We recognize that the institutions of science have often privileged some people at the expense of others. In the Autonomous Empirical Research Group, we know that we must do better. Thus, we value and invite group members’ efforts to create systemic change both within our group and in the broader scientific community.
We also believe that our research is altogether better with a diverse team. As such, we embrace and encourage our members’ differences in age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other characteristics that make our members who they are.
Our team is not confined to a single geographic area or type of institution. Instead, we welcome talented students and researchers from around the world, who come from varied backgrounds and have interests in neuroscience, cognitive science, psychology, computer science, artificial intelligence, machine learning, statistics, and/or physics.
Are you interested in joining us? If you are interested in learning more about our research or joining the Autonomous Empirical Research group, reach out to us via firstname.lastname@example.org.
Ben Andrew is group manager at the Autonomous Empirical Research Group. As part researcher and part facilitator, he enjoys enabling others and building infrastructure to improve science and technological development. More broadly, he is interested in tools, discoveries, and people that can augment human potential and well-being. To varying degrees, he has trained as a researcher, program manager, early-stage entrepreneur, and investor.
George Dang is a senior data scientist at the Center for Computation and Visualization at Brown University as well as a member of the Autonomous Empirical Research Group. He received his Masters in Environmental Science and Engineering at the University of North Carolina at Chapel Hill. George is leading the design of interfaces between autonomous theorists and experimentalists in AutoRA.
Marina Dubova is a current PhD candidate in cognitive science at Indiana University. Marina develops formal (e.g. computational models) and empirical methods to put the foundations of scientific method to rigorous tests and use insights from cognitive science to better understand the mechanisms of scientific discovery.
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Joshua Hewson is a recent graduate of Williams College. Joshua has a background in data science, cognitive science, and mathematics. He is adapting and extending AutoRA methods for automated equation discovery. In addition, Joshua is working to enhance the functionality of EEG-GAN.
John G. Holland is a senior data scientist at the Center for Computation and Visualization at Brown University as well as a member of the Autonomous Empirical Research Group. He received his PhD in Astrophysics at the Max Planck Institute for Extraterrestrial Physics in Garching. John is leading our efforts of open-sourcing and releasing AutoRA. He is helping re-design the system architecture of our toolbox.
[Mail] [Github] [Web]
Brian Ji is a freshman at Brown University. Brian is automating the documentation of experimental designs generated by SweetPea using transformers.
Ioana Marinescu is a junior studying Computer Science at Princeton University. Ioana is adapting AutoRA methods for equation discovery and is exploring ways of integrating high-level knowledge into the search process.
Sebastian Musslick is an Assistant Professor of Cognitive, Linguistic, and Psychological Sciences (Research) at Brown University, Schmidt Science Fellow, BRAINSTORM Innovator at the Carney Institute for Brain Science, an incoming Assistant Professor of Computational Neuroscience at Osnabrück University. Before joining Brown University, Sebastian received his Ph.D. in Quantitative and Computational Neuroscience at Princeton University. Aside from directing the AER Group, Sebastian is studying limitations in the human mind's capacity to exert mental effort and the consequences of these limitations for natural and artificial cognition.
[Mail] [Twitter] [Github] [Web]
Younes Strittmatter is a research assistant at the Autonomous Empirical Research Group. Younes received his BA in Computer Science and Psychology at the University of Freiburg. He is general interest lies in the integration of AI in cognitive neuroscience, applied to the study of mental effort and cognitive control. Younes is enhancing AutoRA with interfaces for behavioral experimentation.
Chad Williams is a postdoctoral fellow at the Autonomous Research Group. He received his PhD in Neuroscience from the University of Victoria. Chad's research focuses on the investigation of neural systems that underlie human reasoning, using a combination of electroencephalography (EEG) and automated computational modeling. Chad is one of the lead authors of EEG-GAN, a tool for augmenting EEG data using Generative Adversarial Networks.
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Mikako Inaba (Princeton University)
Isabella Pu (Princeton University)
Jessica (JT) Tao (Princeton University)