RISEI Lab (Research and Innovation for Social and Economic Inclusion Lab) is a research lab at Northwestern University directed by Dr. Michelle Yin. It advances rigorous, evidence-based work across technology and the future of work, workforce and disability, education and assessment, and global inclusion. The lab has $50M+ in lifetime funding and serves as evaluation partner for federal agencies including IES, NSF, DOL, and SEED grants.

Who is the director of RISEI Lab?

RISEI Lab is directed by Dr. Michelle Yin, Professor at Northwestern University's School of Education and Social Policy and former Senior Advisor to the U.S. Department of Labor. Her research has been featured in The Wall Street Journal and The Hill and published in Labour Economics, AERA Open, AERJ, and NBER Working Papers.

Where is RISEI Lab located?

RISEI Lab is based at Northwestern University, 633 Campus Drive, Evanston, Illinois 60208, within the School of Education and Social Policy.

What does RISEI Lab research?

RISEI Lab research spans four areas: Technology and the Future of Work (AI measurement and LLM occupational exposure, NBER Working Paper #35110), Workforce and Disability (subminimum wage elimination, vocational rehabilitation, Virginia EPIC, Maine P2P), Education and Assessment (NAEP process data, inclusive curriculum design), and Global Inclusion (Special Olympics Unified Champion Schools evaluation across 170+ countries).

How do I partner with RISEI Lab?

RISEI Lab partners with federal and state agencies, foundations, NGOs, and fellow researchers on evaluation, AI tooling, knowledge translation, and speaker engagements. Email risei@northwestern.edu or michelle.yin@northwestern.edu to start a conversation.

What does RISEI stand for?

RISEI stands for Research and Innovation for Social and Economic Inclusion, a research lab at Northwestern University's School of Education and Social Policy.

RISEI Lab · Northwestern University

RISEI Lab at Northwestern University: pushing research, innovation, and evidence forward.

RISEI is a research lab at Northwestern University advancing rigorous, evidence-based work across technology, workforce, education, and global opportunity. We produce peer-reviewed research, build AI-powered tools, design new curricula and apprenticeship models, serve as evaluation partners on federal and international grants, and translate findings into formats policymakers and practitioners can act on.

Explore the research → Work with us

AI Measurement Program

$50M+

Lifetime external funding

$4M+

Active federal support

170+

Countries reached

Flagship projects underway

§ 01 · RESEARCH AREAS

Four lines of inquiry, one thesis.

Marginalized populations are systematically under-measured, under-served, and under-represented. Our work produces the evidence — and the measurement infrastructure — to close that gap.

Technology & the Future of Work

How AI changes the calculus of employment for workers already on the margin. Measuring what current exposure frameworks miss, and building an Adaptive Precision Framework for policy under model uncertainty.

AI Measurement Labor Automation Policy Under Uncertainty

Enter research

Workforce & Disability

Vocational rehabilitation, subminimum wage elimination, and competitive integrated employment — the evidence base for what happens after Section 14(c).

VR Section 14(c) CIE

Enter research

Education & Assessment

How accessibility features in digital assessments shape outcomes for students with disabilities. Process-data methods, transitions, and the economics of inclusive schooling.

NAEP Transitions Inclusive Design

Enter research

Global Inclusion

Longitudinal evaluation of unified sports and inclusive programming across 170+ countries. Where attitudes shift, how high-school completion responds, and why the effects persist.

Special Olympics Attitudes Completion

Enter research

§ 01.5 · FEATURED PROGRAM

How AI exposure is measured is the measurement.

A two-paper program on the stability and identification of occupational AI exposure: instability within a fixed instrument across LLMs, and bias between instruments driven by who actually uses each AI platform. Together they argue for partial-identification bounds and continuous recalibration, not single-number exposure scores.

Figure 2: Three polar plots comparing theoretical AI capability against published exposure measures from Massolinik & McCrory, Anthropic Economic Index, and Microsoft Copilot

New · May 2026 · arXiv 2605.21743

The users in AI platform logs are not the workforce.

Yin, M., & Ogut, B. (2026)

Platform-derived exposure scores conflate task applicability with the occupational composition of each platform's user base. Switch only the platform input and the post-ChatGPT employment coefficient shifts by a factor of 1.9; consumer and enterprise channels of the same vendor disagree in sign.

1.9×

Coefficient shift, platform change only

42–93%

Attenuation after BLS reweighting

SOC groups, users vs. workforce

Read paper → arXiv ↗

Figure 3: E1 exposure across 95 occupations

April 2026 · NBER WP No. 35110

Four AIs rating the same 95 occupations give four different answers.

