Henny Admoni

Assistant Professor Carnegie Mellon University

  • Pittsburgh PA

Henny Admoni directs the Human And Robot Partners (HARP) Lab, which develops assistive and collaborative robots and AI.

Contact

Carnegie Mellon University

View more experts managed by Carnegie Mellon University

Biography

Henny Admoni is an Assistant Professor in the Robotics Institute at Carnegie Mellon University, and also has a courtesy appointment in the Human-Computer Interaction Institute at CMU. She leads the Human And Robot Partners (HARP) Lab, which studies how to develop intelligent robots that can assist and collaborate with humans on complex tasks like preparing a meal. Henny is most interested in how natural human communication, like where someone is looking, can reveal underlying human intentions and can be used to improve human-robot interactions. Henny's research has been supported by federal agencies and industry, such as the US National Science Foundation, the US Office of Naval Research, the Paralyzed Veterans of America Foundation, and Sony Corporation. Her work has been featured by the media such as NPR's Science Friday, Voice of America News, and WESA radio. Previously, Henny was a postdoctoral fellow at CMU. She holds an MS and PhD in Computer Science from Yale University, and a BA/MA joint degree in Computer Science from Wesleyan University.

Areas of Expertise

Cognitive Psychology
Robotics
Human-Robot Interaction (HRI)
Healthcare
Human Assistance
Computer Science

Media Appearances

Robotics Professor Answers Robot Questions From Twitter

Wired Online  online

2022-11-22

Robotics professor Henny Admoni answers the internet's burning questions about robots! How do you program a personality? Can robots pick up a single M&M? Why do we keep making humanoid robots? What is Elon Musk's goal for the Tesla Optimus robot? Will robots take over my job writing video descriptions...I mean, um, all our jobs? Henny answers all these questions and much more.

View More

Supporting Black Scholars in Robotics

IEEE Spectrum  online

2020-09-10

Robotics is a fast-growing field with important economic and societal impacts. Despite the relevance of robotics, however, there is little diversity among educators and researchers in the area. This problem is especially acute among Black scholars and is not improving. In this article, we outline the representation problem and introduce a reading list along with suggestions for how those in academia—researchers, teachers, students, conference organizers, and others—can take actions that increase Black representation in robotics. While our analysis focuses on the situation in the United States, we hope that our suggestions will be of use to colleagues in other countries as well.

View More

Boston Dynamics’ Spot is leaving the laboratory

The Verge  online

2019-09-24

That’s the opposite of what many academic roboticists focus on, and Henny Admoni, who works on Human-Robot interaction at Carnegie Mellon University, told me it was an understandable but tricky trade-off. “Boston Dynamics has always been strong in mechanics and controls, like being able to shift the robot’s weight properly,” Admoni told me. “But robots operating in human environments won’t really have the option of avoiding humans. Integrating Human-Robot Interaction skills into development at an early stage is probably going to lead to greater success than trying to retrofit human interaction into existing systems.”

View More

Show All +

Social

Industry Expertise

Research
Education/Learning

Accomplishments

RSS Early Career Spotlight

2022

A. Nico Habermann Career Development Professorship

2020–2023

CMU Distinguished Lecture: Teruko Yata Memorial Lecture in Robotics

2019

Show All +

Education

Yale University

Ph.D.

Computer Science

2016

Yale University

M.S.

Computer Science

2012

Wesleyan University

M.A.

Computer Science

2009

Show All +

Affiliations

  • IEEE-RAS Women in Engineering Committee
  • Black In Robotics Allies : Steering Committee
  • Robotics Institute Climate Committee : Co-chair
  • Robotics Institute Education Committee
  • Transactions on Human-Robot Interaction : Associate Editor

Event Appearances

Human Interactive Robot Learning Workshop

HRI 2023  

Cognitive Modeling in Robot Learning for Adaptive HRI Workshop

ICRA 2023  

Communicating Robot Learning Across Human-Robot Interaction Workshop

ICRA 2023  

Show All +

Articles

Towards Online Adaptation for Autonomous Household Assistants

HRI '23: Companion of the 2023 ACM/IEEE International Conference on Human-Robot Interaction

2023

Many assistive home robotics applications assume open-loop interactions: robots incorporate little feedback from people while autonomously completing tasks. This places undue burden on people to condition their actions and environment to maximize the likelihood of their desired outcomes. We formalize assistive household rearrangement as collaborative online inverse reinforcement learning (IRL).

View more

Teaching agents to understand teamwork: Evaluating and predicting collective intelligence as a latent variable via Hidden Markov Models

Computers in Human Behavior

2023

Rapid growth in the reliance on teamwork in organizations, coupled with advances in artificial intelligence, has fueled increased use of Human Autonomy Teams (HATs) involving the collaboration of humans and agents to complete work. Although there are many successful examples of HATs, researchers and technology developers can see additional applications if agents were better able to understand the mental states of humans to anticipate what a team is likely to do next.

View more

The Role of Adaptation in Collective Human–AI Teaming

Topics in Cognitive Science

2022

This paper explores a framework for defining artificial intelligence (AI) that adapts to individuals within a group, and discusses the technical challenges for collaborative AI systems that must work with different human partners. Collaborative AI is not one-size-fits-all, and thus AI systems must tune their output based on each human partner's needs and abilities. For example, when communicating with a partner, an AI should consider how prepared their partner is to receive and correctly interpret the information they are receiving.

View more

Show All +