Amanda is a PhD candidate in the statistics department at Berkeley. Her research focuses on causal inference with applications in education, political science and sports. Previously she earned her Bachelor’s degree in mathematics and statistics, with a secondary in computer science, from Harvard.
Chirag is a 2nd year graduate at the I-School. Proficient in Python, Java, R, and SQL, he navigates software application development, machine learning and data science. His keen interest lies in data analysis and statistical methods, driving him to bridge theory and practice seamlessly. Chirag's dedication to excellence, adaptable mindset, and innate curiosity define him as a dynamic problem solver in the ever-evolving tech landscape.
Data Science for Social Justice Senior Fellow 2024
Electrical Engineering and Computer Science (EECS)
I am a PhD student at UC Berkeley in the EECS department co-advised by Prof. Sarah Chasins and Prof. John Canny. My research interest broadly lies in the intersection of AI and HCI, with a focus on making usable AI tools accessible to end users.
I am currently looking into making NLP tools usable and accessible for low-resourced languages. I am also interested in the impact of AI on society, specifically in how it affects Global Majority countries and communities. Outside of research, I like to read books, make and drink traditional Ethiopian coffee, knit,...
This two-part workshop series will prepare participants to move forward with research that uses text analysis, with a special focus on humanities and social science applications.
This two-part workshop series will prepare participants to move forward with research that uses text analysis, with a special focus on humanities and social science applications.
How can we use neural networks to create meaningful representations of words? The bag-of-words is limited in its ability to characterize text, because it does not utilize word context.
How can we use neural networks to create meaningful representations of words? The bag-of-words is limited in its ability to characterize text, because it does not utilize word context.
This two-part workshop series will prepare participants to move forward with research that uses text analysis, with a special focus on humanities and social science applications.
This two-part workshop series will prepare participants to move forward with research that uses text analysis, with a special focus on humanities and social science applications.
This workshop offers a general introduction to the GPT (Generative Pretrained Transformers) model. We will explore how they reflect and shape our cultural narratives and social interactions, and which drawbacks and constraints they have.
