PALiISaDS Conference for
Professional Readiness, Inclusive Scholarship, and Mentorship
May 2-4, 2025 | UCSB Campus
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Fall 2026 applications are OPEN! Sign up for an Info Session today!
Event Schedule
Event Schedule
Friday, May 2
3:00pm | Arrival & Check In | UCSB Guest House
Saturday, May 3
8:30am | Breakfast | ESB 1001
9:00am | Opening Remarks | ESB 1001
9:15am | Keynote | ESB 1001
10:20am | Workshop Session 1:
Creating your personal website with Quarto & GitHub Pages (Pt 2) | ESB 1001
11:20am | Break
11:30am | Career Panel | ESB 1001
12:30pm | Lunch | ESB Patio
1:35pm | Grad Panel | ESB 1001
2:40pm | Workshop Session #2:
3:40pm | Break
4:00pm | NSF S-STEM: Chicago Debrief | ESB 1001
5:10pm | Closing Remarks | ESB 1001
6:00pm | Sunset Beach Dinner & BBQ | Goleta Beach
Sunday, May
11:00am | Departure & Check Out | UCSB Guest House
I develop and teach data science training curricula for the Master of Environmental Data Science (MEDS) program at the Bren School of Environmental Science & Management, located at UC Santa Barbara. I am also a co-organizer of R-Ladies Santa Barbara, a local data science group which works to promote gender diversity in the R community. Since the beginning of my time in STEM, I was totally terrified of all things data / coding / data science, but thanks to a super supportive community and some really rad colleagues / instructors, I found my new path in data science education and I absolutely love it.
I am working on my PhD in the Department of Statistics & Applied Probability (PSTAT) @ University of California, Santa Barbara. Previously, I completed a double B.S. in Computer Science and Applied Mathematics as well as a M.S. in Statistics @ California State Polytechnic University, Pomona. My research interests are statistical learning, machine learning theory, and robustness. I am also a Graduate Student Mentor for the 2024-2025 cohort of the Pacific Alliance for Low-income Inclusion in Statistics and Data Science (PALiISaDS) program. Additionally, I am a certified Carpentries Instructor, collaborating with the UCSB Library's DREAM Lab to co-lead workshops that support research computing skills across disciplines.
Workshops
Workshops
Session 1
Session 1
Creating your personal website with Quarto & GitHub Pages (Pt 2)
In this follow-up to our February 19 workshop, we’ll dive into personalizing your Quarto website with your own headshot, CV, and achievements, so be sure to have those ready! We’ll also dedicate time to troubleshooting and making sure your site is published and ready to share with the world. Don’t worry if you couldn’t attend the first part of the workshop. We’ll help you get caught up using the same template. Just be sure to follow our setup instructions ahead of time: https://tinyurl.com/your-quarto-website. If you have any questions, feel free to reach out to jose_nino@ucsb.edu.
Session 2
Session 2
Responsible and Reproducible Machine Learning Workflows
In this workshop, we will learn the fundamentals of creating a reproducible workflow to apply machine learning models for predictive tasks. The process of fitting a statistical model to data requires many important data scientist decisions, such as: data cleaning, variable preprocessing and transformation, proposing model variant options, and choosing assessment metrics. This workshop will teach learners how to structure their R or python code to make sure each decision point is clear, correct, and reproducible. We'll rely on the existing pipeline structure provided by the packages Scikit-learn (python) and tidymodels (R) - learners can choose which to use for our interactive examples, and skeleton code will be provided for both. While the examples in this workshop will be limited to linear and logistic regression, the framework we present can be generalized to any predictive machine learning model.
Professional Skills 101: Building Confidence in the Workplace
Join UCSB Career Services for an interactive workshop covering the essential skills every professional needs. From writing polished emails to nailing your next interview—and even mastering the perfect handshake—we’ll help you build confidence and communicate effectively in any professional setting. Whether you’re preparing for an internship or your first job, this session is a great place to start.
Career Panel
Career Panel
Lauren Bennett
Lauren Bennett
Career Panelist
Esri
Lauren Bennett is Program Manager of Spatial Analysis and Data Science at Esri. She oversees research and development for data analysis features within the company’s geographic information system (GIS) software systems. This includes spatiotemporal statistics, spatial machine learning, and multidimensional and big data analytics. Since joining Esri in 2007, Lauren also has served as Software Development Team Lead, Spatial Statistics Product Engineer, and Federal Solution Engineer. She earned a bachelors and master’s degree in geography from McGill University and George Mason University, respectively, and a doctorate in Information Science from Claremont Graduate University.
Connor Levenson
Connor Levenson
Career Panelist
UCSB '22
I graduated in 2022 with a B.S. in Statistics and Data Science. During my undergrad I was a part of the Data Science Club, serving as the VP during my senior year. I was also a Central Coast Data Science fellow and had an NSF REU for three quarters in the Vision Research Lab working on weakly supervised object detection. After graduating I joined the Vision Research Lab as a research engineer where I work on two projects: a cyberinfrastructure project dealing with multimodal scientific images and IARPA HAYSTAC working on modeling human patterns of life.
Parash Upreti
Parash Upreti
Career Panelist
Lionsgate
A data analytics professional with experience in all stages of data lifecycle conducting data analysis, statistics and empirical research and always sharpening his analytical skills through research, training and MOOCs. He is always looking to improve as an individual and professional. Current interests are in data management, data engineering, and automation.
Grad Panel
Grad Panel
Emma Franzblau is a first-year PhD student in Political Science at UCLA, where she studies climate and energy politics and political methodology. She earned her BA in Political Science with a minor in Statistics from UC Santa Barbara, where she was a Central Coast Data Science Fellow. Before graduate school, she worked for an interdisciplinary research initiative applying data science methods to social science questions. Emma is excited to share how combining quantitative skills with domain expertise has helped her tackle complex, real-world political questions.
Doris is a graduate student at the University of California, Santa Barbara, pursuing a PhD in Statistics and Applied Probability.
Mallory Wang
Mallory Wang
Graduate Panelist
UCSB
Mallory is a graduate student at the University of California, Santa Barbara, pursuing a PhD in Statistics and Applied Probability.
I am a Doctoral student at UC Irvine studying Statistics. I love using my domain knowledge and computational skills to better understand the world around me, in both a personal and professional context.
I am a PhD student in Statistics at UC Irvine, with a B.S. in Mathematics and a minor in Statistics from CSUMB. My passion lies in applying quantitative methods to real-world public health challenges, particularly in the context of Alzheimer's disease and health disparities among racial and ethnic communities.
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