Qiaoning (Carol) Zhang张巧宁

Assistant Professor · Human Systems Engineering · Arizona State University
Director, CARE Lab (Collaborative Automation and Robotic Experiences)

I am an Assistant Professor of Human Systems Engineering in the Polytechnic School, Ira A. Fulton Schools of Engineering at Arizona State University. I received my Ph.D. in Information from the University of Michigan under the guidance of my incredible advisors, Dr. Lionel P. Robert Jr. and Dr. X. Jessie Yang.

I believe the best technology doesn't just work, it understands us. That belief drives everything I do. My research focuses on how social contexts influence our interactions with cutting-edge technologies such as AI, healthcare robots, and automated vehicles, and I aim to create a future where technology is not just smart but also empathetic.

As intelligent systems become woven into our daily lives, people deserve technology that respects who they are, responds to how they feel, and earns their trust over time. That is why empathetic design sits at the core of my research: it is the bridge between capable machines and meaningful human experiences. This vision has led me to design socially assistive robots that care for older adults aging at home through compassionate interaction, to study how a vehicle's voice and explanations build and sustain driver trust, and to explore how humans and AI can form complementary teams grounded in mutual understanding. My work has been published at top venues including CHI, HRI, HFES, and in journals such as Journal of Patient Safety, International Journal of Human–Computer Interaction, International Journal of Social Robotics, and Scientific Reports, and featured by the World Economic Forum, NPR, and CNET.

Intelligent systems can now drive, converse, and advise, but being capable is not the same as being helpful. My research asks how intelligent technologies can become true partners in people's lives, through three connected directions: understanding human needs and individual differences, because good help starts with the person; designing responsive interaction that supports human agency, so help arrives when and how people want it; and enabling complementary human–AI collaboration, so human and AI strengths contribute to better joint outcomes. Looking ahead, I study how years of living with intelligent systems can support people's independence, learning, and meaningful participation.

Human-AI Collaboration Human-Robot Interaction Socially Assistive Robots for Aging-in-Place Trust & Transparency in Autonomous Systems Human Factors in Automated Vehicles Human-Centered Design

I am actively seeking Ph.D. students and undergraduate/master researchers to join my team. If you share a passion for building technology that truly serves and connects with people, I'd love to hear from you. Learn more.

qiaoning@asu.edu

Santa Catalina Hall 150M

7271 E Sonoran Arroyo Mall

Mesa, AZ 85212

✉ Email Google Scholar ORCID LinkedIn

CARE Lab

Collaborative Automation and Robotic Experiences Lab

Director: Dr. Qiaoning (Carol) Zhang

The CARE Lab at Arizona State University investigates how people interact with intelligent systems, from socially assistive robots and automated vehicles to AI-powered tools. Our mission is to design technology that is empathetic, trustworthy, and grounded in real human needs. We combine human-centered design methods, behavioral experiments, and applied data science to create systems that genuinely care about the people they serve.

Equipped with a Furhat social robot, wearable eye tracking, and physiological sensing, the lab is moving from scenario-based studies to repeated, live interactions in which people can clarify goals, question recommendations, and redirect or decline assistance. Beyond trust and acceptance, we evaluate whether people understand their options, can steer the system, and continue to learn—including how well they perform when the AI is absent.

Socially Assistive Robotics Trust in Automation Empathetic Design Human-AI Teaming Aging-in-Place

Interested in joining the lab? Learn about open positions.

Lab Facilities

Our lab is equipped with state-of-the-art research instruments for measuring social interaction, visual attention, and physiological responses in real time.

Furhat Social Robot

Expressive, human-like social robot

An advanced humanoid social robot with a back-projected face capable of life-like expressions, gaze, and speech. We use Furhat to study how empathetic communication, personality, and politeness shape trust between older adults and social robots at home.

HRI Social Robotics Empathetic Design

Pupil Labs Neon

Research-grade wearable eye tracker

A lightweight, calibration-free eye tracker that looks like normal glasses. Neon captures gaze, pupil diameter, fixations, and blinks at 200 Hz, enabling us to measure visual attention in naturalistic settings like driving, human-robot interaction, and decision-making tasks.

Gaze Tracking Visual Attention Pupillometry

Shimmer3 GSR+ Unit

Wireless physiological measurement

A compact wearable biosensor that measures galvanic skin response (GSR), heart rate, and motion. Shimmer3 captures moment-to-moment physiological arousal, giving us a window into how users emotionally respond to AI, robots, and automated vehicles in real time.

