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Team Spring 2022

Team Spring 2022, COMPSCI/ECON 206 Computational Microeconomics, Duke Kunshan University

Published onMay 25, 2022
Team Spring 2022
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Instructor, Duke Kunshan University

Prof. Luyao Zhang| Ph.D.

Prof. Luyao Zhang| Ph.D.

Website| LinkedIn | Twitter | GitHub

Research: Luyao (Sunshine) Zhang is Assistant Professor of Economics and Senior Research Scientist at the Data Science Research Center at Duke Kunshan University (DKU). She has an abiding passion for interdisciplinary collaborations, especially those related to Computational Economics (Algorithmic Game Theory and Mechanism Design), Artificial Intelligence (Machine Learning, AI Trust, Human-Computer Interaction), Cryptoeconomics (Blockchain for social good, DeFi, and Consensus Algorithms), Behavioral Science (Bounded Rationality, Trust, and Cooperation), and Interdisciplinary Big Data (Social Media, Sustainability, and Global Health). Her publications appear in economic journals for general interest and beyond, including American Economic Review: Papers and Proceedings, the Review of Economics and Statistics, the World Economy, Nature Scientific Data, ACM CCS, ACM AIES, Remote Sensing, Journal of Digital Earth, Data and Information Management, etc. She received Ph.D. in Economics at Ohio State University, supported by Presidential Fellowship and NSF dissertation grant. She graduated from Peking University with a B.A. in Economics and a B.S. in Math and Applied Math. She holds a blockchain strategy certificate at Oxford University and more than 30 data science certificates. 

Teaching: She has taught economics courses and beyond for students with diverse backgrounds in the U.S., Europe, and China, proposing an Artificial Intelligence and Business Strategy initiative. She has won several teaching prizes for innovation in research-oriented and project-based education. She is passionate about promoting undergraduate research and Scholarship of Teaching and Learning (SoTL). The courses entitled “Intelligent Economics: An Explainable AI Approach” and “Computational Microeconomics” that she developed in this spirit have been listed in the undergraduate curriculum across disciplines. She led the Duke CS+ project entitled “Decentralized Finance: Cryptocurrency and Blockchain on the Internet Computer” with professors in Computer Science and industry pioneers. She is currently leading an “Industry 4.0 Open Education Resource Publication Initiatives” supported by Duke Learning Innovation Center and DKU Center for Teaching and Learning under the Carrying the Innovation Forward program. As an adjunct faculty at New York University (NYU) Shanghai, she taught statistics courses in Integrated Marketing at the School of Professional Studies and core courses in Economics such as Econometrics and Game theory in the Summer Program.

Service:  Luyao has dedicated herself to service with empathy, which she believes is one critical cornerstone of any civil society. She has served the academic community and beyond. She serves on the research policy committee, the advisory board of the mind group as social science division representative and the faculty advisor program for student care at Duke Kunshan University. She also is the associate editor for IEEE Transactions on Computational Social System and the ambassador in Shanghai for Startup Genome. She is the Founding President for SciEcon CIC, NPO registered in the UK, aiming to cultivate integrated talents in research, innovation, and leadership. She was the Founding President of Dance Illumination, an NPO with 501 (c)(3) tax-exempt status to promote diverse dance histories.

Distinguished Guest Speaker, Duke University

Prof. Vincent Conitzer| Ph.D.

Speaker bios: Vincent Conitzer is the Kimberly J. Jenkins Distinguished University Professor of New Technologies and Professor of Computer Science, Professor of Economics, and Professor of Philosophy at Duke University. He is also Head of Technical AI Engagement at the Institute for Ethics in AI, and Professor of Computer Science and Philosophy, at the University of Oxford. He received Ph.D. (2006) and M.S. (2003) degrees in Computer Science from Carnegie Mellon University, and an A.B. (2001) degree in Applied Mathematics from Harvard University. Conitzer works on artificial intelligence (AI). Much of his work has focused on AI and game theory, for example designing algorithms for the optimal strategic placement of defensive resources. More recently, he has started to work on AI and ethics: how should we determine the objectives that AI systems pursue, when these objectives have complex effects on various stakeholders? Conitzer has received the 2021 ACM/SIGAI Autonomous Agents Research Award, the Social Choice and Welfare Prize, a Presidential Early Career Award for Scientists and Engineers (PECASE), the IJCAI Computers and Thought Award, an NSF CAREER award, the inaugural Victor Lesser dissertation award, an honorable mention for the ACM dissertation award, and several awards for papers and service at the AAAI and AAMAS conferences. He has also been named a Guggenheim Fellow, a Sloan Fellow, a Kavli Fellow, a Bass Fellow, an ACM Fellow, a AAAI Fellow, and one of AI's Ten to Watch. He has served as program and/or general chair of the AAAI, AAMAS, AIES, COMSOC, and EC conferences. Conitzer and Preston McAfee were the founding Editors-in-Chief of the ACM Transactions on Economics and Computation (TEAC).

