method of real-time nonrigid mosaicking of laparoscopy images. US Patent 12,456,162, 2025. [Patent]

2024

  1. Bartholomew RA, Zhou H, Boreel M, Suresh K, Gupta S, Mitchell MB, Hong C, Lee SE, Smith TR, Guenette JP, Corrales CE, Jayender J. Surgical navigation in the anterior skull base using 3-dimensional endoscopy and surface reconstruction. JAMA Otolaryngology–Head & Neck Surgery 150(4):318–326, 2024.
  2. Fu E, Zhou H, de la Lastra ÁA, Zhang R, Ayyala H, Broyles J, Pomahac B, Jayender J. SLAM-based breast reconstruction system for surgical guidance using a low-cost camera. IEEE Transactions on Medical Robotics and Bionics 6(4):1345–1353, 2024.
  3. Arefinia E, Jayender J, Patel RV. Machine-learning-based multi-modal force estimation for steerable ablation catheters. IEEE Transactions on Medical Robotics and Bionics 6(3):1004–1016, 2024.
  4. Pedrosa FC, Feizi N, Zhang R, Delaunay R, Sacco D, Patel RV, Jayender J. Image-guided surgical planning of percutaneous nephrolithotomy with patient-specific CTRs. International Journal of Computer Assisted Radiology and Surgery 19(5):801–810, 2024.
  5. Ben-Shlomo N, Rahimi A, Abunimer AM, Guenette JP, Juliano AF, Starr JR, Jayender J, Corrales CE. Inner ear breaches from vestibular schwannoma surgery: revisiting the incidence of otologic injury from retrosigmoid and middle cranial fossa approaches. Otology & Neurotology 45(3):311–318, 2024.
  6. Delaunay R, Zhang R, Pedrosa FC, Feizi N, et al., Jayender J. Transformer-based local feature matching for multimodal image registration. SPIE Medical Imaging 2024: Image Processing, vol. 12926.
  7. Wang J, Zhou H, Boretto L, Regensburger A, et al., Jayender J. Integration of stereo laparoscopy-based surface reconstruction and ultrasound volume rendering for real-time navigated liver surgery. Gastroenterology 166(5):S-1886, 2024 (SSAT/DDW). [Abstract]
  8. Boreel M, Suresh K, Guenette J, Jayender J, et al.. Quantitative measurements for trigeminal nerve tethering secondary to cystic degeneration of vestibular schwannoma. Journal of Neurological Surgery Part B: Skull Base, 2024. [Abstract]
  9. Jayender J, Zhou H. System and methods for a trackerless navigation system. US Patent 11,890,063, 2024. [Patent]

2023

  1. DeBuys C, Ghesu FC, Jayender J, Langari R, Kim YH. Separable tendon-driven robotic manipulator with a long, flexible, passive proximal section. Journal of Mechanisms and Robotics 15(6):061019, 2023.
  2. Ben-Shlomo N, Jayender J, Guenette JP, Corrales CE. Iatrogenic inner ear dehiscence associated with lateral skull base surgery: a systematic analysis of drilling injuries and their causal factors. Acta Neurochirurgica 165(10):2969–2977, 2023.
  3. Salehizadeh M, Pedrosa F, Bassan H, Patel R, et al., Jayender J. Dynamic modeling and identification of a robotic intracardiac echo catheter. IEEE International Conference on Robotics and Automation (ICRA), 2023.
  4. Pedrosa FC, Zhang R, Feizi N, Sacco DE, Patel R, Jayender J. Handheld concentric tube robot for percutaneous nephrolithotomy. 15th Hamlyn Symposium on Medical Robotics, pp. 139–140, 2023.

2022

  1. Zhou H, Jayender J. EMDQ: removal of image feature mismatches in real-time. IEEE Transactions on Image Processing 31:706–720, 2022.
  2. Pedrosa FC, Feizi N, Zhang R, Delaunay R, Sacco D, Jayender J, Patel R. On surgical planning of percutaneous nephrolithotomy with patient-specific CTRs. MICCAI 2022, LNCS 13437:626–635.
  3. Xu Z, Luo J, Lu D, Yan J, Frisken S, Jayender J, Wells WM III, Li X, Zheng Y, Tong RK. Double-uncertainty guided spatial and temporal consistency regularization weighting for learning-based abdominal registration. MICCAI 2022, pp. 14–24.
  4. Salehizadeh M, Jayender J, Razminia M, et al.. Future directions of intracardiac echocardiography (ICE). In: Intracardiac Echocardiography: A Handbook for Electrophysiologists, 2022. [Book chapter]
  5. Khan M, Pedrosa FC, Wang L, et al., Jayender J. PCNL access planning using a novel optimization algorithm. The Journal of Urology 207(Suppl 5):e726, 2022. [Abstract]
  6. Bueno R, Jayender J, Jolesz FA. System and method for a tissue resection margin measurement device. US Patent 11,246,666, 2022. [Patent]
  7. Bueno R, Jayender J, Lucas AD. System and method for a tissue resection margin measurement device. US Patent 11,234,732, 2022. [Patent]