GSR / EDA Heart Rate Arousal

Research Team

My mentoring connects opportunities to contribute to scholarship with the development of independent judgment: students take increasing responsibility for their work, and together we create new things that matter to people.

The people behind the research. Click on a team member to learn more!

Director

Dr. Qiaoning (Carol) Zhang

Assistant Professor

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About Carol

Carol is an Assistant Professor in Human Systems Engineering at ASU and Director of the CARE Lab. She earned her Ph.D. in Information from the University of Michigan, advised by Dr. Lionel P. Robert Jr. and Dr. X. Jessie Yang. Her research centers on empathetic design and trust dynamics in human-AI, human-robot, and human-vehicle interactions, with a focus on supporting older adults aging at home and building more humane intelligent systems.

Empathetic Design Trust Dynamics HRI Automated Vehicles Aging-in-Place

Email Scholar

Ph.D. Student

Jiongyu (Johnny) Chen

Ph.D. Student, HSE

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About Johnny

Johnny is a second-year Ph.D. student designing and evaluating human-centered AI systems, especially conversational and robotic agents. He studies how communication strategies shape user trust, experiences, and behavioral outcomes across healthcare and everyday contexts. M.S. in Information (UX Research) from University of Michigan; B.S. in Psychological Sciences and B.A. in Sociology from Purdue.

Human-Centered AI Conversational Agents Trust UX Research

Website Email

Ph.D. Student

Xiaoyu Li

Ph.D. Student, HSE

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About Xiaoyu

Xiaoyu joined the CARE Lab in Fall 2026 as a Ph.D. student in Human Systems Engineering at ASU, advised by Dr. Zhang.

You?

Join Our Team!

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Research

How can intelligent technologies become partners that support people's goals while respecting their judgment, choices, and ways of living? Across transportation, home healthcare robotics, and AI decision support, my work connects understanding the person, designing the interaction, and enabling collaboration. Three connected directions organize this research; the projects below are grouped under them.

DIRECTION 01

Understanding Human Needs & Individual Differences

FoundationWhich differences in users' priorities, abilities, and expectations matter for design, and why.

Next phaseHow do goals and valued support evolve across life circumstances and experience with AI?

DIRECTION 02

Designing Responsive Interaction That Supports Human Agency

FoundationHow explanations, politeness, empathy, and system-initiated interaction shape users' experiences and trust.

Next phaseHow can people shape and revise AI's participation while retaining choice and control?

DIRECTION 03

Enabling Complementary Human–AI Collaboration

FoundationComplementary expertise and joint performance in human–AI teams.

Next phaseHow can evolving human and AI capabilities improve joint outcomes while supporting human learning and judgment?

🏥

Direction 01 · Human Needs

Healthcare Robot Feature Prioritization

Applying the Kano model to identify "must-be" and "attractive" design attributes for healthcare robots, optimizing user acceptance and functional utility for older adults.

This project applied the Kano model framework to systematically prioritize design features for healthcare robots intended for older adults. By categorizing features into "must-be," "one-dimensional," and "attractive" attributes, this work provides actionable guidance for designers to optimize both user acceptance and functional utility.

Key Publications:
Zhang, Q., Zhou, F., Robert Jr, L. P., & Yang, X. J. (2026). Designing Healthcare Robots for Community-Dwelling U.S. Older Adults: A Kano Model Perspective. International Journal of Social Robotics.
Zhang, Q., Zhou, F., Robert Jr, L. P., & Yang, X. J. (2024). Designing Healthcare Robots at Home for Older Adults: A Kano Model Perspective. HRI 2024.

Click to learn more ▾

📊

Direction 01 · Human Needs

Expectation and Trust in Automated Vehicles

Studying how individual differences, personality, and prior expectations shape trust formation and long-term acceptance through large-scale representative surveys.

Using a large-scale survey with a representative U.S. sample, this research explores how expectations, personality traits, and individual differences shape initial trust formation and long-term acceptance of automated vehicles. This line of work provides a foundational understanding of what people want and expect from AVs before they even encounter one.

Key Publications:
Zhang, Q., Yang, X. J. & Robert, L. P. (2022). Individual Differences and Expectations of Automated Vehicles. IJHCI.
Zhang, Q., Yang, X. J. & Robert, L. P. (2020). Expectations and Trust in Automated Vehicles. CHI 2020 Extended Abstracts.

