The National Law Review and Wickard are proud to announce the Top 50 Legal Innovators in Academia for 2026, a national recognition honoring the educators, administrators, researchers, and academic leaders who are shaping the future of legal education. The recognition highlights individuals who are developing innovative programs, conducting impactful research, modernizing curricula, launching new centers and initiatives, and preparing students to meet the evolving demands of the legal profession.

Honorees were selected through an independent Selection Committee process, described more fully in the Selection Methodology below. The Committee included: Dean Neel Sukhatme, University of Michigan Law School Dean; Stefanie Lindquist, WashU Law; Judge Joshua Deahl, D.C. Court of Appeals; Bridget McCormack, President & CEO, American Arbitration Association; Robert Ambrogi, Founder and Journalist, LawSites; Sara Miro, Managing Attorney-Director, KM Solutions, Sullivan & Cromwell; Evan Shenkman, Chief Knowledge & Innovation Officer, Fisher Phillips; Pablo Arredondo, Co-Founder, CaseText, and Innovation Fellow at the Legal Information Institute; Dean Darby Dickerson, President & Dean, Southwestern Law School; Phil Saunders, CEO, Relativity; Andrew Woolf, Chief Strategy and Innovation Officer, Cozen O’Connor; and Stephanie Goutos, Chief AI Officer, Littler.

As part of NLR’s and Wickard’s “Commitment to Integrity,” there was no fee to submit a nomination, and selection was not tied to sponsorship, advertising, or any other paid or non-paid relationship with NLR or Wickard. Neither NLR nor Wickard held voting or selection rights in the Selection Committee’s decision-making process. Wickard personnel, NLR personnel, and members of the Selection Committee were ineligible for recognition. Committee members also recused themselves from reviewing or voting on any nominee with whom they had a conflict of interest.

The resulting 2026 class reflects a broad range of contributions to the continued evolution of legal education, from curricular and institutional innovation to scholarship, technology, and new models of professional training. The 50 honorees are presented below in alphabetical order.

2026 Honorees

Presented alphabetically by last name.

Ifeoma Ajunwa

Asa Griggs Candler Professor of Law and Founding Director of the AI and the Future of Work Program, Emory University School of Law

As the Asa Griggs Candler Professor, Associate Dean for Projects and Partnerships, and founding director of Emory Law's AI and the Future of Work Program, she leads the law school's first initiative devoted to AI training, experiential student learning, and interdisciplinary research on the use of AI across workplaces, businesses, and the professions. Ajunwa's scholarship has supplied a foundational framework for understanding algorithmic hiring, automated worker evaluation, workplace surveillance, privacy, discrimination, and the increasing quantification of employees.

Benjamin Alarie

Osler Chair in Business Law, University of Toronto / Co-founder & CEO, Blue J

Alarie is the Osler Chair in Business Law at the University of Toronto and co-founder and CEO of Blue J. His work connects legal scholarship with artificial intelligence and predictive legal analytics, including technology designed to support legal research and analysis.

John P. Anderson

Dean and Henry Vaughan Watkins and Selby Watkins McRae Professor of Law, Mississippi Christian University School of Law (formerly Mississippi College School of Law)

Under his deanship, Mississippi College School of Law became the first law school in Mississippi and the Southeast to require all first-year students to complete a certification in AI and the law. Beginning in spring 2026, the certification provides foundational instruction, hands-on experience with AI-powered legal tools, formal assessment, and education concerning the ethical, regulatory, and policy issues arising from AI's use in legal practice.

Jonathan Askin

Professor of Clinical Law, Brooklyn Law School

Jonathan Askin has spent more than two decades building institutions, communities, and educational models that redefine how law engages with technology, entrepreneurship, public policy, and access to justice. As the founder of the Brooklyn Law Incubator & Policy (BLIP) Clinic at Brooklyn Law School, Askin created one of the nation's first technology-focused legal clinics and one of the most influential models for experiential legal education.

Kathleen (Katie) Brown

Associate Dean for Information Resources, Charleston School of Law

Katie Brown's work focuses on how technology is taught, measured, and applied in legal education. Her recent scholarship examines who is responsible for building technology competence in ABA-accredited law schools and how those expectations translate into curriculum and training.