Yin, M., Vu, H., & Persico, C. (2026)

Exposure scores that drive workforce forecasts and policy diverge by 77 percentile points across major LLMs. Some occupations flip sign entirely — low-exposure on one model, high-exposure on another. We propose the Adaptive Precision Framework: continuous recalibration rather than frozen single-model judgments.

77pt

Max divergence across models

3.6×

Variance ratio

Occupations tested

Read paper & brief → NBER ↗

§ 02 · FLAGSHIP PROJECTS

Long-horizon commitments, built with states.

Two active federal model projects anchor the lab: Virginia's transition from subminimum wage employment, and Maine's multi-agency partnerships for youth with disabilities. Plus four more in the field.

U.S. Department of Education
Disability Innovation Fund

$4.29M

Virginia EPIC: Real pay for real jobs

Eliminating Section 14(c) subminimum wage for workers with disabilities across Virginia through evaluation, education, outreach, and capacity-building — in partnership with DARS and DBVI.

Active · 2022–2028 View project →

U.S. Department of Education
RSA Model Demonstration

$2.98M

Maine Pathways to Partnerships

Statewide collaborative model connecting vocational rehabilitation, special education, community partners, and employer networks to improve transition outcomes for children and youth with disabilities.

Active · 2023–2028 View project →

Institute of Education Sciences
Innovation Grant

IES

NAEP Process Data & Accessibility

Using process data from NAEP digital assessments to investigate how accessibility features affect mathematics performance for students with disabilities — and what the results imply for test design.

Active · IES funded View project →

Special Olympics International
Global Evaluation Partner

170+ countries

Special Olympics Global Evaluation

Longitudinal evaluation of unified sports and inclusive programming on social inclusion, high-school completion, and community attitudes — across more than 170 countries.

Ongoing · multi-year View program →

§ 03 · RECENT PUBLICATIONS

Working papers & policy briefs.

A selection of what's been shipped or is about to ship. The full portfolio is on the publications page.

2026

How (un)Stable Are LLM Occupational Exposure Scores?

Yin, Vu & Persico · NBER Working Paper #35110 · RISEI Policy Brief companion

New

2026

Making Time Count in Vocational Rehabilitation

Yin & Guerrero · Rehabilitation Counseling Bulletin (forthcoming)

Journal

2026

Something EPIC in Virginia: Progress on Eliminating Subminimum Wage

RISEI · Policy brief

Brief

2025

The Economic Imperative of Vocational Rehabilitation

Yin et al. · Peer-reviewed

Journal

2025

The Hidden Market: Disability Employment & the Gap We Aren't Measuring

RISEI · Policy brief

Brief

2025

The Uneven Playing Field of Workforce Participation

RISEI · Research report

Report

Read all publications →

Search the library

Looking for a specific paper, project, or dashboard?

Everything the lab has published, is running, or has shipped — in one place. Start typing to filter across 30+ items instantly.

18+Papers & briefs 4Research areas 3Flagship projects 5Dashboards

Browse everything → All papers All projects All dashboards

Director · Principal Investigator Michelle Yin, Ph.D.

§ 04 · THE LAB

Directed by Michelle Yin. Built by a distributed team.

Leading a $50M+ research portfolio at the intersection of workforce, education, and emerging technologies — with six senior advisors and a distributed bench of economists, postdocs, and research staff who ship papers and policy briefs, not just data.

$50M+

Lifetime funding

170+

Countries reached

Lab members

Meet the full team → Director biography ↗

Senior Advisors Six senior advisors spanning economics, psychometrics, and disability policy — from Rochester, Virginia, Stony Brook, AIR, and Third Sight.

Lead Economists & Postdocs Four lead economists with PhDs from Tennessee, American, Kansas, and Houston — plus two postdoctoral researchers at Northwestern.

Tulane U. · PhD, U. of Houston

Kathryn R. Johnson

Postdoctoral Researcher

+ The bench

Research staff & graduate assistants at Northwestern · five affiliates at AIR, American U., and beyond · four alumni who shipped papers with the lab.

See everyone →

Collaborate with the lab

Rigorous research, on a policy timeline.

We partner with agencies, foundations, advocacy organizations, and fellow researchers on evaluation, working papers, and policy briefs. Prospective students and postdocs: we review applications year-round.

Contact the lab →

General & Press

risei@northwestern.edu

Phone

847-491-7377

Address

633 Campus Drive
Evanston, IL 60208