BCIs for Teamwork: Assessing and Augmenting Team Performance in Creative Collaboration (2023 – present)

The success of people engaging in creative tasks has the potential to be amplified by collaboration, allowing them to achieve greater efficiency and output than those working individually. Recent work has shown that brain signals can be used to reliably and non-invasively detect levels of team processes in team members engaged in collaborative problem-solving, which are crucial for determining whether a team is functioning effectively. However, to date there are no existing interventions that leverage this ability to facilitate effective teamwork in creative contexts. This project takes a user-centered approach to assess the needs and concerns of the various stakeholders (potential users and team leaders) that might benefit from such an intervention, in order to inform the development of a prototype.

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Interpersonal Neural Synchrony BCI for Adaptive Multi-Agent Human-Robot Collaboration (2022 – present)

When humans work closely together, they can pick up subtle cues from their team members and adapt their behavior appropriately. However, in contexts with robot team members, robots may not be able to detect these cues and respond accordingly, and the presence of a robot may impact the performance and cognitive states of human collaborators. Interpersonal neural synchrony (INS), where the brain activity of multiple people over a period of time is similar, has been observed in neurophysiological recordings of pairs of participants engaging in cooperative and social activities. I am currently investigating how measurements of INS acquired using functional near-infrared spectroscopy (fNIRS) might be used to assess and augment teamwork in complex multi-agent human-robot team tasks.

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Social Media Polarization (2020 – 2022)

As polarization among political officials has increased dramatically in recent years, the social media landscape has followed suit. The increased prevalence of disinformation, inflammatory rhetoric, and harassment online has augmented polarization in turn, propelling a feedback loop resulting in the erosion of democratic norms. Effective moderation of social media platforms can help solve this problem.

 

My MS thesis work explored how implementing a democratic, peer-based "digital jury" moderation system for social media platforms would impact polarization online, compared to traditional, "top-down" moderation that is conducted by employees of the platforms themselves. While the peer-based system did not significantly impact polarization, our moderators on average viewed the system as just, legitimate, and effective at reducing harmful content. Additionally, end users noticed no difference between the two systems, indicating that implementing such a peer-based moderation system has the benefit of providing users agency in platform governance without adversely impacting user experience.

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Postbaccalaureate Research (2017 – 2019)

After graduating from college, I joined Dr. Hal Blumenfeld's lab at the Yale University School of Medicine as a postgraduate research associate. I contributed to several projects that aimed to understand the neuromechanisms of normal and disordered consciousness, but my main project (under the supervision of postdoctoral fellow Dr. Kate Christison-Lagay) explored the mechanisms of auditory perception. I helped record and analyze intracranial EEG signals from patients with medically intractable epilepsy who performed an auditory threshold perception task.

 

Observations indicated that a switch-and-wave phenomenon similar to what had previously been observed during visual perception was also present during auditory perception, suggesting the presence of a common perceptual network spanning multiple sensory modalities.

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Undergraduate Research (2014 – 2017)

BCI-based Brain-to-Brain Communication (Summer 2016)

In the summer before my senior year, I attained a competitive Vredenburg Scholarship to conduct research abroad at Tokyo Institute of Technology under Dr. Tohru Yagi. There, I pursued a project (with then-PhD student Theerawit Wilaiprasitporn) that explored how an EEG-based brain-computer interface (BCI) could be used to facilitate bi-directional communication using brain signals. Although just a proof-of-concept, results indicated that by synchronizing participants' signals using steady-state visually evoked potentials (SSVEP), we could increase potential information content being communicated directly between individuals’ brains.

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Effects of Exercise on Mouse Cerebral Vascular Structure (2014 – 2017)

My first research experience was in Dr. David Linden’s neuroscience lab at the Johns Hopkins University School of Medicine, supervised by postdoctoral fellow Dr. Robert Cudmore. We sought to determine if exercise influenced cerebral vascular structure of adult mice; vascular plasticity has been shown to occur in young mice, but whether adults also exhibited this phenomenon was unknown. I used customized software to convert time series of vascular image stacks into a collection of undirected graphs, and developed an open-source browser using Python to make the analysis publicly accessible. I discovered no systemic change in capillary diameter but did observe that pruning occurred for a small number of vessels that were part of short cycles in the vascular network, potentially indicating that cerebral vasculature selectively removes vessels that make the local network inefficient.