SP

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. My work spans automated sleep staging algorithms serving clinical labs, deep learning models for medical image segmentation, and comprehensive data harmonization across multi-site research studies.

What drives me: Taking complex biomedical data and creating solutions that clinicians can actually use. I've learned that the best healthcare AI isn't just technically sophisticated - it's reliable, interpretable, and seamlessly integrated into clinical workflows.

Technical expertise: Python, R, AWS, Docker, machine learning, deep learning, medical imaging, EEG/fMRI analysis, and full-stack development. But more importantly, I understand how to deploy these technologies in regulated healthcare environments where reliability and patient safety are paramount.

Looking to collaborate with teams pushing the boundaries of healthcare AI, precision medicine, and clinical decision support systems.

Senthil Palanivelu

Skills

💡
Python
scikit-learn
CI/CD
MATLAB
Linux
Docker
R
SQL
PyTorch
Pandas
Numpy
Data Engineering
AWS
Jupyter Lab
C++
R Shiny
Data visualization
GitHub actions
matplotlib
Excel
Optimization
Classification
Feature selection/engineering
Neural networks
Clustering
Regression
Statistical modeling
Computer vision
Bayesian statistics
Signal Processing
Predictive modelling
Data analysis
Data science
Shell scripting
GitHub/Version control
HTML & CSS
Containerization
VS code
Software development
Machine Learning
Time series analysis
Algorithms development
GitHub Copilot
AI agents
OpenAI
Prompt Engineering
RAG
Finetuning
LLM

Experience

  • 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

Education

  • Master of Science in Computer Science

    Jan 2015 - Jan 2019 | University of Massachusetts Boston
    • Courses: Advanced Algorithms, Algorithms in Bioinformatics, Analysis of Algorithm, Big Data Analytics, Linear Algebra, Calculus, Software Development and Design, Database Management, Computing Data Structure, Mathematical Logic

  • Certifications

    • July 2024 | Mathematics for Machine Learning and Data Science by DeepLearning.AI on Coursera
      • A comprehensive course covering fundamental mathematics toolkit of machine learning: calculus, linear algebra, statistics, and probability.
        • View Certificate

    • February 2025 | Google Prompting Essentials by Google on Coursera
      • AI agent design, Multimodal prompting, Prompt chaining, Prompt Design, Prompt evaluation and iteration, Responsible AI.
        • View Certificate