We are pleased to present our CTSP Fellows for the 2020 year. This year we have 37 fellows across 18 projects!
We are pleased to present our CTSP Fellows for the 2020 year. This year we have 37 fellows across 18 projects!
Shazeda Ahmed is a Ph.D. candidate at the University of California, Berkeley who researches how China’s government and domestic technology firms are collaboratively constructing the country’s social credit system. Shazeda has worked as a researcher for Upturn, the Citizen Lab, the Mercator Institute for China Studies, and the Ranking Digital Rights corporate transparency review by New America. In the 2018-19 academic year she was a Fulbright fellow at Peking University’s law school.
Julia Bernd is a staff researcher in Usable Privacy and Security at ICSI and a member of the Berkeley Laboratory for Usable and Experimental Security (BLUES). She is a linguist by background (MA, Stanford University, 2002), and has applied this training as a qualitative data analyst on projects including academic research as well as community needs assessments, policy recommendations, and program reviews for The California Endowment and the Oakland School District (among others). At ICSI and UC Berkeley, she has been involved in evaluating California Connects, a statewide digital-literacy program; managing and developing content for curriculum projects including Teaching Privacy, the SJPL Virtual Privacy Lab, Teach Global Impact, and Teaching Security; and researching user expectations about smart-home devices.
Mugdha Bhusari is a 2nd year graduate student at UC Berkeley currently specialising in machine learning, quantitative research methods and causal inference. She has thorough knowledge on model building, natural language processing, statistical learning theory and experimental design. She interned with the machine learning team at Schlumberger’s Technology and Innovation Center and has previously worked as Decision Scientist at Mu Sigma Business Solutions Inc. At School of Information, she is working on interesting projects such as analyzing the effect GAN rendered personalized video on learning speed.
David Chan is a third year PhD student in the EECS Department at UC Berkeley advised by Dr. John Canny. At UC Berkeley, he is part of the Berkeley Institute of Design, BAIR, and Berkeley PATH. His research explores how we can teach artificial agents to understand and operate the world around us. His work also explores how these agents can convey information to users, and explain their own actions in a human-driven and understandable way.
Millie is a PhD student in the Department of Environmental Science, Policy, and Management at the University of California, Berkeley. Her research is at the intersection of decision theory and conservation ecology, with a particular interest in the efficacy of adaptive natural resource management. Prior to Berkeley, Millie worked at the Woods Hole Research Center assessing the global climate mitigation contributions of agroforestry and exploring the socioeconomic and biophysical drivers of deforestation in the context of international climate finance programs. Millie received with bachelor’s degree from Yale University in Ecology and Evolutionary Biology.
Samy Cherfaoui is an undergraduate student studying computer science at UC Berkeley, with extensive experience in software engineering through two internships and with specific experience and connections in the educational technology industry. This includes interning at Coursera, the leading online learning platform.
Nicole Chi (she/her) is a UC Berkeley School of Information student whose experience bridges the technology, nonprofit, and policy space. In the past two years, she launched a program and then an organization that helps nonprofits and technologists collaboratively design technology for the public good. She has also worked in the startup ecosystem in New York, as well as a think tank in DC focused on digital transformation. Nicole’s superpower is pulling together connections, expertise, and people across diverse disciplines to work towards a more just and equitable future. She is excited to explore themes related to participatory democracy, privacy awareness, and technology for movements within the CTSP community.
Aneesa is a product manager with 5 years of experience building inclusive products for SaaS, B2C, and government organizations. As a product manager at Browserstack, she worked on making comprehensive testing infrastructure accessible to small businesses. At Housing.com, an equal housing opportunity platform, she built the property discovery experience. As a consultant for JKBOSE, she worked on a child-centered pedagogy project aimed at training 10 year-olds to think critically about propaganda. Currently, she is pursuing a master’s in Information Science at UC Berkeley and is deeply interested in testing interventions that could impede the spread of misinformation.
Andrew Chong is a PhD student at the UC Berkeley School of Information, where his research focuses on how the use of algorithms influences market competition and outcomes. His work examines the increasing role algorithms and firm-controlled marketplaces play in economic life, and their wider implications for fairness, efficiency and competition. Previously, Andrew worked at the National Bureau of Economic Research examining the impact of behavioral interventions in healthcare and consumer finance. He also has experience developing and implementing pricing models for prescription health insurance (PicWell), and developing dashboards for city governments (with Accela and Civic Insight).
