Our Team

Ben Dichter


Ben received his Ph.D. in Bioengineering from the  UC Berkeley – UCSF Joint Program in Bioengineering, in Dr. Edward Chang’s lab . There he used electrocorticography (ECoG) to study the neural control of speech in humans. Much of this work focused on how we control the pitch of our voice when we speak and sing. He is now a data scientist consultant for neuroscience labs, focusing on building systems for sharing of data and analyses.


Saksham Sharda

Saksham Sharda received his BE in Industrial Engineering and went on to obtain a MSc in Biomedical Engineering from Case Western Reserve University. His research work has focused on developing computational methods for Brain-Computer Interface systems to improve the quality of life of paralyzed people and helping them regain independence. Specifically, with the help of various Machine Learning and statistical methods, he helped develop an understanding of how the neurons in the human motor cortex produce dexterous finger movements and whether its possible to command the fingers to move in real-time with the power of thought alone.
In general, he is interested in developing robust computational methods to electrically interact with the nervous system for therapeutic purposes.

Daniel Sotoude

Daniel received his Ph.D in Electrical and Computer Engineering in 2014 from University of Western Ontario with a focus on robotics. He continued to work on probabilistic algorithms for haptic feedback for teleoperation, software development in robotics, and sensor fusion. His interests are in dynamic and statistical methods, and development of software for machine learning and data analysis in neuroscience.


Ivan Smalianchuk

Ivan Smalianchuk is currently a Ph.D. candidate at the University of Pittsburgh. His research aims to understand how the premotor cortex aids in the execution of coordinated motor tasks. Specifically, Ivan records and analyzes cortical activity and electromyography (EMG) signals during sequential head and eye movements. He utilizes statistical analyses to assess the nature of the influence premotor cortex has over these movements. Ivan’s secondary project looks at local field potential (LFP) properties in the superior colliculus during eye movements.


Konstantinos Nasiotis

Konstantinos is a PhD Candidate in Computational Neuroscience at McGill University. His research involves invasive, chronically implanted multi-electrode arrays on the visual cortex to study cortical processing during eye-movements.

He also has experience in non-invasive magnetoencephalography recordings for studying eye-movements in humans, working with large volumes of data (~100 GB/hour). He is a lecturer for “Unsupervised machine learning” in computational neuroscience at McGill, and a lead developer of the invasive neurophysiology toolbox embedded within Brainstorm.


Luiz Tauffer

Luiz has a BSc in Electrical Engineering, MSc in Biomedical Engineering and am currently at the late stages of his PhD in Computational Neuroscience.

His research work has been focused on mathematical modelling of biological systems and behaviour, i.e. machine learning and data science applied to the life sciences. He is currently expanding my work to cover for more general machine learning / data science consultancy and software development.


Robert H. Moore

For over 30 years, Robert H. Moore has solved technical challenges through R&D and custom software. His simulation software is used throughout the world to optimize paper machines and to analyze bridges. He holds 13 U.S. patents on electronic sensors and has published 30 papers in a variety of disciplines. He is interested in machine learning, signal processing, materials, structures, energy, and just about anything else that involves developing software. His engineering BS and MS degrees are from Virginia Tech and his PhD is from Carnegie Mellon University.


Kristin Quick

Kristin Quick completed her undergraduate degree in Biomedical Engineering at Rose-Hulman Institute of Technology in 2009 and her PhD in Bioengineering with a focus in Neural Engineering at the University of Pittsburgh in 2015. In her PhD, she worked to improve brain-computer interfaces by understanding the underlying neural manifold of motor cortex in non-human primates, as well as investigated methods to assess sensorimotor performance while using nonvisual feedback.

Her post-graduate work, spanning industry and academia, has involved spatial-domain low-coherence quantitative phase microscopy, two-photon calcium imaging in mice, and continued brain-computer interface development in humans. Dr. Quick’s research interests include understanding how interactions between motor cortex and sensory cortex enable dexterous limb movements and the relationship between contralateral and ipsilateral motor cortex.


Alex Song

Alex Song is a researcher interested in emergent microscopy techniques for use in neuroscience research, especially the adaptation of techniques that can be used in vivo. He recently received my Ph.D. in Physics and Neuroscience from Princeton University in Dr. David Tank’s laboratory developing techniques for large-scale two-photon calcium imaging.