Check-in, enjoy breakfast and networking and opening remarks by Dean Eckles, MIT Sloan

• Session Chair: David Holtz (UC Berkeley, MIT IDE)
• Jake Hofman (MSR) “An Illusion of Predictability in Scientific Results”
• Jana Gallus (UCLA Anderson) “The Social Fabric of Work”

Enjoy a coffee break

• Session A: The Information Ecosystem
• Session B: Experimentation in the Presence of Interference
• Session C: E-commerce and Online Platforms

Enjoy lunch and the first half of poster slam presenters (second half on day 2 during lunch)

In order of presentation:

• Session Chair: Dean Eckles (MIT Sloan, MIT IDE)
• Tom Griffiths (Princeton) “From Running Experiments to Running Algorithms with People”
• Kris Ferreira (HBS) “Improving Human Algorithm Collaboration: Causes and Mitigation of Over-and Under-Adherence”

Enjoy a coffee break

• Session D: Advertising
• Session E: Tools for Experimentation and Causal Inference
• Session F: Development

Enjoy a coffee break

• Session G: Algorithmic Recommendations
• Session H: Sequential Testing
• Session I: Education

A Discussion of the Challenges of Conducting Experiments in Industry Contexts Featuring Data Scientists and Researchers from a Number of Prominent Firms.

• Moderator: Dean Eckles (MIT Sloan, MIT IDE)
• Dana Chandler (Hinge)
• Samantha Emanuele (Etsy)
• Rina Friedberg (LinkedIn)
• Che Sharma (Eppo)

Enjoy a networking reception and the chance to view work from all of our poster presenters (both day 1 and 2 posters will be on display)

See you for day 2!

Check-in, enjoy breakfast and networking and opening remarks by Dean Eckles, MIT Sloan

• Session Chair: Dean Eckles (MIT Sloan, MIT IDE)
• Garrett Johnson (BU Questrom) “Inferno: A guide to Field Experiments in Online Display Advertising”
• Hamsa Bastani (Wharton) “Lessons from Reinforcement Learning in Public Health”

• Session J: Human-Computer Interaction
• Session K: Heterogeneous Treatment Effects and External Validity
• Session L: Consumer Choice

Enjoy a coffee break

A Dynamic Conversation on Blockchain, Cryptocurrencies and Web3 Featuring Prominent Researchers in the Space

• Moderator: Sinan Aral (MIT Sloan, MIT IDE)
• E. Glen Weyl (Microsoft)
• Hanna Halaburda (NYU Stern)
• Neha Narula (MIT Digital Currency Initiative)
• Catherine Tucker (MIT Sloan)

Enjoy lunch and the second half of poster slam presenters.

In order of presentation:

• Session M: Bayesian Experimentation
• Session N: Non-Myopic Experimentation
• Session O: Novel Experiment Designs and Estimators

Enjoy a coffee break!

• Session Chair: Dean Eckles
• Solene Delecourt (Berkeley Haas) “Online Gender Stereotypes are Stronger in Images than Text”
• Eytan Bakshy (Meta) “Challenges in Adaptive Experimentation at Scale”

• David Holtz – CODE@MIT 2022 Organizer

Enjoy the closing networking reception and the chance to view work from all of our poster presenters (both day 1 and 2 posters will be on display)

