Research

My training as a mechanical engineer, roboticist and human-factors researcher positions me uniquely to explore these domains at their convergence in human-augmentation, across physical, cognitive and collaborative interfaces in real-world, virtual or hybrid environments. Therefore, my research and interests through grad-school broadly span these ideas.

Human Factors and Cognitive Neuroscience
Adaptive Non-invasive Neuromodulation: I study the mechanistic, operational, and ethical barriers to the use of non-invasive brain stimulation as a fatigue countermeasure during sustained cognitive activity. To that end, I am also developing algorithms to predict fatigue states, and exploring the use of unobtrusive fatigue-indices (e.g. from wearable ECG) towards a human-centered, closed-loop decision support system for neuromodulation. The explainability and interpretability of algorithimic decisions for all relevant stakeholders feature as prominent factors in our development process. [Conference] [Presentation] [Poster]
Human Learning in AR/VR Environments This research is a core component of the NSF Convergence Accelerator project LEARNER where we propose a human-centered training platform for emergency responders across different augmentation technologies. Our specific focus is on building adaptive learning experiences for sensorimotor tasks in virtual reality (VR) and towards improved usability within augmented reality (AR) interfaces. We developed a task-agnostic framework for human learning in VR, where adaptations are driven by performance, neurophysiological and behavioral markers captured during discrete learning experiences. Presently, we are extending this effort towards physical and virtual exercises when using an AR headset. [Journal] [Poster]

Human Factors and Cognitive Neuroscience

Adaptive Non-invasive Neuromodulation: I study the mechanistic, operational, and ethical barriers to the use of non-invasive brain stimulation as a fatigue countermeasure during sustained cognitive activity. To that end, I am also developing algorithms to predict fatigue states, and exploring the use of unobtrusive fatigue-indices (e.g. from wearable ECG) towards a human-centered, closed-loop decision support system for neuromodulation. The explainability and interpretability of algorithimic decisions for all relevant stakeholders feature as prominent factors in our development process.

[Conference] [Presentation] [Poster]

Human Learning in AR/VR Environments This research is a core component of the NSF Convergence Accelerator project LEARNER where we propose a human-centered training platform for emergency responders across different augmentation technologies. Our specific focus is on building adaptive learning experiences for sensorimotor tasks in virtual reality (VR) and towards improved usability within augmented reality (AR) interfaces. We developed a task-agnostic framework for human learning in VR, where adaptations are driven by performance, neurophysiological and behavioral markers captured during discrete learning experiences. Presently, we are extending this effort towards physical and virtual exercises when using an AR headset.

[Journal] [Poster]

Human-Robot Interaction
Haptics in tele-operated surgery: Sensory feedback during human-robot interaction can influence operator cognitive state, overall task performance, and the associated user experience -- especially within tele-operated frameworks. In this research, we study the effect of these stimuli, the relevant sensing modalities, and the active neural pathways on operator behavior when under the influence of both cognitive and physiological stressors (E.g. prolonged, complex surgeries). Further we explore gender-specific differences in sensory perception, and response to feedback modalities. [Journal] [Conference]

Human-Robot Interaction

Haptics in tele-operated surgery: Sensory feedback during human-robot interaction can influence operator cognitive state, overall task performance, and the associated user experience -- especially within tele-operated frameworks. In this research, we study the effect of these stimuli, the relevant sensing modalities, and the active neural pathways on operator behavior when under the influence of both cognitive and physiological stressors (E.g. prolonged, complex surgeries). Further we explore gender-specific differences in sensory perception, and response to feedback modalities.
[Journal] [Conference]

Robot-assisted Surgery
Sensing within small-scaled surgical instruments: This research explored the feasibility of a bi-modal sensing and actuation component for minimally invasive, articulate surgical catheters (< 1 mm). We proposed a Kevlar-reinforced optical fiber Bragg-grating tendon as an actuation intermediary for surgical needles; in a form compatible with Intuitive Surgical's da Vinci interface. My Master's thesis was on the performance evaluation of these tendons, and subsequent research effort was focused on proof-of-concepts within compatible instruments. [Thesis] [Journal] [Poster]
A model for tool-tissue interactions: Deformation behavior in soft biological tissue is time-variant and nonlinear; further it is also a function of bulk properties, loading direction, and the surrounding anatomy. Therefore, an all-encompassing analytical representation is somewhat infeasible. My research explores a data-driven Bayesian model for soft-tissue mechanics, while comparing mechanistic, offline, and online approximations for tool-tissue interaction. We believe that this research can facilitate improved tip-positioning accuracy in robot-assisted surgery. [Journal]
Articulate instruments and steerability: We address two forms of augmentation in this context, 1) function: laser-machining multi-DOF instruments that permit enhanced articulation, and embedding sensors that compliment the performance of these tools in practice. further we went on to investigate the strength, controllability (tip-positioning accuracy), and posability of such miniaturized instruments, 2) design: We perform numerical simulations to systematically investigate the effect of pattern design parameters on tubular structures, and present guidelines for obtaining the preferred behavior. [Journal] [Conference] [Poster]