BIOGRAPHY
Hi👋 I'm Senthil Palanivelu, a graduate with a background in Computer Science from University of Massachusetts Boston.
Healthcare AI Specialist passionate about transforming patient care through data science and machine learning.
With 6+ years of experience across enterprise systems, research infrastructure, and clinical applications, I bridge the gap between cutting-edge technology and real-world healthcare impact.
At leading institutions like MGH, BWH, and Boston University, I've led projects that directly improve patient outcomes - from reducing sleep study analysis time by 90% to developing brain age prediction models that provide new clinical biomarkers.
What drives me: Taking complex biomedical data and creating solutions that clinicians can actually use.
Technical expertise: Python, R, AWS, Docker, machine learning, deep learning, medical imaging, EEG/fMRI analysis, and full-stack development.
Looking to collaborate with teams pushing the boundaries of healthcare AI, precision medicine, and clinical decision support systems.
Experience
Full Stack Developer/Frontend Engineer @Amudham Naturals
Jul 2025 - Present | India- Architected a high-performance e-commerce platform for a premium organic food brand, delivering a seamless shopping experience through modern web technologies and secure payment integration
- Built a high-performance e-commerce SPA using Next.js 15 (App Router), React 19, and TypeScript, achieving sub-second load times with Static Site Generation and strict typing
- Designed a modern, animated UI/UX with Tailwind CSS 4.0 and Framer Motion, implementing infinite-scroll product carousels, smooth multi-step checkout, and persistent cart state using Zustand with custom GST (5%) logic
Bioinformatician I @Brigham and Women's Hospital
Sep 2022 - Dec 2024 | United States- Led data harmonization projects across multiple research cohorts, standardizing EMG, ECG, and EEG configurations for 1000+ participants from diverse clinical sites
- Developed and deployed machine learning models for automated sleep staging and brain age prediction using ensemble methods (Random Forest, XGBoost, LightGBM)
- Created web-based interactive EDF viewer application capturing real-time user inputs and integrating with backend ML models for clinical decision support
- Built and deployed R Shiny applications on AWS EC2 using ShinyProxy and Docker containers, serving 50+ clinical researchers and sleep medicine practitioners
- Implemented CI/CD pipelines using GitHub Actions for automated Python package building and PyPI distribution across multiple platforms
- Conducted comprehensive statistical analysis of SpO2 levels during sleep across 1000 individuals, identifying respiratory health patterns and risk factors
- Designed reproducible HTML workflows with accompanying scripts, enabling audit trails and replication for regulatory compliance and scientific transparency
- Optimized computing infrastructure including cloud storage and compute environments, reducing analysis time from days to hours for large sleep datasets
- Created automated job scheduling scripts for high-throughput analysis of polysomnography data, processing 100+ sleep studies per week
Research Associate - Research Math @Nationwide Children's Hospital
Sep 2021 - Jul 2022 | United States- Developed MATLAB programs for processing human sleep EEG data, creating automated analysis pipelines for large-scale sleep studies
- Implemented Mölle2011 spindle detection algorithm and custom slow oscillation detection methods, enabling high-throughput sleep pattern analysis
- Applied multi-taper spectral analysis to study neurophysiology of sleep, contributing to understanding of memory consolidation mechanisms
- Utilized K-means clustering to categorize spatial patterns of slow oscillations (global, local, frontal), revealing novel sleep architecture insights
- Analyzed sleep brain dynamics in neurodevelopmental populations, supporting clinical research into developmental sleep disorders
- Implemented Support Vector Machine (SVM) classification for slow oscillations based on source current densities, achieving 87% classification accuracy
- Conducted topographic analysis of sleep EEG data, identifying biomarkers for healthy brain development and neurodevelopmental challenges
Research Data Analyst I @Boston University
Apr 2020 - Aug 2021 | United States- Implemented statistical analysis pipelines in Python for multimodal neuroimaging data fusion (EEG, fMRI, behavioral), supporting translational neuroscience research
- Performed brain source analysis using beamforming techniques and advanced signal processing methods for EEG/MEG data interpretation
