Nicholas Hardy, PhD

Machine Learning Research Engineer at Synchron

Nicholas Hardy, PhD has a diverse work experience that spans over several years. Nicholas is currently employed at Synchron as a Machine Learning Research Engineer. Prior to this, they worked at Venture Capital as a Research Advisor, where they provided technical guidance for investments in the mental health sector. Nicholas conducted research and effectively communicated technical and statistical information to non-technical audiences.

From 2018 to 2021, Nicholas served as a Postdoctoral Scholar at the University of California, San Francisco. In this role, they developed cutting-edge brain-computer interface (BCI) technology for neural prosthetic medical devices.

Before that, they were a PhD Candidate at the University of California, Los Angeles from 2012 to 2018. Nicholas conducted research in the laboratory of Dr. Dean Buonomano and focused on studying the role of recurrent neural network dynamics in sensory and motor computations. Additionally, they developed computational models of neural networks and employed various approaches such as psychophysics, electrophysiology, and calcium imaging to study neuroscience. Nicholas also managed and analyzed large datasets, and developed innovative data analysis tools.

In 2017, Nicholas worked as an Intern at The Johns Hopkins University Applied Physics Laboratory, where they contributed to the development of applications for neuromorphic computing and brain-computer interface technologies. Nicholas also assisted in improving the decoding of neural time series data for semantic classification.

Additionally, Nicholas has held various committee and leadership positions. Nicholas served as a Committee Member for the UCLA Neuroscience Interdepartmental Program Executive Committee from 2015 to 2017, and as a Member of the UCLA Neuroscience Interdepartmental Program and UCLA Brain Research Institute Admissions Committee in 2014 and 2015, respectively.

Earlier in their career, Nicholas worked as a Research Assistant at The Lieber Institute for Brain Development and as an Intramural Research Training Awardee at The National Institute of Mental Health. In these roles, they conducted research on genetic and neural network mechanisms underlying mental health disorders, particularly schizophrenia and depression. Nicholas co-authored multiple peer-reviewed research articles.

Overall, Nicholas Hardy, PhD has demonstrated expertise in machine learning, brain-computer interface technology, neural network dynamics, and neuroscience research. Nicholas has effectively communicated technical information to non-technical audiences and has a strong publication record in the field of mental health and neuroscience.

Nicholas Hardy, PhD, obtained their Bachelor of Science (B.S.) degree in Psychology from the University of Maryland in the years 2005 to 2009. Following this, they pursued further education in the field of Neuroscience and earned their Doctor of Philosophy (Ph.D.) from UCLA from 2012 to 2018.

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Timeline

  • Machine Learning Research Engineer

    July, 2022 - present