Ryan Calo

Virginia and Prentice Bloedel Professor, University of Washington School of Law

As a founding co-director of the UW Tech Policy Lab and co-founder of the Center for an Informed Public, he has created durable platforms for research and student engagement on artificial intelligence, robotics, privacy, cybersecurity, and digital governance. Calo's scholarship has provided foundational legal frameworks for understanding how emerging technologies affect consumers, institutions, and civil society.

Seth J. Chandler

Beirne, Maynard & Parsons, L.L.P. Professor of Law, University of Houston Law Center

Chandler has converted decades of computational legal scholarship into three concrete contributions to legal education. His “augmented seminar” lets students use AI to develop topics and test arguments while holding them fully responsible for sourcing, verifying, and defending every claim, a model that produced a published 289-page student anthology. His course Large Language Models for Lawyers moves instruction from demonstration to practice, and his free platform, legaled.ai, shares his course designs and experiments with faculty nationwide.

Adam S. Chilton

Dean, Howard G. Krane Professor of Law, and Walter Mander Research Scholar, University of Chicago Law School

Since becoming dean of the University of Chicago Law School in July 2025, Chilton has overseen a rapidly expanding AI strategy that includes required AI modules for first-year students, integration of AI tools into clinical education, guidance for responsible AI use in legal research and writing, and expanded upper-level coursework on generative AI and law. Under his leadership, the Law School also launched an AI Lab in which students do more than learn to use existing tools.

Kirsten K. Davis

Professor of Law, Stetson University College of Law

Kirsten Davis was among the first legal writing scholars to treat generative AI as a paradigm shift rather than a classroom-integrity problem. Her essay “A New Parlor Is Open” argued that legal communication faculty must research how AI reshapes the discipline's core questions rather than simply policing its use. She translated that scholarship into one of the earliest AI-specific legal writing courses, founded a national peer-learning group that now includes more than 550 faculty members, and served as her university's Provost's Fellow for Generative AI, earning the Legal Writing Institute's 2026 Mary Lawrence Innovation Award.

April Dawson

Professor of Law at Howard University School of Law and Faculty Director of the Howard Law AI Initiative.

Since August 2026, April Dawson has been a Professor of Law at Howard University School of Law and Faculty Director of the Howard Law AI Initiative. Previously, Dawson served as the inaugural Associate Dean of Technology and Innovation and Professor of Law at North Carolina Central University School of Law, where she led the NCCU Technology Law & Policy Center (TLPC).

Gregory M. Duhl

Professor of Law, Purdue Global Law School

Professor Gregory Duhl gives students the innovation legal education promises but rarely delivers. While much of the profession spent the last few years afraid of AI, banning it, policing it, and treating it as something to catch, Professor Duhl rebuilt his entire first-year Contracts course around it, so students learn to supervise, critique, and outperform AI rather than hide from it.

Niva Elkin-Koren

Director, Chief Justice Meir Shamgar Center for Digital Law and Innovation, Faculty of Law, Tel-Aviv University

Niva Elkin-Koren's work in pioneering a transformative model of interdisciplinary legal education in responsible AI was revolutionary. The innovative teaching methodology addresses a fundamental weakness in conventional legal education: AI cannot be governed or regulated responsibly within disciplinary silos.

Kevin Frazier

Director for the AI Innovation and Law Program at the University of Texas School of Law

As founding director of the AI Innovation and Law Program at the University of Texas School of Law, Frazier has built one of the more visible platforms for AI legal education. He co-hosts the Scaling Laws podcast, giving students an accessible way to follow AI policy developments; publishes an open-source syllabus on AI governance that other faculty have adopted; and produces scholarship on AI agents, elections, and the rule of law that has helped shape ongoing policy debates.

Jon Garon

Associate Dean for Technology and Innovation at NSU Florida Shepard School of Law; Director of the Goodwin Program for Society, Technology and the Law

Garon has built one of the most comprehensive technology programs in legal education, from founding the Law + Informatics Institute at Northern Kentucky to leading NSU Law's Advanced Legal Technology Certificate, which combines in-class training with hands-on modules spanning every year of a student's J.D. alongside continuing legal education for practicing attorneys. A prolific scholar with more than 100 published articles, books, and chapters on technology and intellectual property law, he was named a CALI Fellow in Constitutional Law in 2026.