Click to learn more ▾

⚕️

Direction 01 · Human Needs

Enhancing Patient-Physician Relationships

Mapping patient and physician journeys (M-Well project) to design human-centered interventions that foster improved interactions and connectedness in healthcare.

The M-Well project at the University of Michigan mapped patient and physician journeys to identify pain points and design interventions that foster improved interactions and connectedness. This work applies human factors engineering principles to healthcare, including exploring how physicians can design their work environment for well-being, much like pilots design a cockpit.

Key Publication: Zamudio, J., Zhang, Q., et al. (2025). "Invert the Pyramid, Let Internists Design the Job as Pilots Do a Cockpit." Journal of Patient Safety.

Click to learn more ▾

🤖

Direction 02 · Responsive Interaction

Socially Assistive Robots for Aging-in-Place

Designing empathetic robots (e.g., Furhat) that support older adults at home through compassionate communication, investigating stakeholder roles and transparency features that enhance trustworthiness.

Leading the design and evaluation of socially assistive robots with a focus on empathic communication to support aging-in-place. This work investigates how politeness strategies, empathic communication, and role perceptions affect trust dynamics between older adults and healthcare robots, and how transparency features can enhance trustworthiness in human-robot interaction.

Key Publications:
Chen, J., & Zhang, Q. (2026). Interrupting Politely: Robot-Initiated Interruptions and Politeness Strategies in Home Healthcare Interactions with Older Adults. IJHCI.
Chen, J., & Zhang, Q. (2026). The Influence of Perceived Empathy and Negative Attitudes on Trust in Home Robotic Agents Among Older Adults. HFES 2026.
Chen, J., Chalifoux, C., Du, N., & Zhang, Q. (2026). Who Needs What? Empathy Communication and Trait Empathy in a Home-Based Virtual Healthcare Robotic Agent. CHI EA 2026.
Zhang, Q., Zhou, F., Robert Jr, L. P., & Yang, X. J. (2024). Designing Healthcare Robots at Home for Older Adults: A Kano Model Perspective. HRI 2024.

Click to learn more ▾

🚗

Direction 02 · Responsive Interaction

Explanation and Trust in Automated Vehicles

Understanding how a vehicle's voice, explanation timing, modality, and content influence the dynamics of driver trust, workload, and acceptance across different age groups.

This research program examines how design features of automated vehicle explanations (timing, modality, voice gender, voice similarity), human user traits (age, suspicion level, personality), and driving contexts interact to build and sustain trust. Recent work explores how AI voice gender congruity and cognitive vs. affective explanation content shape trust differently.

Key Publications:
Zhang, Q., Yang, X. J., & Robert, L. P. (2025). AI Voice Gender, Gender Role Congruity, and Trust in AVs. Scientific Reports.
Zhang, Q., Yang, X. J., & Robert, L. P. (2025). Explanation Content, User Needs, and Voice Similarity in AV Explanations (three papers). HFES 2025.
Zhang, Q., et al. (2023). Impact of Modality, Technology Suspicion, and NDRT on AV Explanations. IEEE Access.
Du, N., Haspiel, J., Zhang, Q., et al. (2019). Look Who's Talking Now. Transportation Research Part C.

Click to learn more ▾

🧠

Direction 03 · Complementary Collaboration

Human-AI Teams and Complementary Expertise

Examining how humans and AI leverage complementary strengths for better joint decision-making, moving beyond automation toward genuine collaboration.

Conducted at Toyota Research Institute, this research analyzes the intricate behavioral dynamics and decision-making processes within human-AI collaborative teams. The work demonstrates how humans and AI can achieve outcomes that neither could accomplish alone by leveraging their unique, complementary expertise.

Key Publication: Zhang, Q., Lee, M.L. & Carter, S. (2022). You Complete Me: Human-AI Teams and Complementary Expertise. ACM CHI 2022. #1 in HCI by Google Scholar

Click to learn more ▾

Publications

2026

Journal Designing Healthcare Robots for Community-Dwelling U.S. Older Adults: A Kano Model Perspective

Zhang, Q., Zhou, F., Robert, L. P., Jr., & Yang, X. J.

