Dr. Bonnell shapes policy and advances administrative initiatives for the University’s $2 billion research enterprise as well as plays a leadership role in strategic planning for research and administers the development of new research facilities.

She also helps to oversee campus-wide research planning efforts, linkages between the University and industry, and the transfer of technologies from university laboratories to the public sector. In addition, she governs the research activities of Provostial Centers and Institutes, particularly those involving interdisciplinary collaboration.

Lindsey D. Cameron is an assistant professor of management and sociology at the Wharton School, University of Pennsylvania. She is also a fellow at the Institute for Advanced Study, the home of Albert Einstein. She received her Ph.D. in management from the University of Michigan. Her research focuses on how algorithmic management is changing the modern workplace, especially individual’s behaviors at work.

Professor Cameron has an on-going, seven-year ethnography of the largest employer in the gig economy, the ride-hailing industry, exploring how algorithms are fundamentally reshaping the nature of managerial control. She has studied how the COVID-19 pandemic is affecting gig workers on different platforms (e.g., TaskRabbit, Instacart, AmazonFlex) and is currently examining how ride-hailing drivers on three continents navigate disputes.

Professor Cameron’s work has been published in leading academic journals, including Organization Science, Journal of Applied Psychology, Organizational Behavior and Human Decision Process, Annual Review of Organizational Psychology and Organizational Behavior, and proceedings of the Association of Computing Machinery and the Academy of Management. She was awarded Poet and Quants Award, 40 under 40 award for MBA teaching.

Angela Chen is an MD/PhD candidate at the University of Pennsylvania, where she is pursuing her doctorate in Health Care Management and Economics at the Wharton School. Her research focuses on examining the impact of financial incentives in health care, improving access to care, and exploring surgical practice patterns. Angela was part of the inaugural Schwarzman Scholars cohort at Tsinghua University in Beijing.

Prior to returning to Penn, she conducted orthopedic research at Brigham and Women’s Hospital and collaborated with the China Health Partnership at the Harvard T.H. Chan School of Public Health. Angela earned her undergraduate degree from Wharton in 2016.

Natalie Gilbert is a second-year DATS student at the University of Pennsylvania and a Senior Data Scientist at AT&T’s Chief Data Office. There, she drives the development of innovative generative AI applications for various AT&T business units. Currently, she leads a major generative AI project designed to personalize training and coaching plans for all 30,000 of AT&T’s frontline employees, based on individual seller performance metrics.

Prior to her work in generative AI, Natalie spent four years at AT&T as a data engineer, tackling complex challenges in fraud and cybersecurity. Her focus was automating the end-to-end machine learning model development lifecycle to enable real-time fraud detection. Passionate about feature engineering and data quality analysis, she even spent time in call centers and retail stores to gain firsthand insights into fraudulent behavior and proactively develop new features.

Natalie holds a bachelor’s degree in Computer Science from Tufts University. She currently resides in Dallas, TX, where she actively mentors local high school students and data science students from Southern Methodist University. She is excited to be graduating with her master’s degree this coming spring and use what she’s learned to make a bigger impact on the field of data science.

Carleigh Jaques is a member of the Board of Directors of Flywire Corporation (FLYW), a global payments enablement and software company, delivering complex payments across a variety of industry verticals including Education, Travel, Healthcare and B2B. She serves on the Audit Committee.

Prior to joining Flywire, Ms. Jaques was most recently SVP, Global Head of Risk & Identity at Visa, Inc. During the course of her 15 year career at Visa, Ms. Jaques led a number of scaled strategic businesses and functions.

In her role as Global Head of Risk & Identity, Ms. Jaques was responsible for all aspects of the business which blocked over $40 billion in payments fraud annually across a number of sophisticated platforms including leading edge AI platforms. Prior to that, Ms. Jaques was the SVP, Global Head of Acceptance Solutions driving double digit growth across digital transactions, face to face acceptance, transit solutions and the Tap to Phone product lines. She also led Visa’s Strategy, Corporate Development and Venture activity from 2008 to 2016.

Earlier in her career, Ms. Jaques was a Managing Director at Deutsche Bank Securities Inc. focusing on financing and mergers & acquisitions for technology companies across enterprise software, data center, cybersecurity, mobile and hardware. Ms. Jaques has received numerous awards including being named among the Most Influential Women in Bay Area Business, Most Influential Women in Payments and a Top 100 Dealmaker. Ms. Jaques has spoken at The Wharton School as well as Stanford Law School on topics ranging from AI/ML to Innovation to Merger & Acquisitions.

Ms. Jaques holds a BA from the University of Michigan Honors Program in Political Science and French Language and an MBA from The Wharton School of The University of Pennsylvania.

Joyce Kline is Accenture’s Global Industrials Data & AI Lead.

Joyce has been helping clients define their digital capabilities across the extended organization, including how to become a data driven enterprise, how to derive benefits from AI and GenAI powered solutions, and how to embark on a digital transformation.

Prior to her current role, Joyce worked with Aerospace and Defense clients on various supply chain, customer service, and aftermarket projects. During the 20+ years with Accenture, Joyce has partnered with global organizations  to drive business transformation, revenue growth, and operational improvements.

