Paulo Aguiar graduated in Physics (“Engª Física Tecnológica”) from Instituto Superior Técnico, University of Lisbon, Portugal, and completed the course work in the Biophysics Doctoral Program at the Institute for Biophysics and Biomedical Engineering, University of Lisbon in 2001 (final grade 95/100, among the highest achieved in the program). He then moved to the United Kingdom to continue his studies at the Institute for Adaptive and Neural Computation, University of Edinburgh. After finishing his PhD in Computational Neuroscience (U. Edinburgh, 2006) he joined, as a postdoc in neurobiology, the Neuroscience Unit at the Institute for Molecular and Cellular Biology (IBMC), Portugal. In 2008 he was awarded a competitive researcher grant in Computational Biology, and in 2013 he was invited to join the National Institute for Biomedical Engineering (INEB) as an Assistant Investigator.
Since 2016 he is a Principal Investigator at the Institute for Research and Innovation in Health (i3S), where he leads the Neuroengineering and Computational Neuroscience Lab (NCN). His group follows a “neural computation” perspective and is focused on understanding how neural circuits are capable of transmitting, processing and storing information. The team combines expertise in neurobiology, electrophysiology and in vitro neuronal cultures with computational models and neuroengineering tools, to reveal and repair neural function.
In 2019 he was elected Vice-Coordinator of the Neurobiology and Neurologic Disorders Research Program at i3S (harboring 23 research groups), and he is also invited Associate Prof. at ICBAS, invited Associate Prof. in Neuroengineering at Faculty of Engineering, and Affiliate Prof. in Biophysics at Faculty of Medicine, all at Univ. of Porto. He has been responsible for several courses in physics, mathematics, neurobiology and engineering, and has received a Univ. of Porto Pedagogical Score of 6.7/7.0 by the students. He has supervised and co-supervised 16 PhD students (completed + ongoing).
Paulo Aguiar is author in 70+ international peer-reviewed publications (including in Science, ACS Nano, Nat. Cell Biology, J. Neuroscience, PNAS, J. Neural Eng., Medical Image Analysis; over 3000+ citations and an h-factor of 24) and is the core developer of several scientific open-source software (collectively with +14,700 registered downloads). He has been already (co)PI/Task Leader in 18 national and international research projects, obtained in competitive calls.
Selected Publications
Disrupting abnormal neuronal oscillations with adaptive delayed feedback control. eLife13:, 2024. [Journal: Article] [IF: 6.4 (*)]
DOI: 10.7554/eLife.89151 SCOPUS: 85190939220
Oliveira A.M., Carvalho E., Barros B., Soares C., Ferreira-Pinto M.J., Vaz R., Aguiar P.
DBScope as a versatile computational toolbox for the visualization and analysis of sensing data from deep brain stimulation. npj Parkinson's Disease10(1):, 2024. [Journal: Article] [IF: 6.7 (*)]
DOI: 10.1038/s41531-024-00740-z SCOPUS: 85198638602
Mateus J.C., Sousa M.M., Burrone J., Aguiar P.
Beyond a Transmission Cable—New Technologies to Reveal the Richness in Axonal Electrophysiology. Journal of Neuroscience44(11):, 2024. [Journal: Article] [CI: 2] [IF: 4.4 (*)]
DOI: 10.1523/JNEUROSCI.1446-23.2023 SCOPUS: 85187697885
Horton S., Mastrolia V., Jackson R.E., Kemlo S., Pereira Machado P.M., Carbajal M.A., Hindges R., Fleck R.A., Aguiar P., Neves G., Burrone J.
Excitatory and inhibitory synapses show a tight subcellular correlation that weakens over development. Cell Reports43(7):, 2024. [Journal: Article] [CI: 1] [IF: 7.5 (*)]
DOI: 10.1016/j.celrep.2024.114361 SCOPUS: 85196183410
Manubens-Gil L., Zhou Z., Chen H., Ramanathan A., Liu X., Liu Y., Bria A., Gillette T., Ruan Z., Yang J., Radojević M., Zhao T., Cheng L., Qu L., Liu S., Bouchard K.E., Gu L., Cai W., Ji S., Roysam B., Wang C.W., Yu H., Sironi A., Iascone D.M., Zhou J., Bas E., Conde-Sousa E., Aguiar P., Li X., Li Y., Nanda S., Wang Y., Muresan L., Fua P., Ye B., He H.y., Staiger J.F., Peter M., Cox D.N., Simonneau M., Oberlaender M., Jefferis G., Ito K., Gonzalez-Bellido P., Kim J., Rubel E., Cline H.T., Zeng H., Nern A., Chiang A.S., Yao J., Roskams J., Livesey R., Stevens J., Liu T., Dang C., Guo Y., Zhong N., Tourassi G., Hill S., Hawrylycz M., Koch C., Meijering E., Ascoli G.A., Peng H.
BigNeuron: a resource to benchmark and predict performance of algorithms for automated tracing of neurons in light microscopy datasets. Nature Methods20(6):824-835, 2023. [Journal: Article] [CI: 25] [IF: 36.1]
DOI: 10.1038/s41592-023-01848-5 SCOPUS: 85153062588
Oliveira A.M., Coelho L., Carvalho E., Ferreira-Pinto M.J., Vaz R., Aguiar P.