Event concludes

Sinan Aral a global authority on business analytics; award-winning researcher; entrepreneur and venture capitalist. He is the David Austin Professor of Management, Marketing, IT and Data Science at MIT, Director of the MIT Initiative on the Digital Economy (IDE) and a Founding Partner at Manifest Capital. He was the Chief Scientist at SocialAmp, one of the first social commerce analytics companies (until its sale to Merkle in 2012) and at Humin, a social platform that the Wall Street Journal called the first “Social Operating System” (until its sale to Tinder in 2016). He is currently on the Advisory Boards of the Alan Turing Institute, the British National Institute for Data Science in London, the Center for Responsible Media Technology and Innovation in Bergen, Norway and C6 Bank, one of the first all-digital banks of Brazil. Sinan has helped leading Fortune 500 firms, including Facebook, Yahoo!, Twitter, LinkedIn, Snapchat, WeChat, Spotify, AirBnB, Microsoft, Walmart, IBM, Intel, Cisco, Oracle, SAP and The New York Times to realize business value from big data analytics, social media and IT investments. His research has won numerous awards including the Microsoft Faculty Fellowship, the PopTech Science Fellowship, an NSF CAREER Award, a Fulbright Scholarship and the Jamieson Award for Teaching Excellence (MIT Sloan’s highest teaching honor). In 2014, he was named one of the “World’s Top 40 Business School Professors Under 40.” In 2018, he became the youngest ever recipient of the Herbert Simon Award of Rajk László College in Budapest, Hungary. In the same year, his article on the spread of false news online was published on the cover of Science magazine and became the second most influential scientific publication of the year in any discipline. Sinan’s first book, The Hype Machine, which was named a 2020 Best Book on Artificial Intelligence by WIRED, a 2020 Porchlight Best “Big Ideas and New Perspectives” Book Award Winner and among the Best New Technology Books and Best New Economy Books to Read in 2021 by BookAuthority, became an instant classic and a must-read for business leaders at every level of management. A managerial economist and econometrician by training, Sinan’s expertise spans social networks, causal inference, the design and analysis of large-scale digital experiments, machine learning, predictive modeling, natural language processing, AI, big data, marketing, IT, social commerce, ecommerce, behavior change and economic productivity. He earned his PhD at MIT and completed his Master’s degrees at the London School of Economics and at Harvard. You can find Sinan on Twitter @sinanaral and on Instagram @professorsinan.

Eytan Bakshy is a director and research scientist at Meta, where he leads the Adaptive Experimentation team. Their work focuses on developing practical and robust methods for sequential experimentation for real-world applications. Eytan’s research interests include Bayesian optimization, Bayesian machine learning, multi-armed bandits, and active learning. Much of his work earlier has focused on the use of randomized experiments and causal inference in understanding social behavior, including influence and information diffusion in networks.

Hamsa Bastani is an Assistant Professor of Operations, Information, and Decisions at the Wharton School, University of Pennsylvania. Her research focuses on developing novel machine learning algorithms for data-driven decision-making, with applications to healthcare operations, social good, and revenue management. Her work has received several recognitions, including the Wagner Prize for Excellence in Practice (2021), the Pierskalla Award for the best paper in healthcare (2016, 2019, 2021), the Behavioral OM Best Paper Award (2021), as well as first place in the George Nicholson and MSOM student paper competitions (2016).

Dana is a Data Science Manager at Hinge (the dating App). He is an MIT-trained Data Scientist (PhD Economics) with over 10 years of data science experience across multiple domains and industries including: tech companies, data science consulting, and finance. At Hinge, he enjoys working with great colleagues and using data to help people find their match.

Solène Delecourt is an Assistant Professor at UC Berkeley in Management of Organizations (Haas School of Business). She studies gender inequality in business performance and online using novel data and experiments. She is also a Faculty Affiliate at the Center for Effective Global Action and an Invited Researcher as part of the Gender and Economic Agency Initiative at J-PAL. Her work on these topics has appeared in the Strategic Management Journal and Management Science.

She holds a PhD from the Stanford Graduate School of Business (2020).

Dean Eckles is an Assistant Professor of Marketing at MIT Sloan.

His substantive research examines people’s interactions with and through communication technologies, especially how these technologies mediate, amplify, and direct social influence. This work sometimes requires or benefits from new analytical methods, so Eckles also works on applied statistics, design of field experiments, and causal inference.

Prior to joining MIT, he was a scientist at Facebook, where he worked on many product areas and analytical methods, including News Feed, messaging, advertising, tools for randomized experiments, and survey methods. Eckles previously worked in research at Nokia and Yahoo.

Eckles received his BA in philosophy, a BS and MS in cognitive science,  an MS in statistics, and a PhD in communication, all from Stanford University.

Samantha Emanuele is a Staff Data Scientist at Etsy and specializes in experimentation and measurement techniques. With over 7 years experience working in analytics, she has held previous roles at an ad tech company called The Trade Desk, and J.Crew. Samantha holds an MPH in Biostatistics from Yale University along with a Bachelor of Science in Mathematics and Statistics from George Washington University. Outside of analytics, Samantha enjoys traveling and spending time with her dog, Cavatelli.