Naomi Goodno

Dean of Students and AI Innovation, Professor of Law, Executive Director of the Quattrone Wrongful Convictions Appellate Clinic, Co-Director of Trial Advocacy Programs, Pepperdine Caruso School of Law

Award-Winning, School-Wide Innovation Professor Naomi Goodno created and chairs P(AI)R for Lawyering, Pepperdine Caruso School of Law's school-wide AI readiness initiative, which received the 2026 Excellence in Innovation: Law Schools Award from Insight Into Academia. P(AI)R stands for "Pepperdine AI Readiness for Lawyering" and reflects the program's central purpose: pairing practical AI fluency with the judgment, values, and professional responsibility required for effective lawyering.

Daniel James ("Jim") Greiner

The Honorable S. William Green Professor of Public Law & Faculty Director, Access to Justice Lab, Harvard Law School

As part of his effort to transform law into an evidence-based field, Jim Greiner has pioneered the use of randomized field experiments in the legal profession. Although earlier scholars had conducted occasional, one-off randomized trials, none had recognized the central importance of randomization in persuading the legal profession to reduce its disdain for evidence-based thinking.

Leah Chan Grinvald

Dean and Richard J. Morgan Professor of Law, William S. Boyd School of Law, University of Nevada, Las Vegas

Beginning in fall 2026, Boyd Law will require 1Ls to complete Introduction to the Responsible Use of AI, a course providing hands-on experience with generative and agentic AI while emphasizing professional judgment, client service, human oversight, and the principle that a task should not be delegated to AI merely because the technology can perform it. Students will examine platform strengths and weaknesses, ethical obligations, prompt engineering, bias, and the use of AI in foundational first-year subjects such as Contracts and Civil Procedure.

Maura Robin Grossman

Research Professor, David R. Cheriton School of Computer Science, University of Waterloo; Faculty Member, Vector Institute for Artificial Intelligence; Visiting Professor, Duke University

Grossman has repeatedly changed how the legal profession understands, evaluates, and adopts artificial intelligence. She established the empirical foundation for technology-assisted review, demonstrating that well-designed machine-learning workflows could outperform traditional manual review while remaining transparent, defensible, and measurable.

Neel Guha

Associate Professor, Columbia Law School

Neel Guha holds advanced training in both law and computer science—a JD from Stanford Law School and a PhD in computer science from Stanford, advised by Christopher Ré—a combination held by very few legal academics. His principal contributions are to legal AI evaluation: the measurement of how well AI systems perform legal tasks.

Gillian K. Hadfield

Bloomberg Distinguished Professor of AI Alignment and Governance, Johns Hopkins University

As a Bloomberg Distinguished Professor at Johns Hopkins, she bridges law, economics, computer science, and public policy. Her research on AI alignment and computational models of normative systems addresses a foundational challenge: how advanced AI systems can operate consistently with legal and social expectations.

Sean A. Harrington

Director of the AI & Legal Tech Studio, Sandra Day O’Connor College of Law at Arizona State University

Sean Harrington is nominated for building, not just describing, the future of AI in legal education. At ASU Law's AI and Legal Tech Studio, he has turned a new initiative into a working program: production AI tools used daily across the College and its clinics, a hands-on AI and the Practice of Law course, and a proprietary AI learning system for ASU Law's new JD Online program.

Woodrow Hartzog

Andrew R. Randall Professor of Law, Boston University School of Law

His work has changed how scholars and policymakers understand privacy by demonstrating that legal outcomes are embedded not only in statutes and policies, but also in the architecture and defaults of digital systems. His books, including Privacy's Blueprint and Breached!, have become touchstones for scholars, technologists, and policymakers grappling with how design choices shape privacy and security outcomes.

Daniel E. Ho

William Benjamin Scott and Luna M. Scott Professor of Law; Professor of Political Science; Professor of Computer Science, Stanford University

Through Stanford's Regulation, Evaluation, and Governance Lab, Ho leads interdisciplinary teams that work directly with government agencies to evaluate and deploy AI using rigorous empirical methods. RegLab's work combines law, machine learning, causal inference, and public-sector implementation rather than treating AI governance as a purely theoretical problem.

Daniel W. Linna Jr.

Professor of Instruction in Law and Computer Science & Director of Law and Technology Initiatives, Northwestern Pritzker School of Law & McCormick School of Engineering

Linna works at the intersection of law, technology, data, and legal-service innovation. At Northwestern, he directs law and technology initiatives spanning the law school and engineering school and develops interdisciplinary approaches to technology-enabled legal practice.

