Tricia Davies is the founder and CEO of The Public Good. She has worked for and advised policy makers, philanthropies, government leaders, nonprofit boards, international NGOs and local community-based organizations on program development, performance improvement and financial planning for 20 years. She has served as a board member and a volunteer to local and international community nonprofits and as an advocate for equity and diversity among NYC’s public schools. Tricia has an MPA from Columbia University’s School of International and Public Affairs. She has taught classes at SIPA and NYU-Wagner and is currently an Adjunct Professor at the NYU Tandon School of Engineering-CUSP teaching and advising student teams on urban planning and data science projects.
Interests: Media Consumption and Susceptibility to Misinformation
Michael Haupt is a doctoral research fellow at the Global Health Policy and Data Institute and a PhD student in Cognitive Science at University of California, San Diego. His current research involves using machine learning and social network analysis to investigate political mobilization, communication dynamics, and misinformation spread on social media.
Michael is interested in mentoring QMSS students interested in working on the spread of conspiracy theories and misinformation. For more information on the projects Michael is working on and how to get involved, email [email protected].
Laura Uguccioni is an alumna of QMSS. For her master’s thesis, she applied NLP techniques to Twitter data to explore the relationship between public spaces in New York City and well-being. Following her studies, she embarked on a career as a data scientist, joining KPMG’s AI Analytics & Engineering consulting practice. Most recently, she served as an Associate Director at KPMG’s Data Science Center of Excellence, specializing in NLP and probabilistic models. Currently, she is on an extended maternity break, cherishing time with her baby, studying Spanish while in Mexico, and working on personal data science projects.
GRE Writing Tutoring App - Brief project description
The project, the GRE Writing Tutoring App, seeks to harness the capabilities of Language Models (LLMs) to assist prospective graduate students in preparing for the GRE Writing exam. The primary objective is to create a tool that provides graded feedback on writing tasks, tailored specifically to the criteria of the GRE Writing exam. The overarching goal is to democratize access to GRE preparation resources, particularly for individuals who may not have the means to afford expensive training programs.
This project involves building an LLM App using LangChain. Some key components include prompt engineering, building AI agent workflows, evaluation, and building a demo. Based on evaluation results, fine-tuning approaches and costs will explored.
Interests: Data Science Entrepreneurship
Kevin is an early stage investor focused on data & cloud at .406 Ventures and has 8 years of technology advisory and investment experience working closely with software and data companies ranging from start-ups to F1000 enterprises. He spends a disproportionate amount of time within data science & ML given his personal interests and learnings developed through the QMSS program. A few companies that he’s actively involved with include: ClosedLoop, Promethium, Linea, ChaosSearch, and Telmai. Prior to joining .406, Kevin was an investor at BV Investment Partners where he focused on technology investments serving financial services, healthcare and the enterprise. Kevin began his career in technology investment banking at J.P. Morgan, and spent most of his time within enterprise software and tech-enabled services. He received his BA in Economics, Political Science, and Mathematics from The University of Connecticut, and his MA in Quantitative Methods from Columbia University. During his free time, he enjoys backpacking, scuba diving, skiing, and traveling, and is actively involved within Big Brothers Big Sisters as a big brother.
Kevin is interested in mentoring students who are thinking about using their data science skills in starting new ventures.
Jan Batzner is a Research Associate at Weizenbaum Institute Berlin, the German Internet Institute, and a Doctoral Researcher in Computer Science at Technical University Munich (TUM). His research focuses on Large Language Model Alignment. Jan graduated with a Master‘s in QMSS from Columbia University in New York City.
Before joining the Weizenbaum Institute, Jan worked for a leading hybrid cloud computing enterprise and has been recognized as a Fellow of the International Cooperation of Assigned Names and Numbers (ICANN) and the Bavarian Elite Academy (BEA).
Current Project:
Sycophancy, deceptive alignment, and (harmful) short-cuts in the learning process in AI training, all relate back to the need of better measurement and benchmarks. Jan is working on developing LLM Alignment Benchmarks in order to address some of the harms that sycophancy and deceptive alignment can produce. Motivating talented junior researchers for building Sycophancy Benchmarks and being part of the AI Alignment community, benefits society overall. Ideally we do contribute to mitigation and advance to the current state of evaluation, but most importantly is to get researchers with this QMSS innovation lab involved and part of the process of making conversational AI safer.
Fatema Alhashemi holds a Master of Public Administration in Development Practice and a Master of Arts in Quantitative Methods in the Social Sciences from Columbia University. She has worked as a researcher at organizations such as the Brookings Institution, the UN, ILO, and WFP for the past 8 years. Fatema has recently started managing a startup research initiative called Arabi Facts Hub, which seeks to combat misinformation in Arabic through using machine learning and AI technologies on data collected from fact-checking organizations throughout the Arab world.
Adam Arenson is professor of history at Manhattan College. He is the author of two award-winning books: The Great Heart of the Republic: St. Louis and the Cultural Civil War (Harvard University Press, 2011) and Banking on Beauty: Millard Sheets and Midcentury Commercial Architecture in California (University of Texas Press, 2018). He is co-editor (with Andrew Graybill) of Civil War Wests: Testing the Limits of the United States (UC Press, 2015), and (with Jay Gitlin and Barbara Berglund) of Frontier Cities: Encounters at the Crossroads of Empire (University of Pennsylvania Press, December 2012).
Arenson has published a half-dozen scholarly articles, as well written for The New York Times Disunion series, The Atlantic, The Washington Post, and History News Network. He has spoken about his Civil War Era research at the Library of Congress, the Jefferson National Expansion Memorial, Lincoln University Founder’s Day, the Autry National Center, Yale’s Gilder Lehrman Center for the Study of Slavery, Resistance, and Abolition, York University’s Harriet Tubman Institute for Research on Africa and its Diasporas, and the Buxton Homecoming, as well as at academic annual meetings.
Arenson holds an A.B. in History and Literature from Harvard and a Ph.D. in History from Yale. More about his research on U.S. history, memory, and visual culture can be found at http://adamarenson.com and https://manhattan.edu/campus-directory/adam.arenson
Innovation Lab Mentors
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