- Leverage subject matter expertise in law to create, review, and optimize text prompts involving legal use cases, in order to train large language models through reinforcement learning from human feedback.- Evaluate the performance of large language models by testing, analyzing, and ranking outputs from large language models.

- Develop and maintain research agenda analyzing high-dimensional legal data using various methodologies. Collaborate with senior researchers to design and implement research studies, and select appropriate methodologies. Communicate findings to cross-functional audiences through presentations and reports. - Trained and implemented document embedding model using Python (Doc2Vec) to determine similarity between the text of Supreme Court legal opinions and approximately 10,000 amicus curiae briefs submitted by interest groups from 2005 to present. Assembled original dataset, including textual similarity scores and other theoretically relevant variables, for hierarchical regression analysis in R. - Built transformer-based text classifier using TensorFlow in Python to predict the origins of legislation from twenty congressional committees in the 112th and 113th sessions of Congress.Implemented and trained Google’s BERT text classification algorithm on Supreme Court oral arguments to predict the identity of a speaker when provided their comments. - Measured longitudinal influence of prior case law on recent judicial decisions by constructing social network of 38,261 judicial decisions from 1954 to 2013 (using degree and eigenvector centralities) in R. - Analyzed compliance with judicial decisions using multilevel regression modeling in R.- Evaluated the impact of multiple demographic indices on political preferences using multinomial logistic regression. - Compiled and maintained original dataset consisting of multiple indices of judicial independence for 195 countries. Used principal component analysis to identify indices that best measure judicial independence. - Provided instructional support to graduate students in advanced regression (e.g. logistic and multinomial regression, mixed models) and probability (e.g. distributions, functions of random variables). Designed curricula and practice problems in R, and held lab sessions to address students’ questions.

- Managed a team of graduate and undergraduate students in applying a variety of natural language processing techniques on a large corpus of NetApp product documents to evaluate their efficacy in communicating technically complex specifications to consumers. - Designed a research strategy to generate readability scores for NetApp product documentation from dictionary-based and machine learning techniques, including dimensionality reduction, informational entropy, and embeddings-based modeling. - Provided guidance to team members in crafting reports and visualizations detailing findings to stakeholders.

- Led a team of students to create a dynamic visual dashboard using Tableau to assist investment team at Duke University Management Company in reviewing individual and portfolio-level exposures across multiple financial asset classes and public market accounts. - Conducted user interviews with investment team to gather information relevant to dashboard design. - Coordinated with client stakeholders to provide updates on progress, ensuring the project remains on schedule and consistent with clients’ requirements and expectations.

- Provided recommendations to research team concerning appropriate research designs, scope and methods, data collection tools, protocols for data collection, data reliability, and data management. Offered quality assurance on data analysis issues during research projects. - Designed and disseminated three surveys on student civic participation and partisan attachment. Analyzed subsequent findings longitudinally, conducting sentiment analysis of open-ended survey responses.- Developed and deployed questionnaires for organizational clients to explore a variety of issues, including employee satisfaction, user experience, community needs, and public perceptions. Consult with research team on survey findings, offering insights that inform strategic recommendations for clients.- Employed QGIS to visualize regional trip generator locations for a study of potential regional transit hubs in northeastern Pennsylvania. - Co-authored policy analyses and technical reports with research team on a range of policy issues, including public-private sector apprenticeship investment, EITC expansion, cash bail reform, municipal consolidation and voluntarily disincorporation, and net neutrality.- Designed and facilitated focus groups and semi-structured interviews on stakeholder and consumer attitudes in market research and program evaluations (e.g. competitor analysis and communication strategy formation). Coded transcripts from interviews and focus groups in NVivo. - Provided guidance to college-level interns in research methodology and best practices. - Managed datasets of regional indicators in economic development, health, education, and crime. Prepared advisory memoranda analyzing indicators and offering recommendations, and presented findings to cross-functional community stakeholders. - Developed research protocols to meet institutional review board requirements, and helped develop codebooks for multiple community-based research projects and grant applications.

- Authored a white paper analyzing the dispersion of financial investment under the European Union’s current migrant integration policy.- Participated in weekly research seminars, and partnered with faculty and staff on workshop and conference reports in support of Perry World House’s 2017 research theme, Global Shifts: Urbanization, Migration, and Demography.

- Managed a team of interns in interpreting and researching the Justice Against Sponsors of Terrorism Act’s application to questions of international money laundering on behalf of an international law firm, in connection with pending litigation arising from the events of 9/11. - Determined and reviewed applicability of documentation recordings possible incidents of international money laundering offenses, ensuring compliance and confidentiality of all sensitive documentation. - Reported all disclosable material revealed by team’s investigation to a team of multiple stakeholders.

- Produced policy analysis of public-private sector apprenticeship investment on regional workforce development. - Analyzed quantitative research data from surveys of regional small business expansion.

Researched and wrote judicial memoranda on various legal questions concerning applications of the Fair Labor Standards Act, Federal Tort Claims Act, and Pennsylvania law on confessions of judgment. Provided briefings on these materials to law clerks as appropriate.

Coordinated with representatives of regional governments and local stakeholders to alert them to relevant legislation or regulations, and identify additional policy affecting them. Conducted stakeholder interviews to assess responses to regional implementation of state policy concerning human services funding.

Operated and updated database for constituent opinion tracking and outreach. Managed scheduling requests. Organized and presented casework for the review of the senator’s constituent advocate.