Ronan Doorley
Verified Expert in Engineering
Machine Learning Developer
Dublin, Ireland
Toptal member since December 4, 2018
Ronan has several years of experience in data science and machine learning with Python, R, and MATLAB. He has a passion for developing validated models of human behavior and complex systems. Currently, he works with the City Science group at the MIT Media Lab where he develops predictive models of individual behavior such as activity scheduling, location choices, and modes of transportation.
Portfolio
Experience
- Machine Learning - 6 years
- Data Science - 6 years
- Regression - 6 years
- Python 3 - 4 years
- Classification - 3 years
- Scikit-learn - 3 years
- Flask - 2 years
- Probabilistic Graphical Models - 2 years
Preferred Environment
GitHub, Jupyter, Spyder, Anaconda, MacOS
The most amazing...
...model I’ve developed simulates a human population from an urban plan and predicts their daily activity schedules and transport mode for each activity.
Work Experience
Mobility Modeling Engineer
MIT Media Lab
- Developed AI for agents in urban simulations using a cascade of Bayesian Network and Random Forest models calibrated with survey data.
- Built a Bayesian network model in Python for generating traffic predictions in the country of Andorra; it was based on a combination of cell phone records and traffic counter data.
- Created also the front-end visualization for the traffic project using Web Sockets and Mapbox GL.
- Developed a Poisson process model in R to explain the formation of dense clusters of social activity in cities based on the physical urban features.
- Deployed a Python Flask API which uses a pre-calibrated discrete choice logit model to predict mobility patterns in response to an input describing changes to land use.
- Used the spatiotemporal data from app usage to develop a discrete choice model in Python to describe how people choose which amenities to visit.
- Implemented neural networks in Python Keras to model proxy metrics for urban vibrancy based on Google Street View images.
Doctoral Researcher | Teaching Assistant
Trinity College Dublin
- Developed a mathematical framework for quantifying the benefits and risks of walking and cycling for transport in urban environments.
- Designed and built a mobile pollution sensing node on the Arduino platform and used it to characterize the exposures of pedestrians and cyclists to various pollutants in Dublin.
- Constructed a game theoretical model in MATLAB describing how people change their transportation behaviors in response to changes in the cycling infrastructure.
- Created a genetic algorithm in MATLAB to find the optimal design of a cycle network, considering the expected behavioral responses and the resulting health and environmental impacts.
Analyst
Accenture
- Created functional designs and tested web applications for clients in the financial sector.
- Worked closely with client resources to determine and document their requirements in areas such as data capture, system functionality, pricing, risk acceptance criteria, automatic document generation, and more.
- Developed product prototypes using Axure and led teams of about ten developers in building fully functional web applications based on these prototypes.
- Thoroughly tested the product during development, mainly using automatic testing scripts.
Experience
CityScope MoCho
https://www.media.mit.edu/projects/mobcho/overview/I built a Flask app which reads the state of the district design from an API and uses a discrete choice logit model to predict the changes in travel patterns and resulting environmental impacts at a regional level. The analysis results are exposed through the Flask API.
Reversed Urbanism
Dynamic Traffic Prediction in Andorra: a Bayesian Network Approach
https://www.media.mit.edu/projects/traffic-andorra/overview/Education
Fulbright Scholar in City Science
Massachusetts Institute of Technology | MIT - Cambridge, MA, USA
PhD Degree in Civil, Structural and Environmental Engineering
Trinity College Dublin - Dublin, Ireland
Bachelor's Degree in Mechanical Engineering
Trinity College Dublin - Dublin, Ireland
Certifications
Data Manipulation at Scale: Systems and Algorithms (MOOC)
University of Washington via Coursera
The Data Scientist's Toolbox (MOOC)
Johns Hopkins University via Coursera
Statistical Inference (MOOC)
Johns Hopkins University via Coursera
Skills
Libraries/APIs
Scikit-learn, NumPy, SciPy, Pandas, Matplotlib, Mapbox GL, NetworkX, PySpark, D3.js, Leaflet, jQuery, Keras
Tools
MATLAB, Spyder, GitHub, Bayes Net Toolbox (BNT), Jupyter, Git
Languages
Python 3, R, Python, JavaScript, HTML, C++
Frameworks
Flask, Selenium, RStudio Shiny
Paradigms
REST
Platforms
MacOS, Anaconda, Arduino
Storage
MySQL
Other
Machine Learning, Research, Statistics, Regression, Classification, Software Development, Probability Theory, Probabilistic Graphical Models, Neural Networks, Axure, Analysis, Data Science, Bokeh, WebSockets, HTTP, Ajax, Experimental Design, Random Forests
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