Thalia Rodriguez, Ph.D

Experience

Machine Learning Engineer UK Dementia Research Institute 2021 - 2024	• Improved clinical data quality by 5% and environmental by 30% by integrating third-party APIs (EMR, NHS, sensors) data and implementing ETL batch workflows for data validation, transformation, and advanced analytics. • Built a custom production ML system to develop therapies for +100 patients by engineering sleep related features and creating models to identify causes of sleep disruption. • Authored and updated software documentation and technical reports, covering system architectures, algorithms, analytics insights, and research methodologies.

Data Scientist Consultant 2018 - 2020	• Reduced in 90% manual data entry by designing a website and integrating automated data collection systems. • Boosted client’s website conversion rates from 2% to 10% through targeted A/B testing strategies. • Optimized data processing by developing a user-friendly Python interface with a SQL backend, enabling betterunderstanding and tracking of key KPIs, while reducing query execution time by 20%.

Physics Lecturer Indiana University Purdue University Columbus 2019 - 2020	• Maintained 100% attendance in classes by engaging students with adaptive teaching methods, receiving an 89% positive evaluation rate. • Mentored students to improve their grades by an average of 10% across physics, mathematics, and statistics courses through enhanced critical thinking and problem-solving exercises

Research Assistant Lab of Computational Biophysics TCU 2013 - 2018	• Created mathematical models in Python (scikit-learn, SciPy) to analyze the effect of novel antivirals in respiratory viral infections, tracking benchmark metrics and reducing experimental research costs. • Applied statistical techniques (MCMC, bootstrapping) and regression methods (linear, ODE parameter estimation) to extract insights and maximize value from limited data.

Case competitions:

IOWA Tippie Business Analytics Competition 2018 February 2018	• Conducted an in-depth analysis of United Airlines customer surveys big data using R and Python. Identified through machine learning that the key factors to improve customer experience. • Delivered visualizations of my findings using Tableau and recommendations to a panel of industry experts.

TCU Neeley School of Business IBM Case Competition 2017 August 2017	• Detected areas of opportunity to take advantage of the emergence of AI and presented recommendations to accelerate market share growth.

Integrative Project Simulation TCU Neeley School of Business August 2017	• Planned and managed a marketing strategy based on data available on the simulation. • Counseled my team members in the areas of R&D, supply chain and finance.

Computer skills:

Python	Pandas Scipy Numpy Seaborn Matplotlib NLTK Spacy ScikitLearn Statsmodels
Analytics:	SAS HuggingFace PyTorch Tableau XGBoost CatBoost R
Data Storage & Control:	Git SQL AWS Snowflake Airflow Docker
Web Development:	HTML/CSS/Javascript Flask Streamlit

Other skills:

            
          Logical thinking:I love puzzles and problem solving. I believe logic and critical thinking is more
		important than memorization.

            
            
          Communication: In college, I was invited to work as radio host for a musical show.
		But instead, I asked to have a section in a science oriented show. 
		A couple of times people recognized my voice in the street.

            
          Business:I took MBA courses during my Ph.D.
		I learned about Business Operations, Marketing, Supply Chain, and Finance.

		I also met awesome people.

Education

Texas Christian University and Neeley School of Business Ph.D. in Physics with Business Option	2013 - 2018 GPA: 3.6
Texas Christian University M.S. Physics	2013 - 2016 GPA: 3.9
Universidad Autonoma de Zacatecas B.S. in Physics	2008 - 2013 GPA: 3.1
Certifications:
AWS Cloud Practitioner (CLF-C02) Link	March 2025
Data Engineer by DataCamp Link	February 2025
Structuring Machine Learning Projects by deeplearning.ai	February 2020
Machine Learning by Stanford University on Coursera	January 2020
Level 1 Intelligence Analyst on Udemy	April 2019

Machine Learning

I am interested in using Python and technology to improve people's lives, enhance business and create impact.
Over the past few years, I have focused on healthcare.
However, I am curious about other topics as well. For example, in business school, my favorite classes were Marketing and Finance. I enjoy reading about these subjects and thinking about projects.

