Richeng (Ryan) Piao

Teaching

Microeconomic Theory, Macroeconomics, Game Theory & Information Economics, Industrial Organization, Econometrics, Applied Statistics, Applied Data Analytics, and Statistical & Machine Learning for Economics.

Research

Industrial organization and platform economics; algorithmic pricing and antitrust; causal inference and machine learning; the labor-market and pedagogical effects of generative AI.

• Northeastern University

  August 2021

  Ph.D. in Economics — Industrial Organization

• University at Albany, State University of New York

  May 2012

  B.S. in Economics (Honors Program) and B.S. in Mathematics

• Director of AI Teaching Innovation

  August 2026 – June 2027

  College of Social Sciences and Humanities, Northeastern University

  • College-level appointment under Northeastern's Curricular Transformation Initiative, funded by the Offices of the Provost and Chancellor, to build faculty AI capacity across CSSH.
  • Convene and lead a faculty community-of-practice cohort that experiments with AI-aware teaching, exchanges discipline-specific practice, and evaluates the effectiveness of redesigned activities and assessments.
  • Design and deliver workshops and collegial programming that meet faculty across the novice–expert spectrum, grounded in the university AI Readiness framework and Assessment & AI Task Force guidance.
  • Built and maintain the CSSH “AI in Teaching” faculty resource hub: plain-language policy guidance, copyable syllabus statements, an AI-resilient assignment toolkit, and a gallery of interactive classroom examples.
  • Co-convene the collegewide AI showcase with the Director of AI Curricular Transformation, featuring faculty work and employer perspectives on AI in the workplace; administer a $10,000 innovation grant budget.

• Assistant Teaching Professor of Economics

  2024 – Present

  Department of Economics, College of Social Sciences and Humanities

Department of Economics, Northeastern University, Boston, MA

• Statistical & Machine Learning for Economics (ECON 3916)

  Spring 2026 – Present
  • Built a unified curriculum bridging classical econometrics and data science through a “Concept Extension” pedagogy that scales statistical foundations to high-dimensional machine learning.
  • Covered causal machine learning (Double ML, causal forests), high-dimensional regression, NLP for economists, and predictive modeling with pandas, scikit-learn, and EconML.
  • Delivered dual-modal instruction pairing theory seminars with computational laboratories in Google Colab.

• Applied Data Analytics in Economics (ECON 5200)

  Spring 2025 – Present
  • Developed the “Foundations First, Expansion Second” curriculum, which sequences manual Python coding (OLS and DiD derivation) before generative-AI tooling is introduced.
  • Designed the P.R.I.M.E. Prompting Framework, positioning students as junior analysts who use AI to scale analysis while retaining rigorous economic verification.
  • Integrated experiential learning with real-world BLS and FRED data in Python and Jupyter.

• Game Theory (ECON 1916)

  Fall 2025 – Present
  • New course preparation: designed a full curriculum on strategic decision-making, Nash equilibrium, dynamic games, and asymmetric information.
  • Built interactive in-class simulations and case studies connecting formal models to real strategic settings.

• Microeconomic Theory (ECON 2316)

  2023 – Present
  • Taught calculus-based intermediate theory: utility maximization, demand, cost minimization, equilibrium, and strategic decision-making.
  • Examined market imperfections — public goods, externalities, asymmetric information, imperfect competition — with emphasis on policy implications.

• Information Economics & Game Theory (ECON 4681)

  2020 – Present
  • Designed an applied curriculum on strategic interaction across economics, politics, and business.
  • Facilitated in-class games and case analysis covering Nash equilibria, evolutionary game theory, repeated interaction, and asymmetric information.

• Principles of Microeconomics (ECON 1116)

  2019 – Present
  • Active-learning lectures on supply and demand, elasticity, market structure, and externalities using current events.
  • Mini-projects including price-elasticity estimation from CPI and CES data; fieldwork assessing market competitiveness in real retail settings.

• Principles of Macroeconomics (ECON 1115)

  2017 – Present
  • Lectures on GDP, inflation, unemployment, and business cycles grounded in historical and contemporary crises.
  • Group projects using World Bank indicators, synthesized across groups in class; post-pandemic monetary policy including the IORB rate.

• Applied Econometrics (ECON 2560)

  Summer 2023

• Applied Statistics for Economics (ECON 2560)

  Fall 2022

• Money and Banking (ECON 3442)

  2016 – 2017

• Principles of Microeconomics — Interactive Open Textbook

  ECON 1116 · 2025 – Present
  • Complete draft of a 19-chapter, ~202,000-word interactive principles textbook with manipulable economic visualizations in place of static figures, written to replace a commercial textbook.
  • Every chapter ships as a unit: draft, podcast, auto-graded homework, quiz bank, interactive charts, in-class attendance activities, and lecture deck. All 19 chapters now have decks.

• Microeconomic Theory — Calculus-Based Text

  ECON 2316 · 21 chapters, rebuilt 2026
  • Rebuilt around a 37-meeting Fall 2026 course map that fixes scope against actual contact hours, with per-chapter cut lists so scheduling decisions are made in advance rather than improvised.
  • Includes an audio edition, a TA plan, and explicit protection for department-required topics (Cournot, Stackelberg, Bertrand, uncertainty and information asymmetry).

