Ben Dichter is the founder of CatalystNeuro. He 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.

GitHub: https://github.com/bendichter

Personal website: bendichter.com

Publications: https://orcid.org/0000-0001-5725-6910

Contact: ben.dichter@catalystneuro.com

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.

GitHub: https://github.com/luiztauffer
Linkedin: https://www.linkedin.com/in/luiz-tauffer
Blog: https://luiztauffer.github.io/guacamole-data-science/

Alessio Buccino has a BSc and MSc in biomedical engineering and an MSc in computer science. During his PhD at the University of Oslo, he explored the use of advanced modeling techniques and engineering solution to improve the state-of-the-art methods in extracellular electrophysiology for high-density neural probes, from spike sorting to selective electrical stimulation. Alessio is the lead architect of the SpikeInterface platform. He is currently an Electrophysiology Pipeline Development Engineer at the Allen Institute for Neural Dynamics, where he builds standardized and efficient pipelines for the analysis of large-scale electrophysiology data.

Publications

Cody earned his PhD in Applied and Computational Mathematics and Statistics (ACMS) at the University of Notre Dame while working in the Rosenbaum Group for Theoretical and Computational Neuroscience. His thesis focused on inference problems for second-order moments of activity in biological neural networks, including spike-time correlations, balance regimes, and synaptic structure. In particular, his primary interests focus on information processing and flow through biophysical neural models, which can eventually allow a thorough understanding of high-level cognitive function.

Ramón Heberto Martinez Mayorquin has a BSC in Physics and an MSc in Complexity Science and a Ph.D. in Computational Neuroscience. During his Ph.D., he studied in the theoretical and computational study of associative neural networks (e.g. Hopfield Network). During his studies, he has developed an interest in software practices that assure efficient, reproducible, and robust scientific simulations. This, together with his love for statistics and data wrangling has led him to move forward with a career in data science where he can combine and further develop those interests.

Paul Adkisson received his B.S. in Neuroscience from the University of California Los Angeles and his M.S.E. in Biomedical Engineering from Johns Hopkins.  In his Master’s research, he investigated the effects of different types of electrical stimulation on networks of neurons using computational models.  Now, he works on the SpikeInterface platform to develop modular spike sorting pipelines available to all.  In his free time he enjoys rock climbing and backpacking.

Szonja comes from the interdisciplinary field between computer science and neuroscience. She holds a BSc and MSc in Info-bionics Engineering, and has experience in software development. She is keen to learn about and to build reliable, scalable, and maintainable data analysis tools and pipelines. Besides working at CatalystNeuro, she is also working at the Lyon Neuroscience Research Center (CRNL) as an Engineer in a research group interested in learning and memory in the field of Cognitive Neuroscience.

Github: https://github.com/weiglszonja
Linkedin: https://www.linkedin.com/in/weiglszonja/

Dr. Alessandra Trapani received her Ph.D. from Politecnico di Milano, in the NearLAB. Her thesis project aimed at modeling cerebellar motor functions in a large-scale spiking neural network (CerebNEST project).