Kris Ferreira is an Assistant Professor at Harvard Business School in the Technology and Operations Management (TOM) Unit. She teaches the Supply Chain Management course in the MBA elective curriculum and analytics in various Executive Education programs. In her research, Kris focuses on helping e-commerce companies make more profitable revenue-management decisions, including pricing, assortment planning, ranking, etc. For much of this work, she partners with online retailers to design new machine learning and optimization algorithms that use the massive amount of data at their fingertips to improve their decision making in this domain. Most recently, Kris has started studying how users make decisions with such algorithmic input, and correspondingly how to improve algorithmic development and deployment.

Kris’s work has been awarded the M&SOM Best OM Paper in OR Award, two-time finalist for the M&SOM Best Paper Award, first place for the Revenue Management and Pricing Section Practice Award, finalist for the M&SOM Practice-Based Research Competition, and first place and finalist for the Innovative Applications in Analytics Award. Kris earned her PhD in Operations Research at the Massachusetts Institute of Technology and her BS in Industrial and Systems Engineering at the Georgia Institute of Technology. Before entering graduate school, she was a supply chain consultant for Alvarez & Marsal.

Rina Friedberg is a senior data scientist at LinkedIn, specializing in experimentation and causal inference research. She focuses on practical problems in data science, including hypothesis testing under differential privacy and quantifying demographic representation changes in large-scale A/B testing systems. She has previously worked in global health statistics, studying clinical trials to evaluate gender-based violence prevention programs for adolescents in Nairobi. Friedberg received her BS in mathematics from the University of Chicago and a PhD in statistics from Stanford University.

Jana is an Associate Professor of Strategy and Behavioral Decision Making at UCLA’s Anderson School of Management. She studies incentives and organizational design. Much of her work has focused on analyzing the effects of nonfinancial incentives on motivation, performance, well-being, and inclusion in the knowledge economy. Methodologically, Jana mostly uses field experiments. Her collaboration partners include organizations such as NASA, Wikipedia, the American Red Cross, hospitals, schools, and various private sector firms, mostly in tech. She consults for organizations in the private and public sectors, such as the European Commission. She serves as an Associate Editor for Management Science, as a Standing Panelist for the NSF, and as a reviewer for several journals across different fields.

Jana’s work has been published in Management Science, Psychological Review, Proceedings of the National Academy of Sciences, Organizational Behavior and Human Decision Processes, Strategic Management Journal, and Applied Economics, among other journals. She is the coauthor of Honours versus Money: The Economics of Awards, Oxford University Press.

Jana joined UCLA from Harvard and received her PhD in Economics (summa cum laude) from the University of Zurich in Switzerland.

Tom Griffiths is the Henry R. Luce Professor of Information Technology, Consciousness and Culture in the Departments of Psychology and Computer Science at Princeton University. His research explores connections between human and machine learning, using ideas from statistics and artificial intelligence to understand how people solve the challenging computational problems they encounter in everyday life. Tom completed his PhD in Psychology at Stanford University in 2005, and taught at Brown University and the University of California, Berkeley before moving to Princeton. He has received awards for his research from organizations ranging from the American Psychological Association to the National Academy of Sciences, and is a co-author of the book Algorithms to Live By, introducing ideas from computer science and cognitive science to a general audience.

Hanna Halaburda joined New York University Stern School of Business as an Associate Professor of Technology, Operations and Statistics in September 2019.

In her research, Professor Halaburda studies how technology changes economic forces and thus affects business models and interactions in the marketplace. One strand of her work focuses on competition between digital platforms. Since 2011, she has built a research program in digital currencies and blockchain technologies, including analyses of incentives in consensus protocols, cryptocurrency adoption, smart contracts, and token issuance. Professor Halaburda’s work has been published in Management Science, RAND, American Economic Journal, Games and Economic Behavior, and other academic journals. In 2015 she co-authored Beyond Bitcoin: The Economics of Digital Currency, the first book analyzing digital currencies from the economic perspective. The book’s 2nd edition, co-authored with Miklos Sarvary and Guillaume Haeringer, was published by Palgrave Macmillan in 2022.

Prior to joining NYU Stern, Professor Halaburda was an Assistant Professor at Harvard Business School, and a senior economist at the Bank of Canada.

