About Me

I am a passionate data scientist who believes in data-driven decision making and empowering executives with actionable facts. I focus on bridging the gap between data science and data engineering, utilizing modern design patterns for cloud-based and containerized workflows to maximize data science impact. I currently work for CBS Interactive in the Applied Machine Learning Group

News

Mar 2020 I will be presenting "Deploying Machine Learning Models with Flask and Docker" at PyTennessee 2020
Oct 2019 I attended ODSC West 2019 in San Francisco, California
Apr 2019 I was promoted to Lead Machine Learning Engineer in the Applied Machine Learning Group within CBS Interactive
Apr 2019 I presented "A Glimpse into CBS Interactive's AI/ML Group" at Google Next 2019 in San Francisco, California Available on YouTube
Aug 2018 I presented "Serverless Streaming Web Analytics with AWS Kinesis and Lambda" at the Nashville Analytics Summit and Nashville AWS users group meetup
Jul 2018 I was promoted to Senior Machine Learning Engineer in the Applied Machine Learning Group within CBS Interactive.
Mar 2018 I presented "Building a Serverless Recommendation Engine" at the Brentwood Artificial Intelligence meetup discussing how to use AWS Lambda and PySpark on AWS ElasticMapReduce using collaborative filtering to generate personalized recommendations for millions of users for just a few dollars.
Feb 2018 I attended PyTennessee 2018 in Nashville, Tennessee
Nov 2017 I attended AWS re:Invent 2017 in Las Vegas, Nevada
Jul 2017 I presented my work integrating our custom analytics with Splunk into our chatbot for on-demand analytics queries by our publishers at the Splunk Nashville Users Group.
Apr 2017 I began working at 247Sports.com at CBS Interactive
Mar 2017 I successfully defended my PhD in Electrical Engineering from Vanderbilt Univeristy entitled "Optic Nerve Characterization using Magnetic Resonance Imaging: The Search for Biomarkers" under the supervision of Dr. Bennett Landman (Electrical Engineering) and Dr. Seth Smith (Radiology and Biomedical Engineering).
Feb 2017 I attended SPIE Medical Imaging in Orlando, FL

Work Experience

Apr 2019 - Present CBS Interactive - Applied ML Group, Lead Machine Learning Engineer
  • Lead a team of machine learning engineers working on recommendations and video processing

  • Spearhead new ML product opportunities including HLS live-stream processing and deep personalization of CBS All Access utilizing Django Rest Framework to rapidly iterate on self-documenting PoCs.

  • Work with brands to define recommendation products and integrations

  • Promote ops best practices including helm chart authoring, owning of prometheus/grafana monitoring infrastructure and management of 6 production Kubernetes clusters running dozens of microservices.

Jul 2018 - Mar 2019 CBS Interactive - Applied ML Group, Senior Machine Learning Engineer
  • Search and recommendations product lead: algorithm development, deployment and monitoring for multiple brands including CNET, TV Guide, Metacritic, CBS Sports and CBS All Access

  • Created scalable deep learning based content-to-content recommendations platform utilizing a distributed celery queue to rapidly ingest and recommend content

  • Designed serverless ALS collaborative filtering recommendations platform using Google Cloud Dataproc which went on to be the most clicked-on carousel on the CBS All Access homepage

  • Created highly available and scalable generic recommendation selection and serving API run on Kubernetes serving 1 million recommendations per day

  • Lead policy implementations surrounding monitoring, alerting, CI/CD, testing, Git, Jira workflow and Kanban migration

Apr 2017 - Jul 2018 CBS Interactive - 247Sports.com, Data Engineer
  • Seamlessly moved analytics from custom PHP+MySQL application to AWS Kinesis streaming while maintaining business reporting

  • Worked on multiple AWS Lambda backend services to power real-time updates to the site based on streaming analytics

  • Created serverless personalized recommendation engine using PySpark to get recommendations for >2 million users for a few dollars

  • Created machine learning spam detection algorithm using Naive Bayes TF-IDF classifier, deployed to production

