I'm
V A Sairam
Turning complex AI into real-world impact — from hospital diagnostics to business automation.
I'm
Turning complex AI into real-world impact — from hospital diagnostics to business automation.
About
With a strong academic foundation spanning Artificial Intelligence, Machine Learning, and Biomedical Engineering, I work at the intersection of healthcare domain expertise and applied AI systems. My experience involves designing, developing, and scaling AI solutions in medical imaging, multimodal healthcare analysis, and predictive maintenance.
I currently serve as a Machine Learning Engineer at CurieDx, a healthcare startup in the United States, where I'm involved in early-stage R&D as well as production-level system development. Alongside this, I work as an AI Consultant for Microheal Wellness Pvt. Ltd., building multimodal AI pipelines for healthcare diagnostics using Vision-Language Models.
As an independent researcher and freelancer, I support PhD scholars and startups in building robust AI pipelines — from cardiac MRI segmentation to Alzheimer's diagnosis to predictive maintenance of industrial systems. I also help businesses automate their operations through intelligent data entry systems, automated quotation generation, and AI-driven workflow optimization.
I've authored 5 open-source Python frameworks on PyPI, published a Udemy course on data science, and have 30+ research publications with international collaborators across France, UK, and India. I hold 2 patents in predictive maintenance and have been cited on Google Scholar.
Based in Chennai, I'm available for speaking engagements, workshops, guest lectures, hackathon judging, AI consulting, and research collaborations.
Tech Stack
What I Do
End-to-end ML systems for healthcare diagnostics — from multi-site data ingestion to model deployment. Building multi-modal diagnostic pipelines combining imaging, symptom data, and audio signals for clinical decision support.
Object detection, image segmentation, and multimodal image classification for clinical applications. Training and deploying computer vision models on real medical imaging data across hospital networks.
Designing clinical reasoning frameworks for medical LLMs. Systematic prompt engineering on models like MedGemma for diagnostic classification, plus GenAI R&D for healthcare and business applications.
Building classifiers that detect disease conditions from audio signals. Ensemble models using focal loss and domain-adapted pretraining for production-grade diagnostic performance.
Partnering with businesses to understand their operations and automate workflows end-to-end. Building intelligent data entry systems, automated quotation generation for supply chains, and custom automation pipelines that convert manual processes into revenue-generating machines.
My Resume
Publications
30+ peer-reviewed publications across SAGE, CMC, IEEE, and international conferences. Full list on Google Scholar.
Development of deep learning algorithms for segmentation, classification and quantification of polyps using colonoscopy images.
Deep learning algorithm for automated diagnosis of gastrointestinal abnormalities from capsule endoscopy images.
A machine learning predictive model for ureteroscopy lasertripsy outcomes, developed in collaboration with University of Southampton NHS and Newcastle.
A multimodal approach combining electronic nose sensor data and thermal imaging for gas detection and classification using SRGAN and sparse autoencoder deep learning methods.
Integrated diagnostic system for diabetes using deep learning across fundus imaging, thermal imaging, dermal imaging and OCT modalities.
Integrated system for breast cancer diagnosis, confirmation and follow-up analysis using deep learning and medical imaging modalities.
Comprehensive book covering the history, pathology and modern developments in knee osteoarthritis diagnosis and treatment.
Projects
Beyond industry work, I build open-source tools and contribute to the AI + biomedical community.
100+ image features extraction
Automated clustering (supervised + unsupervised)
Automated data cleaning
ML experiment logging & visualization
Audio preprocessing & feature extraction
Achievements
Recognized as Award-Winning AI/ML Expert by Topmate, featured on a billboard at Times Square, New York City.
Highest CGPA (9.16) in the entire M.Tech AI & ML batch, Symbiosis Institute of Technology.
Collaborated with Newcastle University and University of Southampton on ML predictive models for clinical healthcare.
Won first place and ₹10K at Socio Hackathon by IIT Bombay & YourEngineer.
Co-inventor: "System and Method for Predicting Water Pump RUL and Machine Health Status Using AI."
Published across SAGE, CMC, IEEE, and international conferences with collaborators from UK, France, India.
Python frameworks for image extraction, clustering, data cleaning, ML logging, and audio processing.
Research at Avignon Université on multimodal brain tumor diagnosis using MRI.
Published "Data Cleaning and Visualization in Python" on Udemy.
Topped among 2,000+ students nationally.
National 36-hour hackathon. Built DL system for medical waste segregation.
Won IPC-2022 inter-college competition for autism detection software.
Departmental honor for 5 research projects, publications, and 3 workshops.
Recognized for publishing Python modules on PyPI.
Gallery
Testimonials
Open to: Speaking · Guest lectures · Hackathon judging · Workshops · AI consulting · Research collaborations