Selected Earlier Publications

  • Jayender J, Lee TC, Ruan DT. Real-time localization of parathyroid adenoma during parathyroidectomy. New England Journal of Medicine 373(1):96–98, 2015.
  • Tempany CMC, Jayender J, Kapur T, Bueno R, Golby A, Agar N, Jolesz FA. Multimodal imaging for improved diagnosis and treatment of cancers. Cancer 121(6):817–827, 2015.
  • Gill RR, Zheng Y, Barlow JS, Jayender J, et al. Image-guided video assisted thoracoscopic surgery (iVATS): phase I–II clinical trial. Journal of Surgical Oncology 112(1):18–25, 2015.
  • Zhou H, Jayender J. Real-time dense reconstruction of tissue surface from stereo optical video. IEEE Transactions on Medical Imaging 39(2):400–412, 2019.
  • Trejos AL, Jayender J, Perri MT, Naish MD, Patel RV, Malthaner RA. Robot-assisted tactile sensing for minimally invasive tumor localization. International Journal of Robotics Research 28(9):1118–1133, 2009.
  • Jayender J, Azizian M, Patel RV. Autonomous image-guided robot-assisted active catheter insertion. IEEE Transactions on Robotics 24(4):858–871, 2008.
  • Jayender J, Patel RV, Nikumb S, Ostojic M. Modeling and control of shape memory alloy actuators. IEEE Transactions on Control Systems Technology 16(2):279–287, 2008.

Members

Lab Director

Jayender Jagadeesan

Jayender Jagadeesan, PhD

Associate Professor, Harvard Medical School · Lead Investigator, Brigham and Women's Hospital · Research Associate, Broad Institute of MIT and Harvard

Dr. Jayender Jagadeesan is an Associate Professor at Harvard Medical School and Lead Investigator at Brigham and Women's Hospital. He earned his B.Tech. in Electrical Engineering from IIT Kanpur in 2003 and his Ph.D. in Electrical and Computer Engineering from the University of Western Ontario.

His research spans robotics, medical imaging, machine learning and surgery. He develops technologies that improve the precision and effectiveness of surgical procedures, including real-time surgical navigation, image-guided intervention, and AI-based image analysis for clinical decision-making.

He has held research positions at the University of Western Ontario, Canadian Surgical Technologies and Advanced Robotics, Massachusetts General Hospital, and Brigham and Women's Hospital. He is Co-Founder of Navigation Sciences, Inc., which translates advances in medical navigation into clinical practice.

Faculty

Haoyin ZhouHaoyin Zhou, PhDAssistant Professor, Harvard Medical School

Postdoctoral Fellows

Weiming MiWeiming MiPostdoctoral Research Fellow
Mojtaba EsfandiariPostdoctoral Research Fellow

Interns

Jiahui AnJiahui AnResearch Intern
Yiming HuangResearch Intern
Guerin ChanResearch Intern