International Journal of Social Robotics, 18(7), Article 91

Journal Interrupting Politely: Robot-Initiated Interruptions and Politeness Strategies in Home Healthcare Interactions with Older Adults

Chen, J., & Zhang, Q.

International Journal of Human-Computer Interaction (advance online publication)

Conference The Influence of Perceived Empathy and Negative Attitudes on Trust in Home Robotic Agents Among Older Adults

Chen, J., & Zhang, Q.

Proceedings of the Human Factors and Ergonomics Society Annual Meeting (HFES 2026)

Conference "I Feel You" vs. "I Understand You": How Distinct Empathic Strategies Shape Robot Personality and Trust for Older Adults

Chen, J., & Zhang, Q.

Proceedings of the Human Factors and Ergonomics Society Annual Meeting (ASPIRE – HFES 2026), in press

Conference Shaping Future Automated School Bus Systems: Multi-Stakeholder Insights Informing Human-in-the-Loop Design

Zhang, Y., Ye, B., Zhang, Q., Zeng, B., & Du, N.

Proceedings of the Human Factors and Ergonomics Society Annual Meeting (ASPIRE – HFES 2026), in press

Extended Abstract Who Needs What? The Interaction Between Empathy Communication and Trait Empathy in a Home-Based Virtual Healthcare Robotic Agent for Older Adults

Chen, J., Chalifoux, C., Du, N., & Zhang, Q.

Extended Abstracts of the CHI Conference on Human Factors in Computing Systems (CHI EA 2026)

2025

Journal Artificial Intelligence Voice Gender, Gender Role Congruity, and Trust in Automated Vehicles

Zhang, Q., Yang, X. J., & Robert, L. P., Jr.

Scientific Reports, 15, Article 16364

#1 in Multidisciplinary Sciences by Google Scholar

Journal "Invert the Pyramid, Let Internists Design the Job as Pilots Do a Cockpit": Views of General Internal Medicine Physicians on Enhancing Well-Being Through Human Factors Engineering

Zamudio, J., Zhang, Q., Quinn, M., Fowler, K. E., Saint, S., & Yang, X. J.

Journal of Patient Safety, 21(7Supp), S36-S42

#3 in Health Policy and Medical Law by Google Scholar

Conference Understanding Explanation Content for Cognitive and Affective Trust in Automated Vehicles

Zhang, Q., Yang, X. J., & Robert, L. P., Jr.

Proceedings of the Human Factors and Ergonomics Society Annual Meeting (HFES 2025), 69(1), 1028-1033

Conference Understanding User Needs in Automated Vehicle Explanations: A Qualitative Approach

Zhang, Q., Yang, X. J., & Robert, L. P., Jr.

Proceedings of the Human Factors and Ergonomics Society Annual Meeting (HFES 2025), 69(1), 1046-1051

Conference Voice Similarity and its Impact on Cognitive and Affective Trust in Automated Vehicles

Zhang, Q., Yang, X. J., & Robert, L. P., Jr.

Proceedings of the Human Factors and Ergonomics Society Annual Meeting (HFES 2025), 69(1), 1040-1045

Conference Voice Design and Trust in Automated Vehicles: Findings and a Research Agenda

Chen, J., & Zhang, Q.

IEEE 7th International Conference on Trust, Privacy and Security in Intelligent Systems, and Applications (TPS-ISA 2025), 688-696

2024

Poster Designing Healthcare Robots at Home for Older Adults: A Kano Model Perspective

Zhang, Q., Zhou, F., Robert, L. P., Jr., & Yang, X. J.

ACM/IEEE International Conference on Human-Robot Interaction (HRI 2024)

Book Chapter Human-Robot Interaction

Esterwood, C., Zhang, Q., Yang, X. J., & Robert, L. P.

In C. Stephanidis & G. Salvendy (Eds.), Human-Computer Interaction in Intelligent Environments (pp. 305-332), CRC Press

Short Paper Finding the Right Voice: Exploring the Impact of Gender Similarity and Gender-Role Congruity on the Efficacy of Automated Vehicle Explanations

Zhang, Q., Yang, X. J., & Robert, L. P., Jr.

Proceedings of the AAAI Symposium Series, 2(1), 219-223 (AAAI Fall Symposium on AI for HRI, 2023)

2023

Journal The Impact of Modality, Technology Suspicion, and NDRT Engagement on the Effectiveness of AV Explanations

Zhang, Q., Esterwood, C., Pradhan, A. K., Tilbury, D., Yang, X. J., & Robert, L. P.

