A Bit About Me
I’m Dhawal Wazalwar — a healthcare AI and medical imaging professional with over 13 years of experience building clinical-grade deep learning workflows.
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My journey began in radiology imaging, where I developed AI algorithms to assist clinicians in diagnosing and treating complex conditions using CT and MRI data. Over the years, I’ve led product-focused AI initiatives at companies like TeraRecon and Noah Medical, contributing to FDA-cleared systems and globally deployed imaging platforms.
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What drives me is the intersection of technology, clinical relevance, and real-world deployment. I’m passionate about building AI that not only performs well in research, but also integrates seamlessly into clinical workflows and meets regulatory standards.
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My recent work includes:
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Integrating segmentation and planning modules in a robotic bronchoscopy platform
- Developing cardiac MRI segmentation algorithms for use in both SDKs and zero-click clinical viewers
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Designing FDA-aligned validation workflows and test automation frameworks
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If you’d like to learn more about my work, you can download my Resume or connect on LinkedIn.
📧 Reach me at: dwhealthai@gmail.com​​​​
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Work Experience
May 2025 - Current
Nov 2021 - April 2025
Mar 2012 - Nov 2021
July 2007 - Feb 2009
Independent GST-Registered Healthcare AI Consultant
Hyderabad​
Work with healthcare teams, hospitals, and MedTech companies to build clinically integrated, regulation-ready AI solutions.
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Design and advise on imaging AI pipelines (e.g., segmentation, inference, post-processing) with focus on deployment readiness
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Support regulatory-aligned workflows including validation planning, documentation, and compliance for FDA 510(k) or CE-marked devices​
Sr. Engineer,
Noah Medical – San Francisco / Hyderabad​
Led segmentation module development for an FDA-cleared robotic bronchoscopy system
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Integrated AI segmentation models and built supporting components for airway analysis, inference handling, and treatment planning within clinical navigation workflows
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Led validation and documentation activities aligned with FDA 510(k) requirements, supporting regulatory submission and compliance
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Managed end-to-end CT and Fluoro dataset workflows, including AI-assisted annotation and DICOM anonymization using open-source tools like ITK-SNAP and 3D Slicer
Technical Lead → Sr. Software Engineer → Software Engineer,
TeraRecon Inc – San Francisco​​
Progressively led algorithm development for CT/MRI clinical AI products in a fast-paced imaging innovation environment.
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Built AI workflows including cardiac MRI segmentation pipelines and thoracic CT tools
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Delivered both SDK-based and viewer-integrated AI solutions used in production
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Contributed to validation protocols and FDA submission documentation
Physical Design Engineer,
Sankalp Semiconductors Pvt Ltd– Hubli, India​​
Worked on full-chip and IO layout design for high-speed interfaces (e.g., D-PHY MIPI, DDR2) in 180nm and 45nm nodes. Contributed to layout automation using tools like Power Plot and pattern generators.
Education
Jan 2010 - Dec 2011
Sep 2003 - June 2007
M.S. in Electrical Engineering
Illinois Institute of Technology, Chicago, USA​
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Completed thesis: License Plate Recognition in Complex Scenes under Dr. Erdal Oruklu and Dr. Jafar Saniie
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Worked on image enhancement, segmentation, morphological processing, and character recognition using neural networks​
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Published research in Journal of Transportation Technologies: “A Design Flow for Robust License Plate Localization and Recognition in Complex Scenes”
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​Coursework:
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Computer Vision & Image Processing, Statistical Pattern Recognition, Digital Signal Processing, VLSI for Signal Processing, High-Speed Arithmetic, SoC Design, Signal Compression, Random Signal Analysis
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B.E. in Electronics & Telecommunication
SRTM University, Nanded, India​
Completed coursework in digital systems, signal processing, and semiconductor fundamentals.
Certifications
April 2025 - June 2025
Jan 2025 - June 2025
October 2024
AI for Healthcare
Udacity Nanodegree​​
Completed a comprehensive, project-based program focused on real-world AI applications in clinical settings.
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Refined prior imaging skills in 2D/3D segmentation, DICOM handling, and model validation
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Gained hands-on experience in EHR modeling, wearable signal processing, and bias/uncertainty analysis​
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Covered topics including:
• Imaging AI (U-Net, PyTorch, transfer learning)
• EHR data workflows (TensorFlow, SHAP, Aequitas)
• Signal processing (ECG, PPG, Pan-Tompkins algorithm)
• Regulatory context (HIPAA, FDA 510(k), clinical integration)
Deep Learning Specialization
Coursera (Andrew Ng)​
Completed a foundational series covering the mathematics, architecture, and real-world implementation of deep learning models.
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Built and trained neural networks from scratch using NumPy and TensorFlow
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Gained practical skills in backpropagation, hyperparameter tuning, optimization, and regularization
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Developed models for image classification, sequence modeling, and machine translation
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Covered CNNs, RNNs, LSTMs, word embeddings, and attention mechanisms​
Transformer-Based NLP for Healthcare
NVIDIA Workshop, Mumbai​
Instructor-led workshop on building and deploying NLP models.
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Built Transformer models from scratch in PyTorch
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Developed a BERT-based NER application for clinical text extraction
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Deployed models using ONNX and TensorRT with Triton Inference Server
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