Machine Learning

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Below are the consultant we have available with Machine Learning and other expertise listed.

Sand Mining - Plugging a Critical Data Gap

May 14, 2024
Suraj Nair
by Suraj Nair. Excessive sand mining is causing a global ecological crisis. In this blog post, I present why sand mining is one of the most pressing challenges facing the planet, and why persistent data gaps hinder accountability and monitoring. I also discuss an ongoing research project of mine where we combine freely available satellite imagery and machine learning models to build open-source sand mine detection tools that can plug some of these data gaps.

Tactics for Text Mining non-Roman Scripts

April 15, 2024
Hilary Faxon, Ph.D.
by Hilary Faxon, Ph.D. & Win Moe. Non-Roman scripts pose particular challenges for text mining. Here, we reflect on a project that used text mining alongside qualitative coding to understand the politicization of online content following Myanmar’s 2021 military coup.

Nicolas Nunez-Sahr

Consultant
Statistics

I lived in Santiago, Chile until I graduated from high school, and then moved to the US for undergrad at Stanford, where I obtained a Bachelor’s degree from the Statistics Department. I then worked as a Data Scientist in an NLP startup that was based in Bend, OR, which analyzed news articles. I love playing soccer, volleyball, table tennis, flute, guitar, latin music, and meeting new people. I want to get better at mountain biking, whitewater kayaking, chess and computer vision. I find nature astounding, and love finding sources of inspiration.

Gaby May Lagunes

Consultant
ESPM

Hello! I’m Gaby (she/her). I am PhD student at the ESPM department, I hold a masters in Data Science and Information from the Berkeley ISchool and I have 5+ years of industrial experience in different data roles. Before that I got a masters in Engineering for International Development and an undergraduate degree in Physics from University College London. And somewhere between all that I got married, survived the pandemic, and had two awesome boys. I’m very excited to help you use data to enhance your work and your experience here at Berkeley!

Thomas Lai

Consultant
School of Information

I am a Product Engineer passionate about applying engineering, data science, machine learning, and problem-solving principles to improve device performance and solve complex challenges. With experience in statistical analysis, lab bench automation, and Python scripting, I have developed a strong technical skill set that allows me to make meaningful contributions to any project. Beyond my work, I am also passionate about exploring new topics and ideas, from the latest technology trends to how to improve the overall well-being of humans. I enjoy applying the first principle to any...

Computational Social Science in a Social World: Challenges and Opportunities

March 26, 2024
José Aveldanes
by José Aveldanes. The rise of AI, Machine Learning, and Data Science are harbingers of the need for a significant shift in social science research. Computational Social Science enables us to go beyond traditional methods such as Ordinary Least Squares, which face challenges in addressing complexities of social phenomena, particularly in modeling nonlinear relationships and managing high-dimensionality data. This paradigmatic shift requires that we embrace these new tools to understand social life and necessitates understanding methodological and ethical challenges, including bias and representation. The integration of these technologies into social science research calls for a collaborative approach among social scientists, technologists, and policymakers to navigate the associated risk and possibilities of these new tools.

Using Big Data for Development Economics

March 18, 2024
Leïla Njee Bugha
by Leïla Njee Bugha. The proliferation of new sources of data emerging from 20th and 21st century technologies such as social media, internet, and mobile phones offers new opportunities for development economics research. Where such research was limited or impeded by existing data gaps or limited statistical capacity, big data can be used as a stopgap and help accurately quantify economic activity and inform policymaking in many different fields of research. Reduced cost and improved reliability are some key benefits of using big data for development economics, but as with all research designs, it requires thoughtful consideration of potential risks and harms.

Dive into the Future of AI with the LLM Working Group at D-Lab

February 7, 2024
Tom van Nuenen, Ph.D.
by Tom van Nuenen, Celebrating 10 years of innovation in data-intensive social science, D-Lab in collaboration with Grad Div is excited to introduce the LLM Working Group, an initiative focused on the exploration and discussion of Large Language Models (LLMs) like ChatGPT within academic research and teaching. This group aims to unite scholars, students, and data scientists to address crucial questions about AI's role in academia, including access, impact, creativity, and learning in the age of information automation. Through a series of interactive sessions, participants will gain insights into LLM capabilities, discuss ethical considerations, and explore innovative approaches to utilizing these tools in their work. Whether you're an AI veteran or a novice curious about the potentials of GenAI, the LLM Working Group offers a collaborative platform to learn, share, and shape the future of academic inquiry. Join us in navigating the world of LLMs together.

Creating the Ultimate Sweet

January 30, 2024
Emma Turtelboom
by Emma Turtelboom. What is the best Halloween candy? In this blog post, we will identify attributes of popular sweets and create a model to understand how these attributes influence the popularity of the sweet. We’ll discuss alternative model approaches and potential drawbacks, as well as caveats to interpreting the predictions of our model.

Addison Pickrell

IUSE Undergraduate Advisory Board
Mathematics
Sociology

Addison is an aspiring mathematician and social scientist (Class of '27). He loves collecting books he'll never read, is an open-source and open-access advocate, and an aspiring community organizer and systems disrupter. Ask me about community-based participatory action research (CBPAR), critical pedagogy, applied mathematics, and social science.