Recent projects:

Predicting Hotel Booking Conversion Rates in Real Zero-Inflated Data: A Dual-Model Approach	July 2024 Trivago is a meta-search website that enables advertisers to promote accommodations and allows users to compare different prices for the same accommodation. By aggregating offers from various booking sites, Trivago provides users with a comprehensive view of available options, helping them to make informed decisions and find the best deals. The task given was to create a model to predict conversion rates for hotel bookings across various advertising sites. This involved using the provided anonymized real data to make predictions for each advertiser-hotel combination for the specific date of August 11. The challenge was further compounded by the sparsity of data and the presence of zero-inflated data, as many advertiser-hotel combinations had no bookings at all. For more info click here.

ThaliaGPT	June 2024 ThaliaGPT is a Streamlit-based app that streamlines interactions between Thalia Rodriguez and recruiters using OpenAI's advanced Large Language Models (LLMs) and personalized data. It offers an engaging chat experience, allowing users to ask questions about Thalia and receive accurate responses. Users can choose their contact method (Email or LinkedIn) and log their details. The app, deployed on an AWS EC2 instance, ensures scalable, reliable performance. This project demonstrates AI-driven chatbot capabilities and serves as a practical networking tool enhanced by personalized data ingestion. For more info click here.

Other projects:

		SmartGram App: Models\ App
		Code here
Code	Code	Code
Code

Research Publications

Method to determine whether sleep phenotypes are driven by endogenous circadian rhythms or environmental light by combining longitudinal data and personalised mathematical models.	.
Quantifying the effect of trypsin and elastase on in vitro SARS-CoV infections.	.
Estimation of viral kinetics model parameters in young and aged SARS-CoV-2 infected macaques.	.
A comparison of methods for extracting influenza viral titer characteristics.	In this article, our aim is to compare the estimates of different viral titer characteristics using three different approaches. The first approach is the traditional method that uses estimates based on experimentally measured data. The second approach relies on the use of a linear model to fit the viral titer data. The third approach uses an exponential model for the fitting process and the parameters of interest are extracted from there.
Investigating different mechanisms of action in combination therapy for influenza	Here, we use a mathematical model of influenza to model combination treatment with antivirals having different mechanisms of action to measure peak viral load, infection duration, and synergy of different drug combinations.

Interests and Voluntary Work

Apart from coding, I enjoy physical challenges. If I have free time, I like to go to the gym to practice boxing (I do it since highschool). In the weekends, I practice yoga at home.

I enjoy sci-fi movies. And in Netflix, I mostly watch crime and mistery shows.

I can't decide if I'm a cat or dog person, I adore both.

I love to talk and learn about science. I spend a lot of time reading about tech.

Machine Learning Engineer, Omdena

• Collaborating in the AI challenge: “Analyzing the role of connectivity on economic and human development”. This challenge is hosted by UNDP and the goal is to build an AI-based solution for identifying the relationship between connectivity and human development indicators (life expectancy, education, and/or per capita income)..

November 2020 - January 2021

Mentor at Honors Program IUPUC

I work closely with a mentee, we use statistics and mathematical models to develop biophysics simulations using Python.

Spring 2020

Volunteer at Alice Carlson Enrichment Classes

Developed a program for the enrichment classes at Alice Carlson Elementary School (Fort Worth, TX).
Taught Magnetism through an interactive course to 3rd grade students.

Spring 2016

Science Communicator at Radio Zacatecas

Created science content for the radio show “A Ciencia cierta." Participated as a host in the live show.

January 2011 - May 2012

Memberships

WWWCode	2019 - Present
Tech Ladies	2018 - Present
Society for Industrial and Applied Mathematics	2013 - 2017
American Physics Society	2013 - 2017