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 a Postdoc at ETH and he is working on combining multiple recording modalities to build accurate and better validated single neuron models.

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 while currently working on the late stages of a Ph.D. in Computational Neuroscience. During his Ph.D., he has been interested 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.

Julia Sprenger has a BSc and MSc in physics from the RWTH Aachen University. During her master thesis and PhD at the Jülich Research Centre, she investigated spike-LFP relations using massively parallel extracellular electrophysiology recordings and related artefacts as well as data and metadata organization for the generation of FAIR electrophysiology datasets. She is the author of the odMLtables package for simplified metadata collection.

She is currently a research engineer at the Institut de Neurosciences de la Timone in Marseille where she works on the development and implementation of data and metadata standards for electrophysiology datasets. She is co-leading the BIDS Extension Proposal 032 for animal electrophysiology and is a maintainer of the Neo package for electrophysiology data representation and conversion.

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/

Melissa Hersh graduated with a B.A. in Psychology from Elon University and then pursued a career in managing businesses and teams. With over 18 years of experience, her business aptitude spans several industries, including hospitality, events, online retail, music, and nonprofits. With an analytical head for numbers, a certification in Human Resources, marketing & branding knowledge, and vast experience at implementing process changes, her general management skills help CatalystNeuro grow by providing consistency and efficiency to our business processes.