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Portrait photo of Andrea Giovannucci
Portrait photo of Andrea Giovannucci

Research Staff

Andrea Giovannucci, Ph.D.

Data Scientist, Center for Computational Neuroscience

Affiliations
  • Assistant Professor, Neural Engineering, UNC/NCSU Department of Bioengineering

Dr. Giovannucci is an Assistant Professor in Neural Engineering at the UNC/NCSU department of Bioengineering. Prior to this appointment, Dr. Giovannucci was a machine learning data scientist at the Flatiron Institute (Simons Foundation) and a postdoctoral fellow (experimental neuroscience) at the Princeton Neuroscience Institute. Dr. Giovannucci obtained his PhD in artificial intelligence from the University of Barcelona and the Artificial Intelligence Research Institute of Spain. Dr. Giovannucci is affiliated with the UNC/NCSU joint Bioengineering department, the Closed loop Engineering for Advanced Rehabilitation (CLEAR) and the UNC Neuroscience Center.

Publications

CaImAn an open source tool for scalable calcium imaging data analysis.

Elife., January 17, 2019

A. Giovannucci, J. Friedrich, P Gunn, J Kalfon, BL Brown, SA Koay, et al.

Efficient and accurate extraction of in vivo calcium signals from microendoscopic video data.

Elife, February 22, 2018

P Zhou, SL Resendez, J Rodriguez-Romaguera, JC Jimenez, SQ Neufeld, A. Giovannucci, et al.

NoRMCorre: An online algorithm for piecewise rigid motion correction of calcium imaging data

Journal of Neuroscience Methods, November 1, 2017

E. Pnevmatikakis and A. Giovannucci

OnACID: Online Analysis of Calcium Imaging Data in Real Time, Advances

Advances in Neural Information Processing Systems, October 2, 2017

A. Giovannucci, J. Friedrich, M Kaufman, A Churchland, D. Chklovskii, L Paninski, et al.

Featuring Andrea Giovannucci

An image of neurons (white) taken using calcium imaging techniques. An innovative software dubbed CaImAn can automatically differentiate between individual neurons (yellow outlines) with nearly the same accuracy as a human (red outlines).

Open-Source Software Tracks Neural Activity in Real Time

Comparative images of neuronal data (D) from a low resolution dataset (C) as from a high resolution one (A,B)

Pixelated Movies Yield Faster Way To Image Many Neurons

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Center for Computational Neuroscience

Understanding the human brain is one of the greatest and most challenging scientific frontiers of our time. CCN’s mission is to develop models, principles and conceptual frameworks that deepen our knowledge of brain function — both in health and in disease.

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