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Professor Hirshfield’s research explores the use of non-invasive brain measurement to passively classify users’ social, cognitive, and affective states in order to enhance usability testing and adaptive system design. She works primarily with functional near-infrared spectroscopy (fNIRS), a relatively new non-invasive brain imaging device that is safe, portable, robust to noise, which can be implemented wirelessly; making it ideal for research in human-computer interaction. The high density fNIRS equipment in...

James is a postdoctoral research fellow at the Institute of Cognitive Science. More specifically, he is a cognitive neuroscientist at SHINE Lab. He uses multimodal methods (e.g., fMRI, fNIRS, deep-learning, etc.) in ‘real-world’ and lab-based paradigms to investigate the neurocognitive mechanisms supporting cognitive security (i.e., how the brain defends against information-based threats). This research is supported by the Department of Defense’s Multidisciplinary University Research Initiatives (MURI) Program.

Alex Arnold is a first-year PhD student in computer science working in the SHINE lab. His research interests are in using computer science and computational methods to better understand human intelligence and cognition. His previous research includes topics in machine learning, neuro-symbolic learning, and music cognition.

Michael is a first year PhD student in computer science interested in AI development, human-AI teaming, and planning. Before coming to Boulder, Michael conducted research with Dr. Nancy Cooke in the Center for Human, AI, and Robot Teaming at Arizona State University, and he holds a B.S in mathematics.

Emily Doherty is a fourth-year PhD student in computer and cognitive science working in the SHINE Lab. Her research explores human-AI teaming using multimodal methods (non-invasive neuroimaging, natural language processing, machine learning) in varied contexts spanning from education to extreme environments. She is particularly interested in the design of equitable AI that not only enhances cognitive capabilities but also broadly serves society.

Amanda Hernandez is a first-year PhD student in the Computer and Cognitive Sciences program. Her research interests focus broadly on how computational models can enhance our understanding of cognitive processes and their applications in artificial intelligence. She received a B.Sc. in Cognitive Neuroscience and Computer Science from Brown University where she was also able to contribute to research on AI applications in neuroscience.

Zachary Kaufman is a first-year PhD student in Computer, Cognitive, and Neural sciences. He holds a B.S. in Intelligent Systems Engineering with a minor in Creative Technologies in Art & Design, and a M.S. degree in Intelligent Systems Engineering concentrating in Neuroengineering; both from Indiana University Bloomington. Zach has four years of research experience in human-robot interaction, social sciences, and physiological signal interpretation. His primary research interests are in developing...

Melissa McLain is a first-year PhD student in the Computer and Cognitive Sciences program. She is also a Lt Col in the United States Air Force and leads development of Resiliency Against Disinformation programs for the Air Force. Melissa is interested in developing evidence backed educational approaches to safeguard cognitive processes from cognitive manipulation, primarily in the form of adversarial narratives propagated across social media platforms. Her background is in...

Jalynn Nicoly is a first-year PhD student in the Computer Science Department interested in the intersection between augmented reality and brain computer interfaces. She recently graduated from Colorado State University with four years of research experience and second author of an ACM TAP published paper. She aims to conduct research at a National Laboratory.

Cara Spencer is a fourth-year computer science PhD student working in the SHINE Lab. Her research interests are in measurement and modeling of human and team performance through non-invasive, unobtrusive measurement and machine learning. Ultimately, she would like to conduct this research for high performing populations such as pilots and astronauts and in extreme or unique conditions, such as wilderness expeditions and AI-teams.

Akarea Steele is a third-year Undergraduate Research Assistant studying Neuroscience and Psychology. She has collected data for several studies involving AI and VR and has experience utilizing EEG and fNIRS technologies.

Nitin Kumar is a recent MS graduate and applied researcher at SHINE. He has strong expertise in Artificial Intelligence and Software Development. His focus is on researching in the area of biologically inspired architectures for Deep Learning as well applications of AI in Neuroscience, NLP and Robotics.

Michal (B.S. Computer Science, B.S. Creative Technology and Design) is interested in innovating Human-Computer Interaction to be more seamless, beautiful, and socially beneficial. During his time at SHINE, he was responsible for applied programming, working on testbeds (web, desktop), as well as a full-stack developer for the NSF Insititute for Student-AI Teaming (iSAT), where he worked on dashboards and tools utilizing the institute's AI models. He is now a software...

Reid is a CU Boulder graduate with a B.A. in Neuroscience and Psychology. His research interests include neuroimaging and spectroscopy, as well as the functional regions of the brain devoted to social cognition, affective states, and decision making. He oversaw data collections and participant interactions to further develop the fNIRS datasets at the SHINE lab.

Jack is a recent graduate at the ÀÖ²¥´«Ã½. He is passionate about team dynamic and optimization research, psychology, and data science. His research interest is in the exciting psychological and behavioral insights that can be generated with machine learning models on fNIRS data.

Lucca Eloy is a PhD graduate in computer and cognitive science. His research explores the neural and physiological correlates of affective states that can be derived from non-invasive brain measurement and various multimodal signals. In particular, he studies emotions that arise during human-machine interaction and teaming. He is interested in using linear and nonlinear statistical methods alongside machine learning to better understand and design systems that adapt to human cognition...

Rajshekar G S is a Masters student in the Computer Science department and previously worked as a Research Assistant at the Indian Institute of Science. His research focuses on immersive technologies such as Virtual and Augmented Reality and figuring out effortless interaction mediums for the said technologies that lessen cognitive processing and improve decision-making abilities. He is now a software engineer at Intuitive.

Brian Tan is a previous Undergraduate Research Assistant in the SHINE Lab. He holds a Bachelor's degree in Computer Science and Mathematics. His research interest falls under Brain Computer Interfaces, specifically in Motor Imagery (MI) and also translating conscious thoughts to text. He is now a PhD student at Colorado State University.