I am a computer scientist with an interest and experience in research and policy issues related to developing responsible artificial intelligence technologies for societal well-being and national security. I am a Full Information Scientist at RAND in their Engineering and Applied Sciences Department.
Prior to RAND, I was the 2022-23 AAAS Science and Technology Policy fellow at the National Science Foundation’s Artificial Intelligence (AI) Research Institutes program. I was part of the core team of the ExpandAI program. My research background is in building interpretable machine learning models that model scenarios where data come from novel, heterogeneous sources, often in limited training data settings, and that involve quantifying model uncertainties. I also work on ethical and governance aspects of AI.
I was the 2022 Mirzayan Policy Fellow at the National Academies of Sciences, Engineering, and Medicine, where I contributed to the work of the Committee on National Statistics on aspects of data governance. I am also a visiting scholar in the Department of Computer Science, at Dartmouth College and a member of the Association for Computing Machinery’s (ACM) US Technology Policy Committee and contribute to their policy pieces.
Honored to be the finalist for the Falling Walls Science Breakthroughs of the Year 2023, Engineering and Technology category.
Contributed to the policy paper, titled, Joint Principles for the Development, Deployment, and Use of Generative AI Technologies, Association for Computing Machinery Technology Policy Committee, Europe/US Technology Policy Committees, June 2023.
Honored to be invited by the UN Divison of Social and Economic Affairs for the Expert Group Meeting on the Implementation Of The Third United Nations Decade For The Eradication Of Poverty (2018-2027), UN Economic Commission of Africa, Addis Ababa, May 2023. (Paper and presentation)
Perspective on AI-assisted diplomatic decision-making during crises - challenges and opportunities, published in the Frontiers in Big Data-Cybersecurity and Privacy, May 2023.
Presented my work, “Understanding existential societal problems using a computational lens”, at AAAS Annual Meeting, March 2023 in Washington, DC.
Research paper on Accurate Intercensal Estimates of Energy Access to Track Sustainable Development Goal 7, published in EPJ Data Science, 2022.
I completed my postdoc from the Department of Computer Science, at Dartmouth. As a postdoc, I was awarded a grant from the Irving Institute for Energy and Society at Dartmouth to develop computational methods for understanding energy accessibility in developing economies.
I completed my Ph.D. in Computer Science from the State University of New York at Buffalo, where my doctoral work was awarded the Chih Foundation Research Award. Before my Ph.D., I was a researcher at Oak Ridge National Laboratory. I obtained my M.S. in Computer Science from the University of California, Riverside, where I received the Dean’s Distinguished Fellowship.
I have developed computational methods to map poverty and inequality (PNAS’17, IADB Working Paper’20), to forecast energy deficits given Sustainable Development Goals (EPJ-Data Science’22), to estimate economic well-being (ACM TDS’21), as well as to build secure biometric systems (IEEE TIFS’16, IEEE Access’20).
I have collaborated with the Overseas Development Institute, London, Datapop Alliance, and the Inter-American Development Bank, DC on using novel data and newer methods for human development.