She holds Master’s degrees in Economics from the Warsaw School of Economics and in Philosophy from Warsaw University, and a PhD in Economics from Northwestern University.

Jake Hofman is a Senior Principal Researcher at Microsoft Research in New York City, where he works in the field of computational social science. Prior to joining Microsoft, he was a Research Scientist in the Microeconomics and Social Systems group at Yahoo! Research. He holds a B.S. in Electrical Engineering from Boston University and a Ph.D. in Physics from Columbia University. He is an Adjunct Assistant Professor of Applied Mathematics and Computer Science at Columbia University and runs Microsoft’s Data Science Summer School to promote diversity in computer science. His work has been published in journals such as Science, Proceedings of the National Academy of Sciences, and Management Science, and has been featured in popular outlets including The New York Times, The Wall Street Journal, The Financial Times, and The Economist.

I am an assistant professor in the Management of Organizations (MORS) and Entrepreneurship & Innovation groups at the Haas School of Business at UC Berkeley. I am also a research affiliate at the MIT Initiative on the Digital Economy, and faculty affiliate at the Berkeley Institute for Data Science. My research broadly focuses on the design of online marketplaces and platforms.

Prior to graduate school, I worked full-time as a data scientist in Silicon Valley, most recently at Airbnb. I hold a PhD in Management (Information Technology) and an SM in Management Research from the MIT Sloan School of Management, an MA in Physics & Astronomy from Johns Hopkins University, and an AB in Physics (with a certificate in Theater & Dance) from Princeton University.

My preferred pronouns are he/him/his.

To learn more about my research, please visit my google scholar page or download my full curriculum vitae.

Garrett Johnson researches digital marketing: measuring its effectiveness and examining its privacy issues. His ad effectiveness research uses large-scale experiments to measure how and how much ads work. His privacy research both examines the impact of Europe’s GDPR and studies the economics of identity in online advertising. For his work, Prof. Johnson has been awarded the Paul Green Award, Weitz-Winer-O’Dell Award, and the John D. C. Little Award, and has been a finalist for the John D. C. Little Award and Gary Lilien Marketing Science Practice Prize.

Neha Narula is the Director of the Digital Currency Initiative at the MIT Media Lab, where her research interests are in cryptocurrencies and distributed systems. She is on the Innovation Advisory Council for the Federal Reserve Bank of New York and the Blockchain, Crypto and Digital Currencies advisory council for Paypal. Neha has given a TED talk on the future of money and was named to WIRED’s list of 25 leaders shaping the next 25 years of technology. She received her PhD in computer science from MIT in 2015, where she published work on fast, scalable databases and before that was a senior software engineer at Google.

Che Sharma is the Founder & CEO of Eppo, a next gen AB experimentation platform that is designed to spur entrepreneurial culture. As the 4th data scientist at Airbnb and early data scientist at companies like Webflow, Che has been focused on the maturity curve of growth stage companies and how to establish data as a central stakeholder of decision making. Che previously led the team that developed Airbnb’s knowledge repo, and has led data teams focused on production machine learning and instrumentation integrity.

Catherine Tucker is the Sloan Distinguished Professor of Management Science and Professor of Marketing at MIT Sloan. She is also Chair of the MIT Sloan PhD Program.

E. Glen Weyl is Political Economist and Social Technologist at Microsoft Special Projects, where he is incubating a cluster around Web3 research for the company, and Founder of the RadicalxChange Foundation, the leading thinktank in the Web3 space. He previously led Web3 technical strategy at the Office of the Chief Technology Officer. He is co-author with Eric Posner of the 2018 Radical Markets: Uprooting Capitalism and Democracy for a Just Society, with Puja Ohlhaver and Vitalik Buterin of the 2022 paper “Decentralized Society: Finding Web3’s Soul” (which is one of the 30 most downloaded papers of all time on the Social Science Research network) and is working on an open, Web3-based collaborative book project with Taiwan’s Digital Minister, Audrey Tang, on which this talk is based. He has been recognized as one of the 10 most influential people in blockchain by CoinDesk, as one of the 25 people shaping the next 25 years of technology by WIRED and as one of the 50 most influential people by Bloomberg Businessweek, all in 2018. He graduated as Valedictorian of his Princeton undergraduate class in 2007 and received his PhD in economics also from Princeton in 2008.