• Data Science & Statistical Learning for Economists

  ECON 3916 / 5200 · dual-track
  • One text serving an undergraduate and a graduate course: shared foundations through measurement, sampling, estimation, and inference, then track-specific chapters.
  • 3916 continues to SQL and multivariate OLS prediction; 5200 to difference-in-differences, instrumental variables, and regression discontinuity, before both converge on bias–variance, regularization, and classification.

• Assessment & Course Automation Infrastructure

  2025 – Present
  • Built a reproducible generator for auto-graded homework and quiz banks across five item types with LaTeX math support, covering every chapter of the principles sequence.
  • Developed an API-driven Canvas LMS deployment pipeline that builds complete course modules — gated prerequisites, weighted gradebook structure, quiz imports, consistent styling — programmatically rather than by hand.

• Lecture, Animation & Media Pipelines

  2025 – Present
  • Built a reveal.js lecture-viewer application with presenter mode, dual-monitor sync, pacing indicators, and WCAG-compliant themes, replacing slide-deck software across every course.
  • Authored in-class attendance activities and a podcast for every chapter, with live in-lecture polling wired to a datastore so class responses render on the slide.
  • Produce Manim-based economics animations and a pipeline that converts textbook chapters into teaching videos.

• CSSH AI in Teaching Resource Hub

  2026
  • Designed and published a faculty-facing hub translating university AI policy into plain language, with copyable syllabus statements, AI-resilient assignment redesign patterns, a disclosure template, and a gallery of live interactive classroom examples.

Working Paper

• Algorithmic Pricing and Market Conduct: Evidence from Airbnb Smart Pricing

  2026

  Uses a sharp regression discontinuity around Airbnb's September 2023 platform-wide rollout of redesigned pricing tools across eight major U.S. cities. Price-level point estimates are positive in all eight cities (0.5–1.9 percent), but inference with only eight city clusters cannot rule out zero, bounding the effect between −0.5 and +1.9 percent. Heterogeneity tracks local regulatory stringency.

Research in Progress

• Platform API Pricing and Open-Source Software Ecosystems

  How do platform API pricing changes affect the open-source software built on them?

• Antitrust & Algorithmic Pricing Consultation

  2025

  Patrick Malone & Associates, P.C.

  • Advised legal practitioners on antitrust claims involving Airbnb and algorithmic pricing software.
  • Provided expert input on econometric identification (RDD and fuzzy RDD) and structural demand estimation to quantify consumer-welfare effects in digital platform markets.

• Director of AI Teaching Innovation, College of Social Sciences and Humanities

  2026 – 2027
  • Lead faculty AI capacity-building across CSSH under Northeastern's Curricular Transformation Initiative; convene the faculty community-of-practice cohort and co-convene the collegewide AI showcase (full description under Academic Appointments).

• Chair, Diversity, Equity, Inclusion & Belonging (DEIB) Committee

  2025

  Department of Economics, Northeastern University

  • Led the department's first DEIB climate survey assessing faculty and student belonging.
  • Launched the “XChange Lunch” series to build cross-cultural mentorship and community.

• Member, CSSH AI Readiness Committee

  2025 – Present
  • Contribute to college-level strategy on AI pedagogy and curriculum adaptation across CSSH.

• Member, Economics Graduate Admissions Committee

  2025 – Present
  • Review graduate applications to identify and recruit high-potential candidates.

• Faculty Advisor & Research Mentor

  2025 – Present
  • Directed Studies supervisor for undergraduate research projects (Spring and Summer 2025); faculty member of the Economics Graduate Students Association.

Languages & Tools

Python (pandas, NumPy, scikit-learn, statsmodels, EconML, Matplotlib), R (ggplot2, caret, glmnet), SQL, Stata, Jupyter, Git/GitHub, LaTeX, Tableau, AWS.

Methods

Structural demand estimation (BLP), difference-in-differences and event study, regression discontinuity (sharp and fuzzy), instrumental variables, panel methods, causal machine learning (Double ML, causal forests), high-dimensional regression, clustering, NLP.

Teaching Technology

Canvas LMS and its REST API, H5P interactive content, QTI assessment authoring, reveal.js, Next.js/React, Manim, Remotion, PollEverywhere, Canva.

Languages

Native in Chinese and Korean; fluent in English.

• Google Data Analytics Professional Certificate2025
• IBM Data Science Professional Certificate2021
• Ph.D. Fellowship, Northeastern University2012 – 2021
• Gordon Karp Award for outstanding achievement in Economics, University at Albany2012
• Dean's List, University at Albany2009 – 2012

• Curricular Transformation Initiative Director Kickoff Retreat, Northeastern University — September 2026.
• CATLR: “Navigating Uncertainty in Higher Education” and “Teaching in Uncertain Times” — 2025.
• ADVANCE Office of Faculty Development: Faculty Fellowship Inspiration Session — 2025.