CV

Contact Information

Name Sequoia Rose Andrade
Professional Title PhD Candidate
Email srandrade@berkeley.edu
Location Berkeley, California, USA

Professional Summary

Third year PhD Candidate in Statistics at UC Berkeley working on computational methods for social good applications.

Experience

  • 2024 - Present

    Berkeley, California, USA

    Graduate Student Research Fellow
    University of California, Berkeley
    Department of Statistics
    • Translated a Julia research code base into a reusable, modular Python package for carbon emission inversion modeling and increased computational efficiency by leveraging matrix sparsity
    • Implemented non-parametric statistics to analyze the effect of bomb threats on polling places in Georgia in the 2024 general election, which led to a conference presentation and publication
    • Authored two Expert Declarations filed as evidence in a complaint for a Racial Justice Act violation lawsuit, based on non-parametric simulation-based statistical inference and non-parametric combination of tests
  • 2020 - Present

    Mountain View, California, USA

    Research Engineer (Contract)
    NASA Ames Research Center
    Open Data Integration for Wildfire Response (ODIN-Fire) · Manager for Intelligent Knowledge Access (MIKA)
    • ODIN-Fire: Developed cloud and smoke classification model to improve satellite-based wildfire detection
    • ODIN-Fire: Trained and evaluated a fully connected neural network for image segmentation to classify smoke from cloud, using TensorFlow and self-supervised pre-training
    • ODIN-Fire: Deployed the model on a Python server and displayed results in a JavaScript application using an actor-based messaging system in Scala
    • ODIN-Fire: Resulted in multiple presentations and a journal manuscript in progress
    • MIKA: Developed and applied the Hazard Extraction and Analysis of Trends (HEAT) algorithm for use on large datasets containing both qualitative and quantitative data
    • MIKA: Implemented transformer-based natural language processing algorithms for information discovery, custom named-entity recognition, classification, and topic modeling
    • MIKA: Leveraged statistical analysis methods to interpret findings, identify significant predictors of hazard occurrence, and examine significant differences
    • MIKA: Resulted in four peer-reviewed journal publications
  • 2022 - 2024

    San Francisco, California, USA

    Graduate Student
    San Francisco State University
    Department of Mathematics · Advisor: Dr. Alexandra Piryatinska
    • Created a novel dataset suitable for studying the effect of prescribed fires on wildfires while controlling for climate variables, by fusing disparate data sources from 2015-2022
    • Performed cross-correlation time series analysis to identify relevant variables
    • Utilized non-parametric statistical tests and regression models to evaluate the effect of prescribed burn treatment on wildfire size
  • 2020 - 2020

    Mountain View, California, USA

    Intern
    NASA Ames Research Center
    System Modeling and Analysis of Resilience in Scalable Traffic Management for Emergency Response Operations (SMARt-STEReO)
    • Collaborated with other interns to develop a simulation model of wildfire propagation and response using Python
    • Identified research questions on system performance and resilience, and tested them using statistics (t-test, ANOVA)
    • Resulted in four publications, including one peer-reviewed journal publication and two technical reports

Education

  • 2024 - present

    Berkeley, California

    PhD
    University of California, Berkeley
    Statistics
    • Advisor: Professor Philip Stark
    • Related Coursework: Theoretical Statistics, Probability Theory, Applied Statistics, Statistical Consulting, Case Studies in Prediction, Policy, and AI
  • 2022 - 2024

    San Francisco, California

    M.S.
    San Francisco State University
    Statistical Data Science
    • Advisor: Professor Alexandra Piryatinska
    • GPA: 4.0 (Distinguished Student Award)
    • Related Coursework: Probability Models, Advanced Probability Models, Categorical Data Analysis, Database Management Systems, Topics in Big Data, Statistical and Machine Learning, Computational Statistics
    • Thesis: A Statistical Analysis of Wildland and Prescribed Fires in the Changing California Climate
  • 2016 - 2020

    Santa Clara, California

    B.S.
    Santa Clara University
    Mathematics (applied emphasis), Psychology
    • GPA: 3.71 (Magna Cum Laude)
    • Related Coursework: Probability and Statistics I (Probability Theory), Probability and Statistics II (Statistics), Advanced Calculus, Ordinary Differential Equations, Partial Differential Equations, Combinatorics, Numerical Analysis, Advanced Linear Algebra, Research Methods, Object Oriented Programming

