Alejandro Rodriguez Pascual

Alejandro Rodriguez Pascual

Master’s of Science in Computer Science - Specialization in Data Science

University of Massachusetts - Amherst


I was born and raised in Madrid, Spain, and moved to the San Francisco Bay Area in 2016, where I finished high school. I then got my bachelor’s degree in Mathematics - Computer Science from the University of California San Diego, graduating a year early in the midst of a global pandemic, and then completed a M.S. in Computer Science from the University of Massachusetts, Amherst in 16 months. I have been passionate about computer science and mathematics for as long as I can remember. Not only do I understand how influential a good education and access to technology can be, which I strive to make more accessible, but I also wonder what the future holds, and hope to take part in shaping it. Thus, I have strived to make technology and education more accessible, as well as contributing to research efforts to build towards a brighter future.

  • Artificial Intelligence
  • Machine Learning and Deep Learning
  • Sports Analytics
  • M.S. in Computer Science - Data Science Specialization, 2023

    University of Massachusetts, Amherst

  • B.S. in Mathematics - Computer Science, 2022

    University of California, San Diego


Welcome to my personal website, a virtual space where I will be posting tidbits of my research projects, random thoughts and ideas, thought-provoking articles and stories... This is an opportunity for me to speak my mind, and an opportunity for you to get to know me on a more personal level than a social media profile or a resume might allow you to. Feel free to wander around and contact me if you would like to know a bit more about me or just chat about anything!




R Language




Jupyter Notebooks












Other Interests











TV Shows

Casual Watcher


(our future overlords)


(armchair) Astronaut




Teaching Assistant
Sep 2023 – Dec 2023 Amherst, MA
Held office hours and graded assignments for Prof. Matthew Rattigan in the “Data Analytics with Python” class for 50 students. Topics included Python, web APIs, SQL, Pandas, visualization, Scikit-Learn, supervised & unsupervised learning, causality and model evaluation.
Machine Learning Engineering Intern
Dioscuri Capital
Jun 2023 – Present Remote
Developing a machine learning algorithm and model for detection of volatility contraction patterns in time series of trading data over variable time scales, with a few-shot semi-supervised learning (SSL) approach. Currently implementing this model in an algorithmic investment bot at the core of a new multi-million dollar fund that the firm will market to key clients in 2024.
Data Science Intern
Jun 2022 – Jan 2023 San Diego, California + Remote
Developing machine learning models to better predict basketball game outcomes and player performance in order to better inform bet-placing. Building a full pipeline, from data collection and engineetring, to model creation and training, and forecasting and delivery of results to a team of traders.
Undergraduate Research Assistant - Computer Science and Engineering (CSE) Department
Jan 2021 – Jun 2022 La Jolla, California
Developed machine learning models (multiresolution tensor latent factor models & tensor learning) to generate shooting profiles of NBA players from spatiotemporal tracking data, factoring out temporal and playstyle factors. Advised by Prof. Rose Yu.
Software Developer
Oct 2019 – Jun 2022 San Diego, California
TSE is an organization of engineers, designers, and problem solvers offering pro-bono technical and web development services for nonprofits. We believe that technology should be utilized to better the community. Worked on remodeling and improving the website for Sakyadhita, an international organization for Buddhist women, and built a website for UWEAST (United Women of East Africa) to offer online ordering for their community kitchen.
Associate, Tenderloin Technology Lab
Oct 2018 – Jun 2019 San Francisco, California
The Tenderloin Tech Lab’s mission is to provide residents of the Tenderloin district in San Francisco -homeless and low-income individuals experiencing trauma, substance use/abuse/recovery, mental and physical health challenges, learning disabilities and other challenges- with important technological skills that increase their opportunities for employment, access to essential community resources, and connections with family and friends. I helped to identify and address educational needs and goals of TechLab guests, with a focus on acquiring technology skills for work and daily tasks.
Founder & Director, Balder Labdoo Hub
Dec 2014 – Jun 2016 Las Rozas de Madrid, Spain
Labdoo’s mission is to deliver technology and education access to underserved communities around the world. Their process consists of hubs taking donations of unused laptops and tablets, sanitizing them and loading them with educational software, and giving them to people who are traveling to one of these communities to deliver them. I founded a hub at my school and directed it for nearly two years. We received, sanitized, and shipped a dozen laptops and registered new locations in Mexico and Togo, among others.


Machine Learning Engineering for Production (MLOps) Specialization

This 4-course specialization by I learned how to conceptualize and maintain integrated Machine Learning systems. I mastered well-established tools and methodologies to build production systems that can handle relentless evolving data and continuously run at maximum efficiency. I’m now familiar with the capabilities, challenges, and consequences of machine learning engineering in production. I learned how to:

  1. Design an ML production system end-to-end: project scoping, data needs, modeling strategies, and deployment requirements.
  2. Build data pipelines by gathering, cleaning, and validating datasets. Establish data lifecycle by using data lineage and provenance metadata tools.
  3. Establish a model baseline, address concept drift, and prototype how to develop, deploy, and continuously improve a productionized ML application.
  4. Apply best practices and progressive delivery techniques to maintain and monitor a continuously operating production system.

It consists of the following courses:

  1. Introduction to Machine Learning in Production
  2. Machine Learning Data Lifecycle in Production
  3. Machine Learning Modeling Pipelines in Production
  4. Deploying Machine Learning Models in Production
See certificate
Eta Kappa Nu Member
Inducted to Eta Kappa Nu (HKN), the National Honor Society for Computer Science and Electrical Engineering.
ERSP Scholar
Selected for the Early Research Scholars Program (ERSP) -cohort of 48-, to conduct undergraduate research in computer science.
Deep Learning Specialization

This 5-course specialization by was created and is taught by Dr. Andrew Ng, a global leader in AI and co-founder of Coursera. It’s designed to prepare learners to participate in the development of cutting-edge AI technology, and to understand the capability, the challenges, and the consequences of the raise of deep learning. It helped me learn the foundations of Deep Learning, understand how to build neural networks, and learn how to lead successful machine learning projects. I learned about Convolutional networks, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization, and more. I worked on case studies from healthcare, autonomous driving, sign language reading, music generation, and natural language processing. I practiced all these ideas in Python and in TensorFlow.

It consists of the following courses:

  1. Neural Networks and Deep Learning
  2. Improving Deep Neural Networks - Hyperparameter Tuning, Regularization and Optimization
  3. Structuring Machine Learning Projects
  4. Convolutional Neural Networks
  5. Sequence Models
See certificate
Labdoo International Award
LABDOO is a humanitarian social network joined by people around the world who want to make our planet a better place by providing those in underdeveloped regions a chance at a better education. Awarded the 2016 Labdoo International Award in recognition to my “contribution helping spread education around the world.” I am the youngest person ever to receive this award. I was also an invited speaker at the 2016 Labdoo Global Conference in Barcelona, Spain.


  • 1 N University Dr, Amherst, MA 01002
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