Johanna Kalb

Dean and Professor of Law, University of San Francisco School of Law

Dean Kalb recognized early on that legal education needed to evolve in order to prepare graduates for the current practice of law. Thanks to her foresight and leadership, USF was the first law school in the country to integrate AI learning outcomes into the required core curriculum.

Daniel Martin Katz

Professor of Law and Director of the Law Lab, Illinois Tech Chicago-Kent College of Law

As Professor of Law and Director of the Law Lab at Chicago-Kent, he has built an interdisciplinary model that integrates law, data science, machine learning, engineering, and entrepreneurship. His earlier work testing GPT systems on the bar exam helped establish a concrete benchmark for evaluating large language models in legal reasoning and became one of the most widely cited studies in the field.

Megan Ma

Executive Director, liftlab, Stanford Law School

At Stanford Law School, Megan Ma is building an applied AI lab of its own kind: one focused not on technology for its own sake, but on the human questions at the heart of the profession and the challenge of defining what quality means in the legal space. Ma's research centers on developing "AI twins" for attorneys: systems designed to capture, model, and extend the tacit judgment and practical wisdom of practicing lawyers.

Thomas G. Martin

Adjunct Professor, Suffolk University Law School

Tom Martin has shaped how generative AI is taught in legal education. Over two years teaching his Suffolk Law course, Generative AI and the Delivery of Legal Services, he built a textbook and workbook giving the field one of its first structured curricula for teaching applied legal AI.

Nicole Morris

Professor of Practice and Director of the IP & Innovation Clinic and the TI:GER Program, Emory University School of Law

Professor Morris has helped position Emory Law at the intersection of law, technology, and innovation through her leadership of the TI Program and the IP & Innovation Clinic. Through TI, she leads an innovative experiential program in which law students work directly with scientists and technology innovators, including researchers at Department of Energy National Laboratories, to evaluate emerging technologies and develop commercialization and licensing strategies, giving students hands-on experience translating technological innovation into real-world legal and business solutions.

Korin Munsterman

Professor of Practice and Director of Legal Education Technology, UNT Dallas College of Law

Munsterman earns this recognition because she has done more than adopt AI in her own classroom; she has built structures that let other educators and practitioners do the same. While many law schools were still debating whether to permit generative AI, she was already teaching it, and she turned that head start into a technology-competency requirement that defines and tracks the skills students must demonstrate before they enter practice.

Michele Benedetto Neitz

Professor of Law and Founder and Academic Director of the Center for Law, Tech, and Social Good, University of San Francisco School of Law

As founder and academic director of the University of San Francisco School of Law's Center for Law, Tech, and Social Good, she has developed an academic center that functions as both a research institution and a training ground for future lawyers, lawmakers, regulators, and policy professionals. Under Neitz's leadership, USF Law has developed an AI & Emerging Technology Law Certificate that provides students with structured training in legal doctrine, ethics, regulation, and practical technology use.

Tracy L. M. Norton

Assistant Professor of Law; Erick Vincent Anderson Professorship, LSU Paul M. Hebert Law Center

Long before generative AI became the central technology question in law schools, she was building tools that helped faculty teach more effectively and helped students learn with more feedback and less mystery. The Interactive Citation Workbook alone changed the daily teaching practice of many legal writing programs.

Julian Nyarko

Professor of Law and Faculty Director of liftlab, Stanford Law School

As co-chair of the Stanford Law AI Initiative and faculty leader of liftlab, Nyarko directs one of the first academic programs to unite legal-AI research, technology prototyping, and collaboration with law firms and industry partners. His recent scholarship has produced important infrastructure for legal-AI research.

Dyane O'Leary

Assistant Dean and Professor of Legal Writing, Suffolk University Law School

At Suffolk Law, she has helped build one of the nation's leading legal innovation and technology programs while keeping the focus squarely on students and the practical skills they need to serve clients in a rapidly changing profession. Her work is distinctive because it bridges several worlds that too often remain separate: legal writing, professional skills training, legal technology, generative AI, ethics, and the delivery of legal services.

Jonah Perlin

Professor of Law, Legal Practice, Georgetown University Law Center

Professor Jonah Perlin is a Professor of Law, Legal Practice at Georgetown University Law Center and a Senior Fellow at the Georgetown Center on Ethics and the Legal Profession. He is also the host of the How I Lawyer podcast, creator of the Standout Summer Associate newsletter, and Chair-Elect of the AALS Section on Professional Responsibility.

