Sara Falcone

Personal Quote

I design and study interactive systems that place human experience, agency, and accessibility at the center of intelligent technologies.

Faculty Bio

Assistant Professor of Computer Science specializing in human–computer interaction, embodied AI, and telepresence, with research spanning human–robot interaction, accessibility, and experimental studies of embodiment.

Awards and Honors

• Vassar College, 2024, Frances D. Fergusson Faculty Technology Exploration Fund
• SMC, 2022, Best Paper Award
• Erasmus, 2022, Erasmus Placement
• AISV, 2019, Franco Ferrero Award
• Erasmus, 2018, Erasmus Placement
• Erasmus, 2015, Erasmus +

PhD, University of Twente, Enschede, The Netherlands, 2023
Electrical Engineering, Mathematics, and Computer Science

Visiting Graduate Student, Princeton University, Princeton, 2022
Computer Science

MS, University of Trento, Rovereto, 2019
Human-Machine Interaction

Erasmus Placement, University of Twente, Enschede, 2018
Computer Science

BA, University Federico II of Napoli, Napoli, 2016
Language and Linguistics

Erasmus +, Sorbonne Nouvelle, Paris, 2015
Computational Linguistics

Research Interest

Human–Computer Interaction, Human–Robot Interaction, Embodiment and Agency, Telepresence and Telerobotics, Embodied AI, Accessibility, and Experimental Studies of Interactive Systems.

Grants, Sponsored Research and Contracts

Embodied Kinesthetic Learning Using Motion Capture and Immersive Interfaces
Falcone, S. May 2026 - April 2028. National Science Foundation, Federal. Currently Under Review. This project investigates how wearable motion capture and immersive feedback can enhance kinesthetic learning outcomes. Kinesthetic learning is a critical mode of skill acquisition through bodily motion and proprioceptive experience. It is essential for fields such as teleoperation, rehabilitation, sports training, and tool-mediated interaction. Our work is based on the hypothesis that manipulating perceptual cues of embodiment can influence how motor tasks are learned, retained, and transferred. Using a full-body motion capture system (Xsens Awinda) and a Unity- based virtual environment, we will explore how high-fidelity, real-time feedback improves learning trajectories and long-term skill retention. The ultimate goal is to create a foundational framework for accessible, embodied learning platforms that can be applied to both skill training and physical rehabilitation.

Collaborative Co-Embodiment for Accessible Hybrid Meetings
Falcone, S., Stevenson Won, A., Azenkot, S. & Leigh, S. March 2026 - February 2027. Alfred P. Sloan Foundation, Private. Currently Under Review.

Scholarly Research Application
Falcone, S. November 2025 - May 2026. Pace University. Funded. Used Scholarly Research funds to purchase SenseGlove haptic gloves to support experimental research on embodiment and human–computer interaction.

Kenan Funds
Falcone, S. June 2025 - January 2026. Pace University. Funded.

Past Courses

CS 121: Intro to Computer Science
CS 242: Algorithms & Computing Theory
CS 632: Tpc: Intro Ntrl Lngge Prcssng
CS 661: Python Programming
CS 802: Research Seminar

Professional Memberships

• Institute of Electrical and Electronics Engineers [Member]

Department Service

• AdHoc By-Laws Committee [Committee Member]
• Kenan Funds [Committee Member]