Teaching Assistants, Duke University

Zeyu Shen| Undergraduate, Class of 2023

 LinkedIn | Twitter | GitHub

Zeyu Shen is an undergraduate at Duke University majoring in Math and CS. His research interest lies at the crossroads of algorithmic design and analysis, machine learning, and social science, such as algorithmic game theory, computational social choice, and algorithmic fairness. He wants to leverage his background in computer science to mitigate existing social problems, many of which are exacerbated or created by suboptimal technologies themselves. His publications have appeared in top venues such as ACM Conference on Economics and Computation (EC) and Conference on Neural Information Processing System (NeurIPS). He wants to pursue a PhD in computer science in the future, with a concentration in the intersection of Econ and CS. Aside from research, Zeyu is also interested in problem solving and teaching. He has been the teaching assistant for the Problem Solving Seminar (Math 283S) at Duke for two years, and will be the instructor of this course in the coming semester.

Yinhong Zhao| Undergraduate, Class of 2023

LinkedIn | Twitter | GitHub | Website

 Yinhong “William” Zhao is a junior student majoring in economics and math. He intends to pursue a Ph.D. in economics after his graduation. William’s research interests include development economics, blockchain, and microfinance. Interested in the economic efficiency of blockchain networks, William’s works have been accepted at journals and conferences including ACM Conference on Computer and Communications Security (ACM CCS 2022), Scientific Data, and Equilibria: Duke Undergraduate Economics Journal. He is also serving as teaching assistants for “Innovation and cryptoventures” for Prof. Campbell Harvey at Duke Fuqua and “Data science and econometrics” for Prof. Duncan Thomas at Duke. In his future career, William hopes to pioneer the uses of blockchain technology in developing countries to provide those less fortunate with economic resiliency.

Xinshi Ma | Undergraduate, Class of 2024

LinkedIn | Twitter | GitHub |

Xinshi (Evan) Ma is an undergraduate at Duke University majoring in Economics and Computer Science. His areas of interest include blockchain, decentralized finance, health economics and other topics at the crossroads of data science and economics. He is passionate about leveraging data to gain insights on economic issues that impact policy implementation. His works have appeared in venues such as the Academy Health Annual Research Meeting and the Global Finance Conference. He is a teaching assistant for Principles of Economics for Prof. Thomas Nechyba at Duke. Besides academics, Evan is also loves soccer and the outdoors.

Teaching Assistants, Duke Kunshan Unversity

Xinyu Tian | DKU UG Class of 2023

LinkedIn | Twitter | GitHub

Xinyu Tian is a junior student majoring in Data Science at Duke Kunshan University (DKU) and a full admission scholarship recipient in DKU. Her area of interest includes theory and applications about cooperative AI, blockchain trust and consensus, game theory, and computer vision. Her paper about meta-learning algorithm has been published in 2021 International Conference on Computer Engineering and Application (ICCEA) and she was supported by the Summer Research Scholarship (SRS) program at Duke Kunshan University in 2021 and 2022. She is now working on her Signature Work about cooperative AI mentored by Prof. Luyao Zhang. Besides her academic interest, she also hopes to support the communication between academia and industry. So she is serving as Chair of Communication at SciEcon CIC and contributing to the industry 4.0 Open Educational Resources (OER) Series No. 1 as a chapter author and No.2 as a student manager.

Tianyu Wu| Undergraduate, Class of 2023

LinkedIn | Twitter | GitHub

 Tianyu Wu is a junior student majoring in Applied Mathematics and Computational Science at Duke Kunshan University (DKU), full admission scholarship recipient, and 2019-2020 National Scholarship recipient. His area of interest includes blockchain, cryptocurrency, and algorithmic game theory. He is now carrying out Signature Work, similar to Honor Thesis, mentored by Prof. Luyao Zhang, entitled “Computational Mechanism Design: build a credible economy by automated auction and voting designs on blockchain.” He also serves on many pioneering projects for the great cause of research, innovation, and leadership supervised by Prof. Zhang. First, he was a student project lead of “How Fintech Empowers Asset Valuation: Theory and Applications” for the Summer Research Scholar Program at Duke Kunshan University in 2021 and co-authored a conference paper entitled “A Data Science Pipeline for Algorithmic Trading: A Comparative Study in Applications to Finance and Cryptoeconomics.”  Moreover, he is among the Teaching Assistants for the interdisciplinary research course: “Econ 211 Intelligent Economics: An Explainable AI approach” in Autumn 2021, contributing to the industry 4.0 Open Educational Resources (OER) Series No. 2 as a student contributor; Finally, he also contributed to “Innovate on the Internet Computer”, industry 4.0 OER Series No. 1 as the student project manager. 

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