IEEE Access, 11, 81981-81994

#1 in Engineering & Computer Science by Google Scholar

2022

Conference You Complete Me: Human-AI Teams and Complementary Expertise

Zhang, Q., Lee, M. L., & Carter, S.

ACM CHI Conference on Human Factors in Computing Systems (CHI 2022)

#1 in Human Computer Interaction by Google Scholar

Journal Individual Differences and Expectations of Automated Vehicles

Zhang, Q., Yang, X. J., & Robert, L. P., Jr.

International Journal of Human-Computer Interaction, 38(9), 825-836

#8 in Human Computer Interaction by Google Scholar

2021

Journal What and When to Explain? A Survey of the Impact of Explanation on Attitudes toward Adopting Automated Vehicles

Zhang, Q., Yang, X. J., & Robert, L. P.

IEEE Access, 9, 159533-159540

#1 in Engineering & Computer Science by Google Scholar

Journal Drivers' Age and Automated Vehicle Explanations

Zhang, Q., Yang, X. J., & Robert, L. P., Jr.

Sustainability, 13(4), 1948

Short Paper From the Head or the Heart? An Experimental Design on the Impact of Explanation on Cognitive and Affective Trust

Zhang, Q., Yang, X. J., & Robert, L. P., Jr.

AAAI Fall Symposium on Artificial Intelligence for Human-Robot Interaction (AI-HRI 2021)

2020

Poster Expectations and Trust in Automated Vehicles

Zhang, Q., Yang, X. J., & Robert, L. P.

CHI Extended Abstracts, 2020

Journal A Review of Personality in Human-Robot Interactions

Robert, L. P., Jr., Alahmad, R., Esterwood, C., Kim, S., You, S., & Zhang, Q.

Foundations & Trends in Information Systems, 4(2), 107-212

2019

Journal Look Who's Talking Now: Implications of AV's Explanations on Driver's Trust, AV Preference, Anxiety and Mental Workload

Du, N., Haspiel, J., Zhang, Q., Tilbury, D., Pradhan, A. K., Yang, X. J., & Robert, L. P., Jr.

Transportation Research Part C: Emerging Technologies, 104, 428-442

#2 in Transportation by Google Scholar

Short Paper An Automated Vehicle (AV) Like Me? The Impact of Personality Similarities and Differences Between Humans and AVs

Zhang, Q., Esterwood, C., Yang, X. J., & Robert, L. P., Jr.

AAAI Fall Symposium on Artificial Intelligence for Human-Robot Interaction (AI-HRI 2019)

2018

Conference Evaluating Effects of Automation Reliability and Reliability Information on Trust, Dependence and Dual-Task Performance

Du, N., Zhang, Q., & Yang, X. J.

Human Factors and Ergonomics Society Annual Meeting, 2018

Abstract Trust in AVs: The Impact of Expectations and Individual Differences

Zhang, Q., Robert, L. P., Jr., Du, N., & Yang, X. J.

Conference on Autonomous Vehicles in Society: Building a Research Agenda, East Lansing, MI (non-refereed)

Teaching

I want students to ask what is worth building, for whom, and why—and to explain the evidence behind their choices. In HSE 521 and the HSE 477 capstone, students learn to understand users before they build and to back design decisions with evidence; capstone teams define feasible UX projects, navigate human-subjects research requirements, and present their work at a public poster session. These skills matter more, not less, as AI makes building easier.

Instructor, Arizona State University

Spring 2027HSE 598/494 Human-Centered Design in the Age of AI (new course, scheduled)

Fall 2026HSE 521 Methods & Tools in Human Systems Engineering

Summer 2026HSE 792 Research

Spring 2026HSE 521 Methods & Tools in Human Systems Engineering (two sections)

Spring 2026HSE 584 Internship

Spring 2026HSE 792 Research

Fall 2025HSE 521 Methods & Tools in Human Systems Engineering

Fall 2025HSE 792 Research

Spring 2025HSE 477 Human Systems Engineering Capstone (4.84/5)

Spring 2025HSE 493 Honors Thesis

Fall 2024HSE 521 Methods & Tools in Human Systems Engineering

Graduate Student Instructor, University of Michigan

Fall 2021-22SI 582 Introduction to Interaction Design

Winter 2021SI 618 Data Manipulation and Analysis (4.83/5)