- Built predictive machine learning models on large, high-dimensional neuroscience datasets to identify biomarkers for cognitive and clinical outcomes
- Developed graph theoretical analysis frameworks for brain network connectivity, revealing novel insights into neural communication patterns
- Implemented time-frequency analysis, circular statistics, and non-parametric cluster-based statistics for complex neurophysiological data
- Provided software development support for MNE-Python based platforms, including testing, debugging, and feature enhancement
- Managed and organized multi-modal datasets from translational studies encompassing physiological, neuroimaging, clinical, and behavioral measurements
Clinical Research Coordinator II @Massachusetts General Hospital
Jan 2019 - Mar 2020 | United States- Part of Center for Computational Imaging Anatomy at Massachusetts General Hospital and Psychiatry Neuroimaging Laboratory at Brigham and Women's Hospital
- Developed and trained encoder-decoder deep learning models for diffusion brain MRI segmentation, achieving 95% accuracy on clinical datasets
- Deployed production machine learning models on AWS EC2 infrastructure, serving real-time predictions for clinical research applications
- Analyzed fiber track data from diffusion MR tractography to map brain connectivity patterns in mental health research studies
- Coordinated technical aspects of multi-site clinical studies involving 200+ participants across neuroimaging, clinical, and behavioral data streams
- Built Python-based image processing pipelines for multimodal neuroimaging analysis including resting-state and task-based fMRI
- Utilized professional neuroimaging tools (3D Slicer, FreeSurfer, FSL, SPM) for volumetric brain analysis and preprocessing workflows
- Organized and standardized large datasets from diverse research sites, ensuring data quality and regulatory compliance
Research Assistant @University of Massachusetts Boston
Jul 2016 - Aug 2017 | United States- Developed computational pipelines in Python and UNIX shell scripting, automating research workflows for 200+ faculty across multiple departments
- Optimized C code for parallel computing environments, achieving 40% performance improvements on high-performance computing clusters
- Maintained distributed resource management systems (Son of Grid Engine, SLURM) supporting petabyte-scale storage and thousands of compute cores
- Implemented custom Ganglia Python metric modules and configured Nagios monitoring systems, reducing system downtime by 85%
- Configured DMTCP checkpoint/restart functionality, preventing loss of weeks-long computational jobs during system maintenance
- Managed data center operations including CentOS installation, Linux clustering, and enterprise storage systems
- Provided technical support for scientific applications including Schrödinger software configuration and remote job submission setup
IT Assistant @William Joiner Institute
Sep 2015 - May 2016 | United States- Managed institute website using HTML and Expression Engine CMS, ensuring content accuracy and user accessibility for academic research dissemination
- Designed marketing materials including posters, brochures, and flyers using Adobe Creative Suite (InDesign, Photoshop, Illustrator) and Microsoft Publisher
- Coordinated and organized institutional events with cross-functional staff teams, supporting academic conferences and community outreach initiatives
- Maintained web content management workflows and updated digital resources to support research publication and public engagement efforts
IT Specialist @Mphasis
Oct 2012 - Feb 2014 | India- Managed backup and restore operations for 100+ global clients using HP Storage Services Management System (SSMS), ensuring 99.9% data availability and business continuity
- Administered cross-platform Unix systems (Linux, Solaris, HP-UX) including OS hardening, performance tuning, and security configuration management
- Developed SQL Server 2005 and PL/SQL database solutions for business intelligence reporting and automated billing processes for backup services division
- Implemented EMC Data Protection Advisor across enterprise environments, reducing backup failure detection time by 75% through proactive monitoring
- Diagnosed and resolved complex network connectivity and firewall issues between client servers and data protection infrastructure, maintaining 24/7 service availability
- Created Unix shell scripts for automated failure data collection and analysis, improving incident response time by 60%
- Configured Access Control Lists (ACLs) and file-level security settings across multiple platforms, ensuring compliance with enterprise security standards