Alumni

YearsNamePosition
2025Maddi Lafarga BilbaoMaster's student
2025Avaneesh BabuUndergraduate student
2023Rishad LuthraResearch intern
2023Kush ParikhResearch intern
2022Elise FuResearch intern, INSA Lyon
2021Remi DelaunayPostdoctoral research fellow
2021Ruisi ZhangPostdoctoral research fellow
2020Navid FeiziPredoctoral and postdoctoral research scholar
2020Elaheh ArefiniaPhD student
2020Sara AbkhoftePhD student
2020Mohammad SalehizadehPostdoctoral research fellow
2020Xe ZhuMaster's student, Tsinghua University
2019Filipe PedrosaPredoctoral research scholar
2019Moiz KhanPostdoctoral research fellow
2019Angela Alarcon De La LastraMaster's student, Universidad de Navarra
2019Ritvik PulyaHigh school student, Acton-Boxborough
2018Duo WangPhD candidate, Tsinghua University
2018Lishu LuoTianjin University
2018Bijoy ShahNortheastern University
2018Nir Ben-ShlomoMedical student
2017Haoyin ZhouPostdoctoral research fellow (now Assistant Professor, HMS)
2017Ann WanxinNorthwestern University
2017Dawei WeiCarnegie Mellon University
2017Fan ZhipengNew York University
2017Adelaide GrimaudMS candidate, Arts et Métiers, France
2017Ran XuWestern University
2016Baichuan JiangTianjin University (later Johns Hopkins)
2016Brian XavierMD candidate, Boston University
2015–16Wenpeng GaoHarbin Institute of Technology
2014–15Ruth H. De Morais BoniniHospital de Câncer de Barretos, Brazil
2014Katharina BreiningerFAU Erlangen-Nürnberg
2014Ming LiHuaDong Hospital, Fudan University
2014Clara MeinzerMedical student, Semmelweis University
2013–14Sneha DurgapalUndergraduate, Boston College
2013Boya AbuduUndergraduate, Pittsburg State University
2013Rebecca GerberBrown University
2012, 2014Vivek NarayanPhD candidate, Boston University
2012Tyler BlevinsUndergraduate
2012Neha AgrawalResident
2011–12Banu MahajanResearch fellow
2009–10Madiha TahirResearch fellow

Open Positions

We are recruiting two postdoctoral research fellows. Both are full-time, two-year appointments in the Surgical Imaging and Mechatronics Lab, Department of Radiology, Brigham and Women's Hospital and Harvard Medical School.

SLAM, Neural Scene Reconstruction, and Intraoperative Guidance from Laparoscopic and Endoscopic Video

Position
Postdoctoral Research Fellow
Appointment
Full-time, two years
Start date
As soon as possible; applications reviewed on a rolling basis
Supervisor
Jayender Jagadeesan, PhD

We are seeking a highly motivated postdoctoral fellow to develop the next generation of intraoperative guidance from laparoscopic and endoscopic video. The work centers on recovering dense, deformation-aware 3D models of the surgical field in real time using SLAM, structure-from-motion, and neural scene representations such as NeRF and 3D Gaussian splatting, and registering them to preoperative CT and MRI so that critical anatomy remains visible to the surgeon throughout the procedure. The position sits at the intersection of 3D computer vision, neural rendering, deformable registration, and machine learning, with direct access to clinical data and to the operating room.

Responsibilities, qualifications and benefits

What you will work on

  • Develop real-time SLAM and structure-from-motion methods that recover camera pose and dense 3D anatomy from monocular and stereo laparoscopic and endoscopic video.
  • Build neural scene representations such as NeRF and 3D Gaussian splatting for high-fidelity, deformation-aware reconstruction of the surgical field.
  • Extend these representations to handle tissue deformation, specular reflection, smoke, instrument occlusion, and sparse or rapidly moving views.
  • Develop registration algorithms to align preoperative CT/MRI models with reconstructed intraoperative surfaces.
  • Integrate multimodal intraoperative imaging into the reconstruction and registration pipeline.
  • Optimize the pipeline for real-time performance and deploy it within 3D Slicer and the laboratory's surgical navigation platform.
  • Validate methods on phantom, ex vivo, and clinical datasets in collaboration with surgeons, and present results at MICCAI, IPCAI, CVPR, and related venues.

Who we are looking for

  • PhD completed or nearing completion in Computer Science, Biomedical Engineering, Electrical Engineering, Robotics, Applied Mathematics, or a related field.
  • Strong foundation in 3D computer vision: multi-view geometry, camera calibration, SLAM or structure-from-motion, and dense depth estimation.
  • Hands-on experience with neural rendering and novel-view synthesis (NeRF, 3D Gaussian splatting) and with deep learning frameworks such as PyTorch.
  • Proficiency in Python and C++; experience with CUDA or other GPU-accelerated pipelines is a strong plus.
  • Familiarity with medical image processing and visualization libraries (ITK, VTK, OpenCV, 3D Slicer) and with deformable registration is a plus.
  • Excellent analytical, problem-solving, and communication skills, with a track record of peer-reviewed publication appropriate to career stage.