Honors and Awards

  • 2022
    National Science Foundation Graduate Research Fellowship Program (NSF GRFP)
    National Science Foundation

    On reserve: 2022-2024 · Funded years: 2024-2027

  • 2024
    UC Berkeley Chancellor's Fellowship
    University of California, Berkeley

Skills

Machine Learning: classification and regression, natural language processing, computer vision, neural networks (fully connected, convolutional, recurrent), self-supervised learning, supervised learning
Programming: Rust, Python (Sklearn, Pandas, Transformers, TensorFlow, PyTorch, Ray), R, SQL, GDAL, Scala, Google Earth Engine, Julia, SPSS, C++, MATLAB, JavaScript
Research: public presentations with slides and posters, literature review, team coordination, time management, project scheduling, scientific writing, peer review

Teaching Experience

  • Graduate Student Instructor, UC Berkeley (2025-2026) — Reproducible and Collaborative Data Science; Data Analysis and Machine Learning for Real-World Decision Making
  • Peer Educator, Santa Clara University (2020) — Precalculus
  • Tutor, Santa Clara University (2019-2020) — Precalculus
  • Academic Coach, Cardinal Education (2019-2020) — Precalculus, AP Calculus B/C, Algebra II, Algebra I, Chemistry, Neuroscience

Mentoring Experience

  • Mentor to UC Berkeley Statistics undergraduate students (2025-2026)
  • Mentor to Mason Lee through the NASA internship program (2023)
  • Mentor for the Teens in AI Bay Area Hackathon (2023)
  • Mentor to Cindy Valdez through the NASA internship program (2021-2022)

Publications

  • 2025
    Smoke or Cloud: Real-Time Satellite Image Segmentation in a Wildfire Data Integration Application
    Computers & Geosciences, 204 (2025): 105960

    with Nastaran Shafiei and Peter C. Mehlitz

  • 2023
    Machine Learning Framework for Hazard Extraction and Analysis of Trends (HEAT) in Wildfire Response
    Safety Science, 167 (2023): 106252

    with Hannah S. Walsh

  • 2023
    Natural-Language-Processing-Enabled Quantitative Risk Analysis of Aerial Wildfire Operations
    Journal of Aerospace Information Systems (2023): 1-13

    with Hannah S. Walsh

  • 2023
    Evaluation and Improvement of System-of-Systems Resilience in a Simulation of Wildfire Emergency Response
    IEEE Systems Journal, 17(2), 1877-1888 (2023)

    with Daniel E. Hulse

  • 2023
    Discovering a Failure Taxonomy for Early Design of Complex Engineered Systems Using Natural Language Processing
    Journal of Computing and Information Science in Engineering, 23(3), 031001

    with Hannah S. Walsh

  • 2023
    MIKA: Manager for Intelligent Knowledge Access Toolkit for Engineering Knowledge Discovery and Information Retrieval
    INCOSE International Symposium, 33: 1659-1673