Winter 2020SI 622 Needs Assessment and Usability Evaluation (4.82/5)

Fall 2019SI 501 Contextual Inquiry and Consulting Foundations (4.83/5)

Invited Talks & Presentations

Explanation Content, User Needs, and Voice Similarity: Cognitive and Affective Trust in Automated Vehicles (three papers)

2025 · HFES International Annual Meeting

Designing Healthcare Robots at Home for Older Adults: A Kano Model Perspective

2024 · ACM/IEEE HRI 2024

Bridging Humans and Technology: Human-Centered Design for Trust and Collaborative Futures

2024 · Arizona State University · UM Transportation Research Institute · University of Houston

You Complete Me: Human-AI Teams and Complementary Expertise

2021-22 · Toyota Research Institute · ACM CHI 2022

Finding the Right Voice: Gender Similarity and AV Explanations

2023 · AAAI AI for HRI Symposium

From the Head or the Heart? Explanation and Trust in AVs

2021-22 · HCI Consortium · AAAI AI for HRI Symposium

An AV like Me? Personality Similarities and Differences between Humans and AVs

2019 · AAAI AI for HRI Symposium

Professional Service

Leadership & Committees

Technical Program Committee Co-Chair, IEEE Workshop on Trustworthy and Privacy-Preserving Human-AI Collaboration (TPHAC 2026)
Associate Editor, Human Technology Interaction Track, ICIS 2026
Associate Chair, CHI 2026 (Interacting with Devices)
Program Committee, IEEE TPS 2026 · IEEE CogSIMA 2026
Associate Editor, IT Implementation and Adoption Track, ICIS 2025
Co-organizer, Program Committee Member & Panelist, TPHAC 2025
Associate Chair, AutomotiveUI 2025 & 2024
Program Committee, Intl. Symposium on Trustworthy Autonomous Systems (TAS 2024)
Member, New Faculty Advisory Council, Ira A. Fulton Schools of Engineering (2025-present)
Lead, HSE (Health Systems) M.S. Degree Redesign Task Force, ASU (Fall 2024)

Review Panels

NSF IIS Panel (2025)
NSF OISE Panel (2024)

Journal Reviewing

Artificial Intelligence
Transportation Research Part C & Part F · Interdisciplinary Perspectives
Intl. Journal of Human-Computer Interaction
Intl. Journal of Social Robotics
ACM Trans. on Human-Robot Interaction
ACM Trans. on Accessible Computing · ACM Trans. on Social Computing
Human Factors
Human-Machine Communication
IEEE Trans. Human-Machine Systems
Computers in Human Behavior
Scientific Reports (Nature)
Applied Ergonomics
Interaction Studies
Journal of Medical Systems
JAIS · AIS Trans. HCI

Conference Reviewing

CHI (2021, 2023, 2025, 2026)
HRI (2019, 2024, 2025)
HFES / ASPIRE (2025, 2026)
HICSS 60 (2027)
IEEE TPS (2026) · IEEE CogSIMA (2026)
ICRA (2025)
CSCW (2024) · TAS (2024)
AutomotiveUI (2019, 2021, 2023, 2025)
ICIS (2019, 2021, 2023) · ECIS (2022)
AAAI AI-HRI Symposium (subreviewer, 2021)

Qiaoning (Carol) Zhang张巧宁

CARE Lab

Lab Facilities

Furhat Social Robot

Pupil Labs Neon

Shimmer3 GSR+ Unit

Research Team

Dr. Qiaoning (Carol) Zhang

Jiongyu (Johnny) Chen

Xiaoyu Li

You?

Research

Understanding Human Needs & Individual Differences

Designing Responsive Interaction That Supports Human Agency

Enabling Complementary Human–AI Collaboration

Healthcare Robot Feature Prioritization

Expectation and Trust in Automated Vehicles

Enhancing Patient-Physician Relationships

Socially Assistive Robots for Aging-in-Place

Explanation and Trust in Automated Vehicles

Human-AI Teams and Complementary Expertise

Publications

Teaching

Instructor, Arizona State University

Graduate Student Instructor, University of Michigan

Invited Talks & Presentations

Professional Service

Leadership & Committees

Review Panels

Journal Reviewing

Conference Reviewing

Selected Press

Join My Research Team

Prospective Ph.D. Students

Undergraduate & Master's Students