What we offer

  • Mentorship from leading researchers in image-guided therapy, surgical navigation, and medical robotics.
  • Collaboration with industry.
  • Access to state-of-the-art computational and imaging resources.
  • Opportunities for co-authorship on publications and presentation of results at scientific meetings.
  • A collaborative research environment within the Harvard Medical School ecosystem.

Tissue Deformation Modeling and Simulation Design for Image-Guided Surgery

Position
Postdoctoral Research Fellow
Appointment
Full-time, two years
Start date
As soon as possible; applications reviewed on a rolling basis
Supervisor
Jayender Jagadeesan, PhD

We are seeking a highly motivated postdoctoral fellow to develop computational models and simulation frameworks of soft tissue deformation for image-guided and robot-assisted surgery. The fellow will design patient-specific biomechanical models and surgical simulations that predict how organs move and deform during thoracic and abdominal procedures, and use them to update preoperative imaging, generate training and validation data for learning-based algorithms, and support real-time intraoperative navigation. The position sits at the intersection of computational biomechanics, physics-based simulation, medical image computing, and machine learning.

Responsibilities, qualifications and benefits

What you will work on

  • Develop patient-specific biomechanical models of soft tissue and organs (finite element, meshless, and mass–spring formulations) built from CT, MRI, and ultrasound data.
  • Design and build surgical simulation environments that reproduce intraoperative events such as lung deflation, insufflation, patient repositioning, retraction, resection, and tool–tissue interaction.
  • Develop fast and real-time deformation methods, including reduced-order models, GPU-accelerated solvers, and physics-informed or learning-based surrogate models, suitable for use during navigation.
  • Use simulation to generate large-scale synthetic datasets for training and benchmarking deformable registration, shape completion, and motion compensation algorithms.
  • Integrate deformation models with intraoperative imaging and tracking data to update preoperative plans and compensate for tissue motion during surgery.
  • Characterize tissue mechanical properties and validate models against phantom, ex vivo, and preclinical experiments in collaboration with clinicians.

Who we are looking for

  • PhD (completed or near completion) in Mechanical Engineering, Biomedical Engineering, Computer Science, Applied Mathematics, or a related field.
  • Strong background in continuum mechanics, nonlinear finite element analysis, and computational modeling of soft tissue.
  • Proficiency in Python and C++; experience with simulation frameworks such as SOFA, FEBio, FEniCS, Abaqus, or ANSYS is a plus.
  • Familiarity with medical image processing and meshing tools (ITK, VTK, 3D Slicer, TetGen/CGAL) and deep learning frameworks (PyTorch, TensorFlow).
  • Experience with physics-informed neural networks, reduced-order modeling, GPU programming, or surgical navigation preferred.
  • Excellent analytical, problem-solving, and communication skills.
  • A track record of peer-reviewed publication appropriate to your career stage.

What we offer

  • Mentorship from leading researchers in image-guided therapy, computational modeling, and medical robotics.
  • Close collaboration with surgeons and interventionalists, and with industry partners.
  • Access to state-of-the-art computational (GPU), imaging, and experimental resources.
  • Opportunities for co-authorship on publications and presentation of results at scientific meetings.
  • A collaborative research environment within the Harvard Medical School ecosystem.

How to apply

Send a CV, three representative publications, and contact information for three references to Dr. Jayender Jagadeesan at jayender@bwh.harvard.edu. Please name the position in the subject line. Applications are reviewed on a rolling basis.

We also welcome inquiries about research intern positions; please include your CV.

Resources

AMIGO

The Advanced Multimodal Image-Guided Operating (AMIGO) suite, conceived by Drs. Ferenc Jolesz and Clare Tempany, is a set of three sterile procedure rooms (MRI, operating room, PET/CT) covering 5,700 square feet, where multidisciplinary teams treat patients using multiple imaging modalities.

AT-NCIGT

The National Center for Advanced Technologies for Image Guided Therapy at Brigham and Women's Hospital and Harvard Medical School is a Biomedical Technology Resource Center of NIBIB, led by Dr. Clare Tempany. AMIGO is its clinical translational testbed.

Contact

Jayender Jagadeesan, PhD
Surgical Imaging and Mechatronics (SIM) Lab
Brigham and Women's Hospital
Radiology Building, 1st Floor, Room 126 (RA-126)
20 Shattuck Street, Boston, MA 02115

Email

jayender@bwh.harvard.edu