[Link to Preprints]

  1. Multi-cohort and longitudinal Bayesian clustering study of stage and subtype in Alzheimer’s disease
    Konstantinos Poulakis, Joana B. Pereira, J.-Sebastian Muehlboeck, Lars-Olof Wahlund, Örjan Smedby, Giovanni Volpe, Colin L. Masters, David Ames, Yoshiki Niimi, Takeshi Iwatsubo, Daniel Ferreira, Eric Westman, Japanese Alzheimer’s Disease Neuroimaging Initiative & Australian Imaging, Biomarkers and Lifestyle study
    Nature Communications 13, 4566 (2022)
    doi: 10.1038/s41467-022-32202-6
  2. Unraveling Parkinson’s disease heterogeneity using subtypes based on multimodal data
    Franziska Albrecht, Konstantinos Poulakis, Malin Freidle, Hanna Johansson, Urban Ekman, Giovanni Volpe, Eric Westman, Joana B. Pereira, Erika Franzén
    Parkinsonism and Related Disorders 102, 19-29 (2022)
    doi: 10.1016/j.parkreldis.2022.07.014
  3. Neural Network Training with Highly Incomplete Datasets
    Yu-Wei Chang, Laura Natali, Oveis Jamialahmadi, Stefano Romeo, Joana B. Pereira, Giovanni Volpe
    Machine Learning: Science and Technology 3, 035001 (2022)
    arXiV: 2107.00429
    doi: 10.1088/2632-2153/ac7b69
  4. Deep learning in light–matter interactions
    Daniel Midtvedt, Vasilii Mylnikov, Alexander Stilgoe, Mikael Käll, Halina Rubinsztein-Dunlop and Giovanni Volpe
    Nanophotonics, 11(14), 3189-3214 (2022)
    doi: 10.1515/nanoph-2022-0197
  5. Label-free nanofluidic scattering microscopy of size and mass of single diffusing molecules and nanoparticles
    Barbora Špačková, Henrik Klein Moberg, Joachim Fritzsche, Johan Tenghamn, Gustaf Sjösten, Hana Šípová-Jungová, David Albinsson, Quentin Lubart, Daniel van Leeuwen, Fredrik Westerlund, Daniel Midtvedt, Elin K. Esbjörner, Mikael Käll, Giovanni Volpe & Christoph Langhammer
    Nature Methods 19, 751–758 (2022)
    doi: 10.1038/s41592-022-01491-6
  6. Directed Brain Connectivity Identifies Widespread Functional Network Abnormalities in Parkinson’s Disease
    Mite Mijalkov, Giovanni Volpe, Joana B Pereira
    Cerebral Cortex 32(3), 593–607 (2022)
    doi: 10.1093/cercor/bhab237
  7. Multiplex Connectome Changes across the Alzheimer’s Disease Spectrum Using Gray Matter and Amyloid Data
    Mite Mijalkov, Giovanni Volpe, Joana B Pereira
    Anna Canal-Garcia, Emiliano Gómez-Ruiz, Mite Mijalkov, Yu-Wei Chang, Giovanni Volpe, Joana B Pereira, Alzheimer’s Disease Neuroimaging Initiative
    Cerebral Cortex, bhab429 (2022)
    doi: 10.1093/cercor/bhab429
  8. Comparison of Two-Dimensional- and Three-Dimensional-Based U-Net Architectures for Brain Tissue Classification in One-Dimensional Brain CT
    Meera Srikrishna, Rolf A. Heckemann, Joana B. Pereira, Giovanni Volpe, Anna Zettergren, Silke Kern, Eric Westman, Ingmar Skoog and Michael Schöll
    Frontiers of Computational Neuroscience 15, 785244 (2022)
    doi: 10.3389/fncom.2021.785244
  9. Raman Tweezers for Tire and Road Wear Micro- and Nanoparticles Analysis
    Pietro Giuseppe Gucciardi, Gillibert Raymond, Alessandro Magazzù, Agnese Callegari, David Brente Ciriza, Foti Antonino, Maria Grazia Donato, Onofrio M. Maragò, Giovanni Volpe, Marc Lamy de La Chapelle & Fabienne Lagarde
    Environmental Science: Nano 9, 145 – 161 (2022)
    Featured in:
    University of Gothenburg: New technology enables the detection of microplastics from road wear New technology enables the detection of microplastics from road wear
    Nonsologreen: Le Raman-tweezers per la guerra alle nanoplastiche che inquinano fiumi e mari
  10. Objective comparison of methods to decode anomalous diffusion
    Gorka Muñoz-Gil, Giovanni Volpe, Miguel Angel Garcia-March, Erez Aghion, Aykut Argun, Chang Beom Hong, Tom Bland, Stefano Bo, J. Alberto Conejero, Nicolás Firbas, Òscar Garibo i Orts, Alessia Gentili, Zihan Huang, Jae-Hyung Jeon, Hélène Kabbech, Yeongjin Kim, Patrycja Kowalek, Diego Krapf, Hanna Loch-Olszewska, Michael A. Lomholt, Jean-Baptiste Masson, Philipp G. Meyer, Seongyu Park, Borja Requena, Ihor Smal, Taegeun Song, Janusz Szwabiński, Samudrajit Thapa, Hippolyte Verdier, Giorgio Volpe, Arthur Widera, Maciej Lewenstein, Ralf Metzler, and Carlo Manzo
    Nature Communications 12, Article number: 6253 (2021)
    doi: 10.1038/s41467-021-26320-w
    arXiv: 2105.06766
    Featured in:
    A scientific competition led to improved methods for analysing the diffusion of particles.