Project: Data for Defenders
Sneha Chowdhary comes with foundational experience in digital design and management – having worked as a UX Engineer, Product Designer & Product Manager before joining the School of Information. Her strong yet paced growth in the industry has helped her operatively incorporate design thinking – by empathising with users and keeping them at the core of her design decisions, communication – be the glue in cross-collaboration between people and teams and analytical & strategic planning – to efficiently help projects achieve their end goal. She will leverage these skills to conduct a needs assessment, design & prioritize the product for the required technical solution.
Amrit Daswaney is a 2nd year graduate student at UC Berkeley currently specialising in privacy engineering and machine learning. He worked on privacy engineering projects such as optimizing organ-donation algorithms & dataflows to address privacy concerns of open source datasets from national registries.
Caroline Figueroa is a Postdoctoral Scholar at the UC Berkeley School of Social Welfare within the Digital Health Equity and Access Lab (D-HEAL). She obtained her MD and PhD degree from the University of Amsterdam. Her PhD research focused on on psychological and neurobiological vulnerability for depression. Her work at D-HEAL involves developing and testing digital interventions (text-messaging and smartphone apps) to treat depression and diabetes in low-income and underserved communities. She is passionate about harnessing emergent technologies to improve health for vulnerable populations.
Alisa Frik, Ph.D., is a postdoctoral researcher at the Usable Security and Privacy research group at the International Computer Science Institute (ICSI) and the University of California, Berkeley. She is a member of the Berkeley Laboratory for Usable and Experimental Security (BLUES), under the direction of Dr. Serge Egelman, and the Privacy Economics Experiments Lab (PEEX) at Carnegie Mellon University, under the direction of Prof. Alessandro Acquisti. She has obtained a Ph.D. degree in Economics at the School of Social Sciences, University of Trento, Italy. Alisa applies her expertise in behavioral and experimental economics, decision-making, behavior change, and choice architecture, and experience in survey and interview design, online, lab and field experiments, and experience sampling to investigate privacy and security attitudes and behaviors of regular and vulnerable populations of online users (such as older adults, employees of civil society organizations, domestic workers and non-primary user groups). She explores how contextual and human factors, including trust, heuristics and biases, as well as behavioral interventions, such as personalized nudges, commitment devices, and privacy-enhancing tools, affect users’ behaviors and decisions. She focuses not only on web and mobile privacy and security, but also on emerging technologies in healthcare, Internet of Things, digital advertising, and smart voice assistants.
Shubhra Ganguly is a third year undergraduate at UC Berkeley studying Electrical Engineering and Computer Science. Over his undergraduate career he has worked for a hedge fund doing quantitative data analysis, Lawrence Berkeley National Lab doing city wide energy prediction for underdeveloped economies. He is passionate about enabling everyone, regardless of income-level or location, have access to technology that improves their lives.
Project: An Alternate Lexicon for AI
Noura Howell asks, How do we make meaning with data? Not only analytically, but also with our feelings, bodies, materials, and social relationships? Her design research investigates ways of knowing with biosensory data – data about people’s bodies, behaviors, thoughts, and feelings. Combining critical making, speculative design, and participatory experiences, Howell challenges dominant techno-logics of data and explores alternatives, working code, circuits, wood, e-textiles, and sound. She is a PhD candidate at the School of Information at the University of California, Berkeley, with a Designated Emphasis in New Media. Before grad school, Howell worked at Intel, Microsoft, and The Echo Nest.
Julia Irwin is a PhD student at UC Berkeley in the department of Film & Media with a Designated Emphasis in New Media. Her research focuses on historicising contemporary sensing technologies, such as facial or voice recognition, that have become infrastructural to government and industry practices yet are often black boxed. By tracing their technical, intellectual, and cultural history, her work challenges their opacity and uncovers the assumptions baked into their design. Prior to Berkeley, Julia received a master’s degree in media art from NYU Tisch’s Interactive Telecommunications Program, where she subsequently served as a Research Fellow and Adjunct Professor.
Shagun Jhaver is a PhD candidate in Computer Science at Georgia Tech. His research
builds a foundation for designing fair and efficient content moderation systems. He has contributed in-depth descriptions of how moderation systems on Twitter and Reddit are constituted and how they affect platform owners, content moderators, and end-users. His work has been published in prestigious HCI venues such as TOCHI, CHI, CSCW and ICWSM. It has received two Best Paper Awards (at CSCW and ICWSM), one Honorable Mention Award (at CSCW), and been featured in Editor’s Spotlight in TOCHI. His research has also received attention in the popular press, including The Washington Post, Forbes, New Scientist, and MIT Technology Review.