    with Hannah S. Walsh

Conference Publications

  • Andrade, Sequoia, and Stark, Philip. “Does Extending Polling Hours Compensate for Bomb Threats? Evidence from the 2024 Election in Georgia, USA.” E-Vote-ID, October 2025.
  • Mbaye, Seydou; Hulse, Daniel; Irshad, Lukman; Walsh, Hannah; Andrade, Sequoia. “Towards Computational Functional Hazard Assessment (CFHA): A Gap Analysis and Concept for Emerging Aviation Systems.” AIAA 2025-1411, AIAA SciTech 2025 Forum, January 2025.
  • Andrade, Sequoia R.; Mbaye, Seydou; Davies, Misty; Jones, Garfield. “Evaluating Faulty State Occurrence in Wildfire UAS Missions Using Markov Chains.” AIAA 2024-4365, AIAA AVIATION 2024 Forum, July 2024.
  • Andrade, Sequoia R., and Walsh, Hannah S. “SafeAeroBERT: Towards a Safety-Informed Aerospace-Specific Language Model.” AIAA 2023-3437, AIAA AVIATION 2023 Forum, June 2023.
  • Andrade, Sequoia R., and Walsh, Hannah S. “What Went Wrong: A Survey of Wildfire UAS Mishaps through Named Entity Recognition.” 2022 IEEE/AIAA 41st Digital Avionics Systems Conference (DASC), Portsmouth, VA, 2022, pp. 1-10. Awarded 2nd Best of Conference.
  • Walsh, Hannah S., and Andrade, Sequoia R. “Semantic Search With Sentence-BERT for Design Information Retrieval.” International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, Vol. 86212, ASME, 2022.
  • Andrade, Sequoia R., and Walsh, Hannah S. “Machine Learning Enabled Quantitative Risk Assessment of Aerial Wildfire Response.” AIAA AVIATION 2022 Forum, 2022.
  • Andrade, Sequoia R., and Walsh, Hannah S. “Knowledge Discovery for Early Failure Assessment of Complex Engineered Systems Using Natural Language Processing.” International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, Vol. 85376, ASME, 2021.
  • Andrade, Sequoia R., and Walsh, Hannah S. “Wildfire Emergency Response Hazard Extraction and Analysis of Trends (HEAT) through Natural Language Processing and Time Series.” 2021 IEEE/AIAA 40th Digital Avionics Systems Conference (DASC), IEEE, 2021.
  • Andrade, Sequoia R., et al. “The System Modeling and Analysis of Resiliency in STEReO (SMARt-STEReO).” AIAA AVIATION 2021 Forum, 2021.

Technical Reports

  • Andrade, Sequoia; Hulse, Daniel E.; Irshad, Lukman; Walsh, Hannah S. “Supporting Hazard Analysis for Wildfire Response Using fmdtools and MIKA.” 2022.
  • Lehman, Sarah M.; Slagel, Tanner J.; Andrade, Sequoia; Walsh, Hannah; Goodloe, Alwyn; Brandt, Summer L.; Neogi, Natasha. “NASA System-Wide Safety Wildland Firefighting Operations Workshop Report.” NASA/TM-20220014721, 2022.
  • Hulse, Daniel E.; Andrade, Sequoia R.; Spirakis, Eleni; Walsh, Hannah S.; Davies, Misty D. “SMARt-STEReO: Preliminary Model Description.” 2020.
  • Walsh, Hannah S.; Spirakis, Eleni; Andrade, Sequoia R.; Hulse, Daniel E.; Davies, Misty D. “SMARt-STEReO: Preliminary Concept of Operations.” NASA/TM-20205007665, 2020.

Presentations

  • Andrade, Sequoia; Asimow, Naomi; Giordano, Ryan; Cohen, Ronald. “Towards Accelerated CO2 Inversion Modeling for Understanding Uncertainties through Multicore Processing and a Reusable Code Base.” American Geophysical Union Annual Meeting, 2025.
  • Andrade, Sequoia; Mehlitz, Peter; Shafiei, Nastaran; Coughlan, Joseph; Brat, Guillaume. “Improving Satellite-Based Hotspot Detection Through Deep Learning-Enabled Smoke Recognition.” American Geophysical Union Annual Meeting, 2024.
  • Andrade, Sequoia, and Piryatinska, Alexandra. “Towards a Statistical Analysis of Wildland and Prescribed Fires in the Changing California Climate.” CSU Mathematical Sciences Conference, 2023.
  • Andrade, Sequoia, and Walsh, Hannah. “Natural Language Processing Techniques for Intelligent Knowledge Management of Safety Reports.” NASA Data Science Summit, 2022.

Certificates

  • AWS Cloud Practitioner - Amazon Web Services (2022)
  • Unsupervised Data Science for Aviation - NASA (2022)
  • Advanced Data Science for Aviation - NASA (2021)
  • Data Science for Aviation - NASA (2021)

Leadership

  • Treasurer, Statistics Graduate Student Association, UC Berkeley (2025)
  • Treasurer, Association for Women in Mathematics, Santa Clara University (2019-2020)
  • President, Pi Mu Epsilon (Eta Chapter), Santa Clara University (2019-2020)

Interests

Research Areas: Computational methods, Social good applications, Racial justice in the legal system, Carbon emissions monitoring