  • Created a serverless sessionization pipeline using AWS Lambda and AWS Elasticache (redis) to meet business needs of reporting session-level traffic metrics

  • Created custom serverless ETL pipeline of production data from application tables into BigQuery for analysis

Skills

Languages

Python, Bash, terraform, SQL

Frameworks

Django, NumPy, Pandas, matplotlib, scikit-learn, Celery, Flask, TensorFlow, PySpark

Technologies

Kubernetes, Containerization, Google Cloud, microservice architecture, redis, prometheus, grafana, rabbitmq

ML Topics

NLP, image segmentation, classification, collaborative filtering

Education

Aug 2013 - Mar 2017 Ph.D. in Electrical Engineering
Vanderbilt University
Aug 2011 - May 2013 Master's in Business Administration
The University of Tennessee at Martin
Aug 2007 - Feb 2011 B.S. in Imaging Science
Rochester Institute of Technology

Honors & Awards

2014 - 2017 NEI T32 Training Grant Award
2015 ISMRM Trainee Educational Stipend Award Winner
2012 and 2013 UT Martin Faculty Scholar
2011 RIT Outstanding Undergraduate Scholar Nominee
2010 - 2011 RIT Academic Achievement Scholarship

Speaking Engagements

Apr 2019 A Glimpse into CBS Interactive's AI/ML Group Google Next '19
Aug 2018 Serverless Streaming Web Analytics with AWS Kinesis and Lambda Nashville Analytics Summit
Aug 2018 Serverless Streaming Web Analytics with AWS Kinesis and Lambda Nashville AWS Meetup
Mar 2018 Building a Serverless Recommendation Engine Brentwood AI Meetup
Apr 2017 On-demand analytics for publishers using a splunk powered chatbot Nashville Splunk User Group

Teaching Experience

Fall 2015 Vanderbilt University (VU Athletics), Tutor
Spring 2014 Digital Signal Processing (EECE256), TA
Spring 2013 Image Processing (EECE253), TA
Spring 2008 - Spring 2011 RIT Academic Support Center (Drop in calculus and physics tutoring), Lead Tutor

All Publications

Google Scholar

Journal Articles

Synthetic Atlases Improve Segmentation Consistency between T1-Weighted Imaging Sequences
A. Plassard, S. Rane, P. D'Haese, S. Pallavaram, D. Claassen, B. Dawant, R. Harrigan, and B. Landman
Magnetic Resonance Imaging under review
[J1]
Assessment of Orbital Computed Tomography (CT) Imaging Biomarkers in Patients with Thyroid Eye Disease
S. Chaganti, K. Mundy, M. DeLisi, K. Nelson, R. Harrigan, R. Galloway, B. Landman, and L. Mawn
Journal of Digital Imaging 2019
[J2]
Imaging biomarkers in thyroid eye disease and their clinical associations
S. Chaganti, K. Nelson, K. Mundy, R. Harrigan, R. Galloway, L. Mawn, and B. Landman
Journal of Medical Imaging 2018
[J3]
Robust Multicontrast MRI Spleen Segmentation for Splenomegaly Using Multi-Atlas Segmentation
Y. Huo, J. Liu, Z. Xu, R. Harrigan, A. Assad, R. Abramson, and B. Landman
IEEE TBE 2018
[J4]
Quantitative characterization of optic nerve atrophy in patients with multiple sclerosis
R. Harrigan, A. Smith, B. Lyttle, B. Box, B. Landman, F. Bagnato, S. Pawate, and S. Smith
MSJ-ETC 2017
[J5]
Estimated Incidence of Ophthalmic Conditions Associated with Optic Nerve Disease in Middle Tennessee
S. Chaganti, K. Nelson, R. Harrigan, K. Nabar, N. Nandakumar, T. Goecks, S. Smith, B. Landman, and L. Mawn
arXiv 2017
[J6]
Disambiguating the optic nerve from the surrounding cerebrospinal fluid: Application to MS-related atrophy
R. Harrigan, A. Plassard, F. Bryan, G. Caires, L. Mawn, L. Dethrage, S. Pawate, R. Galloway, S. Smith, and B. Landman
ISMRM 2016
[J7]
Automatic Measurement of Optic Nerve Atrophy in Multiple Sclerosis Patients with and without Optic Neuritis in MRI (P3. 013)
R. Harrigan, B. Landman, L. Mawn, S. Pawate, and S. Smith
AAN 2016
[J8]
Vanderbilt University Institute of Imaging Science Center for Computational Imaging XNAT: A multimodal data archive and processing environment
R. Harrigan, B. Yvernault, B. Boyd, S. Damon, K. Gibney, B. Conrad, N. Phillips, B. Rogers, Y. Gao, and B. Landman
Neuroimage 2016
[J9]
Robust optic nerve segmentation on clinically acquired computed tomography
R. Harrigan, S. Panda, A. Asman, K. Nelson, S. Chaganti, M. DeLisi, B. Yvernault, S. Smith, R. Galloway, and L. Mawn
SPIE MI 2014
[J10]