Joanne Jia is a Masters student at the UC Berkeley School of Information with a focus on Data Science and User Experience Research. She has a dual degree in Philosophy and Economics from Claremont McKenna College, during which she conducted economic forecasting research along with her professor for the underdeveloped Inland Empire area in Southern California. She worked for two years at a fintech startup that develops software and processes to help small business owners secure long-term low-interest funding. She is passionate about leveraging technology to facilitate positive changes for the underprivileged.
Emma Lurie is a PhD student at the UC Berkeley School of Information where her research focuses on studying how algorithmically curated content shapes human decision making. She is particularly interested in online reputation management, election related search engine audits, and automated fact-checking. Previously, Emma received her BA from Wellesley College in Computer Science and Chinese Language & Culture.
Brie is a third-year PhD student in the Jurisprudence and Social Policy program at the University of California, Berkeley. Her research focuses on sociology, law, and policing, with a particular focus in feminist theory and critical race theory. Brie has worked in the non-profit and government sphere, giving her an extensive background in community outreach and policy analysis. Brie also has a Masters in Public Policy and Master of Arts in Women’s, Gender, and Sexuality Studies from Brandeis University and a Bachelor of Arts in Anthropology and Gender Studies from New College of Florida.
Jennifer is a 2nd year graduate student in the school of information, studying Information managementand systems with a focus in Data Science. As a CTSP fellow, she is interested in exploring how theories of social psychology can be applied to the creation of more inclusive technological platforms.
Project: Data for Defenders
Tiffany Pham is a UX researcher and a graduate student at UC Berkeley’s School of Information. She has experience working in the fields of intellectual property law, policy, and user research, specifically research on the design of intuitive educational technologies and forums for refugee advocacy. Tiffany is passionate about advocating for marginalized communities in the design and use of technology. She received her Bachelor’s degree in Computer Science and Psychology at Columbia University.
Akshay is a 2nd year graduate student at UC Berkeley currently specialising in Data Science and Machine Learning. He is deeply passionate about leveraging ML and AI for bigger social impact. His keen interest lies at the intersection of three core tenets – Machine Learning, Security & Product. Over the past 2 years, he has developed a diverse skill set in these domains through research and courses in data science, deep learning working on detection of deep fakes and building an animal classification system. Previously he has worked as a data science intern at PayPal as well as a consultant in the risk and analytics domain at PwC for India’s National ID Program.
Vidya is a product manager with over 6 years of experience building tech products for developing nations. Before coming to graduate school at UC Berkeley, she led product strategy and operations at Uber, devising products for underserved riders and drivers in Brazil, Mexico, Ukraine, and India. Vidya also has a background in trust and safety, and has spent time in the trenches at Twitter and Facebook on the election integrity and ads and commerce trust teams. She has spent many years understanding these ecosystems, and has led investigations on the impact of integrity issues on community. Through her research, she hopes to blend tech and policy to fight the misinformation problem, applying techniques of experimentation and prototyping to a space she’s passionate about.
Nithya Ramgopal is a second year Masters’ student at UC Berkeley School of Information. Her area of expertise is Data Science/ Quantitative Research. She recently completed a data science internship at Tesla where she worked on building models to improve the performance of the Tesla Powerwall and Powerpack. She has experience with data engineering, A/B testing, predictive modelling and data visualization. Nithya also has two years of work-experience as a Data Analytics Consultant. She has worked with clients across the world to build big data solutions for enhancing their businesses. Her interests include reading and traveling.
Project: An Alternate Lexicon for AI
Noopur Raval is a PhD candidate in the Informatics Department at the University of California Irvine and her research looks at the social, cultural and political impact of platforms on urban life and the future of work. Using qualitative research methods and critical posthumanist, decolonial and feminist approaches to technology studies, Raval investigates how platforms reshape social power and lived infrastructure by transforming daily work in the global South. She also writes about the colonial legacies and potential harms of datafication in international development. She is an alumna of the Berkman-Klein Centre for Internet & Society.
Vivant is a software engineer with 4 years of experience building scalable backend systems mainly focusing on Computer Security and Data Protection at Symantec. He has worked on innovative features concerning intelligent information-centric encryption and cloud data loss prevention as part of the Information Protection team at Symantec. Currently a second year MIMS student at UC Berkeley School of Information, he interned at PayPal Inc. during the summer as an Engineering Intern where he worked on enhancing merchant credit eligibility and decisions engine as part of Merchant Risk team. As part of this research project, he is looking forward to applying his quantitative research and software engineering skills to design and create sustainable program centered around the users in order to tackle the misinformation problem.