Prior to joining Accenture, Joyce was employed at four different GE businesses and held various positions in manufacturing, sourcing and quality.

Joyce holds an MBA from MIT’s Sloan School of Management and a BSME from WPI. Joyce is based in Boston, Massachusetts.

Dr. Lilach Mollick is the Co-Director of the Wharton Generative AI Labs. Her work focuses on the development of pedagogical strategies that include artificial intelligence and interactive methodologies. She has worked with Wharton to develop a wide range of educational tools and games used in classrooms worldwide.

She has also written several papers on the uses of AI for teaching and training, and her work on AI has been discussed in publications including The New York Times and Vox. She advises companies and organizations on the advantages and risks of AI in teaching.

Edward Rose, M.D. and Elizabeth Kirk Rose, M.D. Professor
Director, Institute for Biomedical Informatics, University of Pennsylvania, Perelman School of Medicine
Vice President for Research Informatics, University of Pennsylvania Health System
Director, Division of Informatics, Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Perelman School of Medicine
Vice Dean of Artificial Intelligence and Computing, University of Pennsylvania, Perelman School of Medicine

Ragini Verma, PhD,  is a tenured professor of Radiology, Perelman School of Medicine, University of Pennsylvania. Dr. Verma is also the Associate Vice Chair of Radiology for Translation and Commercialization. Dr. Verma leads the Diffusion & Connectomics In Precision Healthcare Research (DiCIPHR) lab (https://www.diciphrlab.com/), building on her foundational training in math and computer science.

Dr. Verma focuses on patient-oriented neuroimaging research, aiming to understand disease-related, developmental and sex-based structural and functional connectivity alterations in the brain. She leads multisite clinical studies  in autism, brain tumors and traumatic brain injury, as well as pre-clinical studies to understand mechanistic underpinnings of neuroimaging findings.

Monica Vyavahare is currently pursuing an MBA at The Wharton School, majoring in Finance and Management. Prior to Wharton, she worked as a Senior Software Engineer at Amazon Robotics, and holds both a BSE and MSE in Computer Science from the University of Pennsylvania, with a specialized focus on Data Science.

Lynn Wu is an Associate Professor at the Wharton School of the University of Pennsylvania, where she teaches MBA, undergraduate, and doctoral courses on the transformative impact of emerging technologies on business and society.

Her research focuses on the intersection of artificial intelligence, analytics, and innovation, exploring how these technologies reshape business strategy, productivity, and workforce dynamics. Specifically, her work spans three core areas:

1. AI and Innovation: Examining the effects of AI on business processes, innovation, labor outcomes, and productivity across both large enterprises and startups.
2. Digital Platforms and Bias: Investigating how enterprise social media and AI-driven platforms influence employee performance, career trajectories, entrepreneurial success, and the emergence of new biases associated with technological adoption.
3. Antitrust and Policy: Studying the antitrust implications of emerging technologies and advising on related matters for various agencies such as the U.S. Department of Justice.

Lynn’s research has been published in leading journals across economics, management, and computer science, earning numerous accolades, including Early Career Awards from INFORMS and AIS, as well as best paper awards from Information Systems Research, ICIS, CHITA, and Kauffman. Her work has been widely cited by major media outlets, including NPR, The Wall Street Journal, The New York Times, The Economist, and Forbes. She is also a recipient of Wharton’s Dean’s Teaching Award for her excellence in education.

Lynn holds undergraduate degrees in Finance and Computer Science from MIT, a master’s degree in Computer Science from MIT, and a Ph.D. in Management Science from MIT Sloan School of Management. Prior to academia, she worked as a software engineer and research scientist at the MIT AI Lab and IBM. She has also collaborated with leading technology companies (e.g., IBM, Google, Meta, SAP), advised government organizations (e.g., the Department of Justice, the World Bank), and consulted for innovative startups.

With a unique blend of academic rigor and industry expertise, Lynn is passionate about uncovering insights at the frontier of technology and business, helping organizations navigate the challenges and opportunities of a rapidly evolving digital economy.

Susan B. Davidson is an American computer scientist known for work in databases and bioinformatics. She is Weiss Professor of Computer and Information Science at University of Pennsylvania. Her dissertation work on distributed databases included results on statistical and mathematical techniques for data resolution as well as mechanisms to avoid database conflicts.

Susan has also done research in bioinformatics, where her work (with collaborators) on data integration was commercialized by GeneticXChange. She also serves on the board of the Computing Research Association.

Linda Zhao is a Professor of Statistics and Data Science at the Wharton School of the University of Pennsylvania. She is a Fellow of the Institute of Mathematical Statistics. Linda specializes in modern machine learning methods.

After getting her PhD in Mathematics/Statistics from Cornell University, Linda taught in UCLA, Los Angeles for one year. She joined the Wharton School in 1994. She obtained a Bachelor of Science degree from the Mathematics department of Nankai University, China.

Linda’s research area covers from Bayesian analysis, nonparametric analysis and numerical computation. She mainly publishes in international leading journals. Current on going projects include forecasting house prices, inference for high dimensional data, data with measurement errors and post model selection inferences. Linda also enjoys teaching very much.