Adam Pah is a Clinical Assistant Professor at the Kellogg School of Management and Organizations at Northwestern University. He received his BS from Arizona State University, PhD from Northwestern University, and has worked industrially as a Data Scientist.

He is a Co-Principal Investigator of the Systematic Content Analysis of Litigation EventS Open Knowledge Network (SCALES OKN), a NSF funded effort to transform the transparency and accessibility of court records. The SCALES OKN is a public platform that uses AI to surface insights into systematic patterns and behaviors in court records. The project's goal is to make it easy for lawyers, legal scholars, and journalists to transform difficult question about how the courts operate into easily obtainable information and answers. His primary research for the platform centers on building language models to understand how litigation proceeds, disambiguating entities, and quantifying the extent that legal outcomes vary within and between court districts.

More broadly, Adam is focused on understanding social phenomena that evolve over time and quantifying individual/group decision-making and performance when direct information is scarce. His research program draws from training in statistical and network-based methods and is focused on both population and individual-level data. This mixture leads to collaborations on a wide range of topics. His broader interests and projects include:

• Using EHR data to quantify physician diagnostic ability, model barriers to implementation, and improve change agent selection to include relative performance measures
• Structural determinants and evolution of school gun violence in the United States over time
• Identifying latent capabilities and prowess of covert organizations from observable actions 
• Developing Bayesian methods to quantify and control for behavioral contagion in time series
  

 

Innovation adoption in professional networks; Predicting social dynamics with missing network information; Healthcare networks and decision support; Social policy; Conflict; Contagion in time series; Racial disparities in educational access and attainment. 

• Ph.D., 2013, Biological Sciences, Northwestern University
• B.S., 2008, Biosciences & Biotechnology, Arizona State University, Tempe, Summa Sum Laude

• Postdoctoral Fellow, Chemical & Biological Engineering, Northwestern University, 2013-present
• Postdoctoral Fellow, General Internal Medicine, Northwestern University, 2013-2014
• Data Scientist, TTX Corporation, 2013-2013
• Data Scientist, Datascope Analytics, 2012-2012
• Visiting Scholar, The Donnelly Centre, University of Toronto, 2011-2011
• Student Researcher, Arizona State University, The Biodesign Institute, 2004-2008

• EFMD Case Writing Competition Winner - Bringing Technology to Market

Impact of artificial intelligence on business; designing and leading data science teams, departments, and initiatives; leveraging crowds for innovation; networks of trust in decentralized contracting systems.

Computational Social Science: Methods and Applications (KPHD-540-0)
This course is designed to prepare PhD students for computational social science (CSS) research. These skills include data acquisition, null model design and programming, and data mining for structured and unstructured data. Prerequisites: Students must be proficient in basic Python programming. Students may either take NICO 101-0 and NICO 102-0 or complete lessons on Datacamp (python for data science, data science toolbox, pandas, and importing data lessons).

Executive Development Program

The Kellogg Executive Development Program transforms organizational leaders. It equips top-performing, mid-level to senior managers to make decisions and take strategic action based upon both traditional and innovative business practices. Participants build skills and awareness as they realize their potential for assuming general management roles.

Leading Into the Future

As the world of business changes at breakneck speed, executives must stay at the forefront of management thinking and practice. This program delivers a wealth of new knowledge and insights for managing change with confidence in the 21st century.

Leveraging Artificial Intelligence for Innovation and Organizational Performance

Learn from Kellogg’s leading experts how to fully leverage AI for analytics, insight, strategy, and organizational growth. This program’s intuitive approach helps leaders enhance innovation, understand the impact of AI on work, and develop AI initiatives within their organizations.

The Strategy of Leadership

Your success as a leader ultimately depends on persuading others to adopt and run with your winning ideas. This program combines cutting-edge behavioral research with compelling interactive learning to improve your ability to work with and through others to drive business success.

Human & Machine Intelligence (MORSX-950-0)
This course focuses on the fundamentals of what artificial intelligence is, how it is applied in business, and why it is heralded as the next industrial revolution. This course requires no prior technical knowledge, starting with an examination of what machine learning and artificial intelligence is, how it functions, and where it excels. We progress to building AI models, exploring potential benefits and pitfalls of AI in comparison to traditional decision-making and how the two are complementary, and discussing best-practices on implementation at organizations. We cover both the historical origins of AI---including how IBM's Deep Blue and Google's AlphaGo beat Chess and Go Grandmasters--as well as modern applications across a broad range of business sectors and applications. This course is a lecture-based course with case-based discussions, group activities and projects, and a final individual assignment. The overarching goal for the course is to enable you to confidently lead data science and design teams, know the expansiveness and limits of AI, and be capable of applying human and machine thought partnerships to grow businesses or disrupt Grand Masters in any field.

Human and Machine Intelligence (MORS-950-5)
This course focuses on the fundamentals of what artificial intelligence is, how it is applied in business, and why it is heralded as the next industrial revolution. This course requires no prior technical knowledge, starting with an examination of what machine learning and artificial intelligence is, how it functions, and where it excels. We progress to building AI models, exploring potential benefits and pitfalls of AI in comparison to traditional decision-making and how the two are complementary, and discussing best-practices on implementation at organizations. We cover both the historical origins of AI---including how IBM's Deep Blue and Google's AlphaGo beat Chess and Go Grandmasters--as well as modern applications across a broad range of business sectors and applications. This course is a lecture-based course with case-based discussions, group activities and projects, and a final individual assignment. The overarching goal for the course is to enable you to confidently lead data science and design teams, know the expansiveness and limits of AI, and be capable of applying human and machine thought partnerships to grow businesses or disrupt Grand Masters in any field. MMM Class of 2019 should not enroll in this class as the content overlaps with DSGN 497-24