Caleb is a Ph.D. Candidate in the Department of Sociology at the University of California, Berkeley, where he studies the relationship between social institutions and the natural environment. He is especially interested in the entanglements of environmental politics, science, law, and technology. Caleb holds degrees in sociology, political science, and economics. His published work appears in Theory & Society, Theory Culture & Society, Science as Culture, Citizenship Studies, Ethics Policy and Environment, The Berkeley Journal of Sociology, and The New Handbook of Political Sociology (Cambridge University Press).
Alicia is a 2019 graduate of UC Berkeley with degrees in Society and Environment and
Interdisciplinary Studies where she focused on the nexus between technology, history and the environment. She has worked within research teams at the Democracy Collaborative, Pew Research Center, UC Berkeley and University of Indonesia. As a CTSP fellow, she will be exploring how disability disclosure varies across social networking platforms.
Project: Cybersecurity Graphic Materials
Franchesca is a recent UC Berkeley graduate who majored with an independent thesis on Bioethics & Design. For her thesis, she conducted ethnographic research on ethical design practices for assistive technology. Throughout her time at UC Berkeley, Franchesca also served as a Super User in the Invention Lab, and a Lab Manager for Karen Nakamura’s Disability Design Lab. She is currently involved in menstrual biosensing research, and actively works to change the discourse around the intersection of disability, sexuality, and technology.
Alicia is a second-year graduate student at UC Berkeley School of Information. Her work focuses on machine learning, optimization and natural language processing. Previously, she worked with the Nuclear Engineering department for proliferation detection using deep learning models and as a data science intern at LinkedIn.
Project: Data for Defenders
Rachel Warren is a first year masters student at the School of Information. She is interested in computational propaganda and bias in machine learning systems. Previously, Rachel worked as a software engineer and data scientists. She spent her career helping to build machine learning tools for people with little technical expertise, most recently for Salesforce. At Salesforce, she also served on an interdepartmental task force helping drive features to detect bias in machine learning systems. Since learning to code Rachel has sought out opportunities to teach technical skills, including working as full time computer science course assistant in Ghana, volunteering as a math tutor with Girls Inc of Alameda, and co-authoring a technical book called High Performance Spark.
Project: Regulating Medical Data Sharing
Reid Whitaker is Ph.D. student at the University of California Berkeley in Jurisprudence and Social Policy and a J.D. candidate at Stanford Law School (class of 2020). Reid’s research interests focus on the role of scientific and technical expertise in regulatory and judicial policy-making. He is especially interested in how health and environmental regulators respond to emerging technologies. Reid is also interested in the use of computational methods for researching law and governance. He was previously a fellow at the Harvard Law School Library Innovation Lab and is a Graduate Student Fellow at the Stanford Regulation, Evaluation, and Governance Lab (RegLab). At Stanford, Reid was Stanford Law Review’s first ever Quantitative Scholarship Editor. Before graduate school, he attended Carleton College where he studied Chemistry.
Projects: Data for Defenders
Jyen Yiee Wong is a UX designer and masters candidate at the UC Berkeley School of Information. She previously worked in a Neurobiology and Genetics laboratory, where she researched neurovascular contributions to Alzheimer’s Disease. While working as a research assistant, she concurrently volunteered as a UX designer at KnowScience, a non-profit aiming to promote science literacy among the public. Jyen Yiee is passionate about designing effective solutions that target the needs of underserved communities. She seeks to better understand the relationship between technology design and accessibility.
Richmond is a PhD candidate at the UC Berkeley School of Information. He studies how design methods and approaches can be used to proactively raise privacy and other social values-related concerns in technology design, and to develop technologies in ways that are cognizant of these issues. He also studies how representations of the future—such as through concept videos, provocative and speculative design concepts—help shape the ways people think about social values in the present. He uses interdisciplinary approaches drawing from human computer interaction, design, and science & technology studies and has published at venues including ACM CHI, CSCW, and DIS.
Sijia Xiao is a PhD student in the School of Information at the University of California,
Berkeley. Her research aims to understand how design decisions and moderation
mechanisms of online platforms shape online discourse. Her recent research studies
the social pressure of the young generation to present an idealized version of self on
social media and how the internet influences people’s beliefs in conspiracy theories.
Sijia Received her M.S. in Human-Computer Interaction in Georgia Institute of
Technology and her BS in Computer Science at Peking University.
Ji Su Yoo (she/her) is a PhD student in the UC Berkeley School of Information, where she focuses on how technologies affect privacy, trust, and information access. She has previously done research on developing data sharing guidelines, dataset anonymization, and privacy protections. Ji Su’s superpower is her knowledge about the unintended consequences of technology, and how technological solutions can exacerbate and maintain existing and historic inequalities.