Ahmed Tahseen Minhaz, PhD

About

I am a biomedical engineer and AI researcher. I am currently a Senior AI Engineer at Quantivly Inc., where I develop AI methods for radiology operations. Previously, I was an AI Engineer and subsequently an AI Scientist at Philips Image Guided Therapy Devices, where I worked on AI for intravascular ultrasound, and a Postdoctoral Research Fellow at Cleveland Clinic, where I worked on accelerated quantitative MRI of the knee.

I received my PhD in Biomedical Engineering from Case Western Reserve University under the supervision of Prof. David L. Wilson. My dissertation, 3D Ultrasound Imaging of the Eye, encompassed the design of 3D ultrasound imaging systems for the anterior segment and the whole eye, together with deep learning methods for image enhancement, segmentation and volumetric assessment.

Research interests Medical image analysis Image enhancement Segmentation Quantitative MRI 3D ultrasound Generative models Clinical translation of AI

Experience

1. Oct 2026 – present

   Senior AI Engineer

   Quantivly Inc., Somerville, MA

   Development of AI methods for radiology operations.

2. Aug 2026 – Oct 2026

   AI Scientist

   Philips, Innovation & Design, Cambridge, MA

3. Jun 2025 – Aug 2026

   AI Engineer

   Philips Image Guided Therapy Devices, Plymouth, MN

   Data readiness, validation and regulatory compliance for AI-enabled intravascular ultrasound (IVUS) products, as part of the algorithm development team.

4. Aug 2024 – Jun 2025

   Postdoctoral Research Fellow

   Program of Advanced Musculoskeletal Imaging, Lerner Research Institute, Cleveland Clinic

   Deep learning for segmentation, image enhancement and radiomics in musculoskeletal and neuroimaging; accelerated whole-knee T1ρ and T2 mapping with automated analysis. Supervisors: Dr. Xiaojuan Li and Dr. Kunio Nakamura.

5. Aug 2018 – May 2024

   Graduate Research Assistant

   Department of Biomedical Engineering, Case Western Reserve University

   Development of 3D ultrasound biomicroscopy and whole-eye 3D ultrasound systems; GAN-based deconvolution of depth-dependent blur (SDV-GAN); deep learning segmentation and volumetric assessment of the ciliary body; deep learning for non-contrast ultrasound microvessel imaging. Supervisor: Prof. David L. Wilson.

6. Dec 2016 – Feb 2018

   Computer Vision Researcher

   Semion, Dhaka, Bangladesh

   Deep learning methods for abnormality detection and localization in chest radiographs.

Publications

A complete and current list is available on Google Scholar.

Journal articles

• 2025

  Improved biometric quantification in 3D ultrasound biomicroscopy via generative adversarial networks-based image enhancement

  Journal of Imaging Informatics in Medicine

  DOIPDF

• 2024

  Assessment of intraocular foreign body using high resolution 3D ultrasound imaging

  Scientific Reports

  DOI

• 2022

  Deep learning segmentation, visualization, and automated 3D assessment of ciliary body in 3D ultrasound biomicroscopy images

  Translational Vision Science & Technology

  DOI

• 2021

  Clinical 3D imaging of the anterior segment with ultrasound biomicroscopy

  Translational Vision Science & Technology

  DOI

Conference papers

• 2024

  Assessment of ocular injuries using high-resolution 3D ultrasound

  SPIE Medical Imaging

  DOI

• 2022

  Deep learning segmentation of ciliary tissues using 3D ultrasound biomicroscopy (3D-UBM) images

  SPIE Medical Imaging

  DOI

• 2022

  End-to-end deep learning for tuning-free non-contrast ultrasound microvessel imaging

  IEEE International Ultrasonics Symposium (IUS)

  DOIPDFSlides

• 2021

  Deconvolution of ultrasound biomicroscopy images using generative adversarial networks to visualize and evaluate localization of ocular structures

  SPIE Medical Imaging

  DOI

• 2020

  3D ultrasound biomicroscopy (3D-UBM) imaging of the eye for unique 3D assessment of ciliary body

  SPIE Medical Imaging

  DOI

• 2020

  Deconvolution and improved visualization of ocular structures in UBM using deep learning

  IEEE International Ultrasonics Symposium (IUS)

  DOI

• 2019

  3D ultrasound biomicroscopy (3D-UBM) imaging and automated 3D assessment of the iridocorneal angle for glaucoma patients

  SPIE Medical Imaging

  DOI

• 2017

  Audio-visual emotion recognition using cross correlation and wavelet packet domain features

  IEEE WIECON-ECE

  DOI

• 2017

  Enhancement of noisy speech based on decision-directed Wiener approach in perceptual wavelet packet domain

  IEEE TENCON

  DOI

• 2016

  Sub-frame based apnea detection exploiting delta band power ratio extracted from EEG signals

  IEEE TENCON

  DOI

Abstracts & preprints

• 2025

  Clinically feasible whole-knee MR T1ρ and T2 mapping in under 3 minutes with accelerated imaging and automated analysis

  ISMRM Annual Meeting · digital poster

• 2017

  Abnormality detection and localization in chest X-rays using deep convolutional neural networks

  arXiv preprint

  arXiv

Patent

• 2021

  Processing three-dimensional (3D) ultrasound images

  US Patent Application 2021/0383548 A1

Education

1. 2018 – 2024

   PhD, Biomedical Engineering

   Case Western Reserve University, Cleveland, OH

   Dissertation: 3D Ultrasound Imaging of the Eye

2. 2016 – 2018

   MS, Electrical and Electronic Engineering

   Bangladesh University of Engineering and Technology (BUET)

3. – 2016

   BS, Electrical and Electronic Engineering

   Bangladesh University of Engineering and Technology (BUET)

Service and Memberships

• Founding President, Bangladeshi Students Association, Case Western Reserve University (2019–2021)
• Member, IEEE (since 2016); Member, SPIE

Contact

Email: tahseenminhaz92@gmail.com