Andrew M. Perlman

Dean and Professor of Law, Suffolk University Law School

Under his deanship, Suffolk Law moved beyond offering advanced legal-technology electives and integrated generative AI training directly into the mandatory first-year Legal Practice Skills curriculum. Beginning in the 2025–26 academic year, every incoming student completes a tailored AI learning track addressing large language models, professional responsibility, risks and limitations, and practical legal applications.

Nancy B. Rapoport

UNLV Distinguished Professor Garman Turner Gordon Professor of Law, William S. Boyd School of Law Affiliate Professor of Business Law and Ethics, Lee Business School

Rapoport built her reputation as one of the country's leading scholars of bankruptcy ethics and professional responsibility, including service as a law school dean and as fee examiner in major bankruptcies such as Toys “R” Us and Caesars, before turning that same rigor toward artificial intelligence. She co-launched one of the first courses at an ABA-accredited law school on the responsible use of AI in legal practice, centered on teaching students to critically evaluate AI-generated content while keeping human judgment at the center of legal work, and co-authored A Short & Happy Guide to the Ethics of Using AI.

Paul Rose

Dean and Professor of Law, Case Western Reserve University School of Law

Dean Rose led Case Western Reserve University School of Law in becoming the first law school in the United States to require every first-year student to complete certification in legal artificial intelligence. Dean Rose championed AI's integration into the foundational curriculum, ensuring that all graduates develop practical competence in emerging technologies, ethical obligations, regulatory developments, and responsible professional use of AI.

Matthew A. Salerno

Associate Professor of Lawyering Skills and Co-Director Legal Writing, Leadership, Experiential Learning, Advocacy, and Professionalism, Case Western Reserve University School of Law

Professor Salerno helped lead Case Western Reserve University School of Law’s pioneering AI initiatives, including launching a required 1L program through which every first-year student designed and prototyped an AI-powered legal technology tool and overseeing the school-wide 2026 Vibe Coding Competition. He has also helped integrate legal technology into the required curriculum, ensuring that students gain hands-on experience with emerging tools.

Matthew Sag

Jonas Robitscher Professor of Law in Artificial Intelligence, Machine Learning, and Data Science, Emory University School of Law

As the Jonas Robitscher Professor of Law in Artificial Intelligence, Machine Learning, and Data Science at Emory, he has helped define the legal framework for determining when AI training and AI-generated outputs implicate copyright law. His work is particularly influential because it connects traditional fair-use doctrine with the technical realities of model training, memorization, data extraction, and generative outputs.

Alexandria Serra

Associate Professor, University of San Francisco School of Law

Professor Alexandria Serra is helping redefine how law schools prepare students for a profession increasingly shaped by artificial intelligence and emerging technology. Her innovative work sits at the intersection of generative AI, experiential learning, and advocacy education, with a focus on a critical question: how can law schools use AI not simply to teach students about technology, but to help them become better lawyers? She has designed and implemented fifteen AI-powered advocacy tools, including simulated hot-bench and witness-preparation programs, and her article on reinventing advocacy training received the 2025 Stetson National Advocacy Writing Competition Award.

Chinmayi Sharma

Associate Professor, Fordham Law School

Chinmayi Sharma conceived, developed, pitched, and secured Fordham Law School's approval to host the Fordham Law ACTech Challenge in partnership with the Atlantic Council, a first-of-its-kind annual competition and curricular program focused on AI and emerging technology governance. Law schools have long trained students through moot court, trial advocacy, negotiation, and arbitration, but those formats do not fit AI governance problems; the ACTech Challenge closes that gap by placing students inside a fast-moving AI crisis where they must deliver decision-useful counsel to simulated boards, executives, and regulators.

Harry Surden

Professor of Law and Director of the Silicon Flatirons Artificial Intelligence Initiative, University of Colorado Law School

A former software engineer, he was among the earliest legal scholars to treat AI and machine learning as distinct technical systems requiring careful legal analysis rather than generalized speculation. His scholarship on computable contracts, machine learning, legal automation, AI ethics, large language models, intellectual property, and autonomous systems has become foundational to the field.