Machine learning for adaptive deep brain stimulation in Parkinson’s disease: closing the loop. Journal of Neurology270(11):5313-5326, 2023. [Journal: Review] [CI: 17] [IF: 4.8]
DOI: 10.1007/s00415-023-11873-1 SCOPUS: 85166426864
Dias C., Castro D., Aroso M., Ventura J., Aguiar P.
Memristor-Based Neuromodulation Device for Real-Time Monitoring and Adaptive Control of Neuronal Populations. ACS Applied Electronic Materials4(5):2380-2387, 2022. [Journal: Article] [CI: 16] [IF: 4,7]
DOI: 10.1021/acsaelm.2c00198 SCOPUS: 85130149541
Mateus J.C., Weaver S., Van Swaay D., Renz A.F., Hengsteler J., Aguiar P., Vörös J.
Nanoscale Patterning of in Vitro Neuronal Circuits. ACS Nano16(4):5731-5742, 2022. [Journal: Article] [CI: 10] [IF: 17,1]
DOI: 10.1021/acsnano.1c10750 SCOPUS: 85129103498
Mateus J.C., Lopes C.D.F., Aroso M., Costa A.R., Gerós A., Meneses J., Faria P., Neto E., Lamghari M., Sousa M.M., Aguiar P.
Bidirectional flow of action potentials in axons drives activity dynamics in neuronal cultures. Journal of Neural Engineering18(6):, 2021. [Journal: Article] [CI: 10] [IF: 5]
DOI: 10.1088/1741-2552/ac41db SCOPUS: 85122868659
Teixeira H., Dias C., Aguiar P., Ventura J.
Gold-Mushroom Microelectrode Arrays and the Quest for Intracellular-Like Recordings: Perspectives and Outlooks. Advanced Materials Technologies6(2):, 2021. [Journal: Review] [CI: 16] [IF: 8,9]
DOI: 10.1002/admt.202000770 SCOPUS: 85097519751
Polónia A., Campelos S., Ribeiro A., Aymore I., Pinto D., Biskup-Fruzynska M., Veiga R.S., Canas-Marques R., Aresta G., Araújo T., Campilho A., Kwok S., Aguiar P., Eloy C.
Artificial Intelligence Improves the Accuracy in Histologic Classification of Breast Lesions. American Journal of Clinical Pathology155(4):527-536, 2021. [Journal: Article] [CI: 19] [IF: 5,4]
DOI: 10.1093/ajcp/aqaa151 SCOPUS: 85102964948
Gerós A., Magalhães A., Aguiar P.
Improved 3D tracking and automated classification of rodents’ behavioral activity using depth-sensing cameras. Behavior Research Methods52(5):2156-2167, 2020. [Journal: Article] [CI: 15] [IF: 6,2]
DOI: 10.3758/s13428-020-01381-9 SCOPUS: 85083094268
Castro D., Nunes V., Lima J.T., Ferreira J.G., Aguiar P.
Trackosome: a computational toolbox to study the spatiotemporal dynamics of centrosomes, nuclear envelope and cellular membrane. Journal of Cell Science133(24):, 2020. [Journal: Article] [CI: 3] [IF: 5,3]
DOI: 10.1242/jcs.252254 SCOPUS: 85099992997
Aresta G., Araújo T., Kwok S., Chennamsetty S.S., Safwan M., Alex V., Marami B., Prastawa M., Chan M., Donovan M., Fernandez G., Zeineh J., Kohl M., Walz C., Ludwig F., Braunewell S., Baust M., Vu Q.D., To M.N.N., Kim E., Kwak J.T., Galal S., Sanchez-Freire V., Brancati N., Frucci M., Riccio D., Wang Y., Sun L., Ma K., Fang J., Kone I., Boulmane L., Campilho A., Eloy C., Polónia A., Aguiar P.
BACH: Grand challenge on breast cancer histology images. Medical Image Analysis56:122-139, 2019. [Journal: Article] [CI: 438] [IF: 11,1]
DOI: 10.1016/j.media.2019.05.010 SCOPUS: 85067343074
Mateus J.C., Lopes C.D.F., Cerquido M., Leitão L., Leitão D., Cardoso S., Ventura J., Aguiar P.
Improved in vitro electrophysiology using 3D-structured microelectrode arrays with a micro-mushrooms islets architecture capable of promoting topotaxis. Journal of Neural Engineering16(3):, 2019. [Journal: Article] [CI: 11] [IF: 4,1]
DOI: 10.1088/1741-2552/ab0b86 SCOPUS: 85065810756
Heiney K., Mateus J.C., Lopes C.D.F., Neto E., Lamghari M., Aguiar P.
µSpikeHunter: An advanced computational tool for the analysis of neuronal communication and action potential propagation in microfluidic platforms. Scientific Reports9(1):, 2019. [Journal: Article] [CI: 7] [IF: 4]
DOI: 10.1038/s41598-019-42148-3 SCOPUS: 85064068131