Conference Proceedings

Improved automatic optic nerve radius estimation from high resolution MRI
R. Harrigan, A. Smith, L. Mawn, S. Smith, and B. Landman
Orlando, Florida 2017
[C1]
Multi-atlas segmentation enables robust multi-contrast MRI spleen segmentation for splenomegaly
Y. Huo, J. Liu, Z. Xu, R. Harrigan, A. Assad, R. Abramson, and B. Landman
Orlando, Florida 2017
[C2]
Effects of b-value and number of gradient directions on diffusion MRI measures obtained with Q-ball imaging
K. Schilling, V. Nath, J. Blaber, R. Harrigan, Z. Ding, A. Anderson, and B. Landman
Orlando, Florida 2017
[C3]
Short term reproducibility of a high contrast 3-D isotropic optic nerve imaging sequence in healthy controls
R. Harrigan, A. Smith, L. Mawn, S. Smith, and B. Landman
San Diego, California 2016
[C4]
Structural functional associations of the orbit in thyroid eye disease: Kalman filters to track extraocular rectal muscles
S. Chaganti, K. Nelson, K. Mundy, Y. Luo, R. Harrigan, S. Damon, D. Fabbri, L. Mawn, and B. Landman
San Diego, California 2016
[C5]
On the fallacy of quantitative segmentation for T1-weighted MRI
A. Plassard, R. Harrigan, A. Newton, S. Rane, S. Pallavaram, P. D'Haese, B. Dawant, D. Claassen, and B. Landman
San Diego, California 2016
[C6]
Constructing a statistical atlas of the radii of the optic nerve and cerebrospinal fluid sheath in young healthy adults
R. Harrigan, A. Plassard, L. Mawn, R. Galloway, S. Smith, and B. Landman
Orlando, Florida 2015
[C7]
TRADITIONAL MBA ADMISSIONS CRITERIA AND GRADUATE SCHOOL SUCCESS: HOW ARE GMAT SCORES, UNDERGRADUATE GPA, AND GRADUATE BUSINESS SCHOOL PERFORMANCE CORRELATED?
K. Hammond, M. Cook-Wallace, E. Moser, and R. Harrigan
AELJ 2015
[C8]

Posters

Automatic Measurement of Optic Nerve Atrophy in Multiple Sclerosis Patients with and without Optic Neuritis in MRI
R. Harrigan, S. Smith, and B. Landman
Vancouver, BC, Canada 2016
[S1]
Imaging in the Optic Nerve: Insights into Optic Nerve Pathology
R. Harrigan, S. Chaganti, S. Smith, and B. Landman
Nashville, Tennessee 2015
[S2]
Optic Nerve Mapping in Multiple Sclerosis Patients with and without Optic Neuritis
R. Harrigan, S. Smith, and B. Landman
Nashville, Tennessee 2015
[S3]
Mapping of the Optic Nerve in MS Patients with and without Optic Neuritis
R. Harrigan, S. Smith, and B. Landman
Toronto, ON, Canada 2015
[S4]