Gabriel Teninbaum

Professor of Legal Writing, Suffolk University Law School

For more than a decade, Gabe played a central role in building Suffolk University Law School into one of the nation’s leading institutions for legal innovation and technology education. He oversaw the day-to-day operations of Suffolk’s Legal Innovation & Technology program, helped bring the nation’s first academic concentration in Legal Innovation & Technology to national prominence, and was one of the architects and founders of the award-winning LIT Lab, a pioneering legal technology clinical program that builds tools for self-represented litigants, courts, and legal aid organizations.

Joseph R. Tiano, Jr.

Founder of Legal Decoder; Adjunct Professor, Sandra Day O'Connor College of Law at ASU.

Tiano founded Legal Decoder, which applies data analytics and algorithms to legal billing and legal spend, and he teaches legal AI at Arizona State University's Sandra Day O'Connor College of Law. His teaching emphasizes practical evaluation of AI tools and professional judgment about their outputs.

George G. Triantis

Dean and Richard E. Lang Professor of Law, Stanford Law School

Under his deanship, Stanford Law launched liftlab, one of the first academic legal-AI initiatives designed to combine rigorous research, rapid prototyping, and direct collaboration with law firms and legal-technology companies. The lab is developing and testing applications involving legal training, professional judgment, contract work, and access to justice.

Kristopher Turner

Associate Director of Public Services, University of Wisconsin Law School

Kris Turner has carried AI literacy training to nearly every part of Wisconsin's legal and civic community. His work is a living example of the Wisconsin Idea, the University of Wisconsin's founding principle that what is learned on campus should serve the entire state.

Carolyn V. Williams

Assistant Professor, University of North Dakota School of Law

Her scholarship on generative AI and the NextGen Bar Exam, honored with the Legal Writing Institute's Teresa Godwin Phelps Award, gives legal educators a practical framework for moving beyond final-product grading toward assessments that measure reading, reasoning, and professional judgment. She extended that work into national infrastructure by co-founding the Legal Writing and Generative AI Convo Group, a monthly forum that now brings together hundreds of law faculty to share AI teaching practices in real time.

Mark Williams

Professor of the Practice, Founding Co-Director Vanderbilt AI Law Lab

Williams works at the intersection of legal technology education and innovation as a Professor of the Practice and founding co-director of the Vanderbilt AI Law Lab. His work examines artificial intelligence, legal services, and access to justice while connecting legal education with emerging technologies.

Jennifer L. Wondracek

Associate Dean of Legal Information, Director of the Underwood Law Library, and Clinical Professor of Legal Research, SMU Dedman School of Law

Wondracek connects legal-technology instruction directly to practice, running parallel legal-research bootcamp and AI Practice Summit tracks that let students and practicing lawyers learn side by side how to build real AI workflows and spot the tools' weaknesses. She maintains a widely cited tracker documenting AI-hallucination cases in the courts, drafted the first practice-related technology-competence requirement for J.D. candidates in the United States, and is a founding blogger of the AI Law Librarians blog.

Selection Methodology

A total of 76 eligible nominees advanced to committee review. Reviewers received biographical information, the stated basis for nomination, and supporting links. Each nominee was evaluated on three criteria, each using a five-point scale:

• Innovation: whether the nominee introduced something new or meaningfully advanced legal education.
• Impact: the measurable or demonstrated effect of the nominee’s work on students, institutions, the legal profession, or society.
• Overall Recommendation: whether, considering the full nomination, the nominee should be recognized among the Top 50 Legal Innovators in Academia.

The three criteria were weighted equally. For each reviewer, the Innovation, Impact, and Overall Recommendation ratings were averaged to produce a reviewer-level composite score. Each nominee’s final aggregate score was then calculated by averaging all complete, non-conflicted reviewer composites. A conflict or missing review was excluded from the denominator and was not treated as a zero.

The aggregate results produced the preliminary selection. The results were reviewed for conflicts, incomplete evaluations, and ties before the 50 honorees were finalized.

Selection Committee

Ten Selection Committee members submitted final evaluation forms and were included in the final review process:

• Sara Miro
• Neel U. Sukhatme
• Andrew Woolf
• Bridget Mary McCormack
• Phil Saunders
• Judge Joshua Deahl
• Stephanie Goutos
• Robert Ambrogi
• Darby Dickerson
• Evan J. Shenkman

Committee members were instructed to declare a conflict and refrain from rating any nominee where an employment, financial, supervisory, familial, or other material relationship could reasonably affect impartiality. Conflicted evaluations were excluded from the nominee’s aggregate score.