    En vetenskaplig tävling ledde till förbättrade metoder för att analysera diffusion av partiklar.
  11. Active droploids
    Jens Grauer, Falko Schmidt, Jesús Pineda, Benjamin Midtvedt, Hartmut Löwen, Giovanni Volpe & Benno Liebchen
    Nature Commununications 12, 6005 (2021)
    doi: 10.1038/s41467-021-26319-3
    arXiv: 2109.10677
    Featured in:
  12. The environment topography alters the transition from single-cell populations to multicellular structures in Myxococcus xanthus
    Karla C. Hernández Ramos, Edna Rodríguez-Sánchez, Juan Antonio Arias del Angel, Alejandro V. Arzola, Mariana Benítez, Ana E. Escalante, Alessio Franci, Giovanni Volpe, Natsuko Rivera-Yoshida
    Sci. Adv. 7(35), eabh2278 (2021)
    bioRxiv: 10.1101/2021.01.27.428527
    doi: 10.1126/sciadv.abh2278
  13. The Cognitive Connectome in Healthy Aging
    Eloy Garcia-Cabello, Lissett Gonzalez-Burgos, Joana B. Pereira, Juan Andres Hernández-Cabrera, Eric Westman, Giovanni Volpe, José Barroso, & Daniel Ferreira
    Front. Aging Neurosci. 13, 530 (2021)
    doi: 10.3389/fnagi.2021.694254
  14. Enhanced prediction of atrial fibrillation and mortality among patients with congenital heart disease using nationwide register based medical hospital data and neural networks
    Kok Wai Giang, Saga Helgadottir, Mikael Dellborg, Giovanni Volpe, Zacharias Mandalenakis
    European Heart Journal – Digital Health (2021)
    doi: 10.1093/ehjdh/ztab065
  15. Directed Brain Connectivity Identifies Widespread Functional Network Abnormalities in Parkinson’s Disease
    Mite Mijalkov, Giovanni Volpe, Joana B Pereira
    Cerebral Cortex, bhab237 (2021)
  16. Microscopic Metavehicles Powered and Steered by Embedded Optical Metasurfaces
    Daniel Andrén, Denis G. Baranov, Steven Jones, Giovanni Volpe, Ruggero Verre, Mikael Käll
    Nat. Nanotechnol. (2021)
    doi: 10.1038/s41565-021-00941-0
    arXiv: 2012.10205
  17. Extracting quantitative biological information from brightfield cell images using deep learning
    Saga Helgadottir, Benjamin Midtvedt, Jesús Pineda, Alan Sabirsh, Caroline B. Adiels, Stefano Romeo, Daniel Midtvedt, Giovanni Volpe
    Biophysics Rev. 2, 031401 (2021)
    arXiv: 2012.12986
    doi: 10.1063/5.0044782
    Featured in:
    “Staining Cells Virtually Offers Alterative Approach to Chemical Dyes”, AIP SciLight (July 23, 2021)
  18. Classification, inference and segmentation of anomalous diffusion with recurrent neural networks
    Aykut Argun, Giovanni Volpe, Stefano Bo
    Journal of Physics A: Mathematical Theoretical 54 294003 (2021)
    doi: 10.1088/1751-8121/ac070a
    arXiv: 2104.00553
  19. Dendritic spines are lost in clusters in patients with Alzheimer’s disease
    Mite Mijalkov, Giovanni Volpe, Isabel Fernaud-Espinosa, Javier DeFelipe, Joana B. Pereira, Paula Merino-Serrais
    Scientific Report 11, 12350 (2021)
    doi: 10.1038/s41598-021-91726-x
    biorXiv: 10.1101/2020.10.20.346718
  20. Age-related differences in network structure and dynamic synchrony of cognitive control
    T. Hinault, M. Mijalkov, J.B. Pereira, Giovanni Volpe, A. Bakker, S.M. Courtney
    NeuroImage 236, 118070 (2021)
    bioRxiv: 10.1101/2020.10.09.333567
    doi: 10.1016/j.neuroimage.2021.118070
  21. Non-equilibrium properties of an active nanoparticle in a harmonic potential
    Falko Schmidt, Hana Šípová-Jungová, Mikael Käll, Alois Würger & Giovanni Volpe
    Nature Communications 12, 1902 (2021)
    doi: 10.1038/s41467-021-22187-z
    arXiv: 2009.08393
  22. Improving epidemic testing and containment strategies using machine learning
    Laura Natali, Saga Helgadottir, Onofrio M. Maragò, Giovanni Volpe
    Machine Learning: Science and Technology, 2 035007 (2021)
    doi: 10.1088/2632-2153/abf0f7
    arXiv: 2011.11717
    Featured in:
    Maskininlärning kan bidra till att bromsa framtida pandemier, Press release, News of the Faculty of Science of Gothenburg University.
    Machine learning can help slow down future pandemics Press release, News of the Faculty of Science of Gothenburg University.
  23. Optical Tweezers: A Comprehensive Tutorial from Calibration to Applications
    Jan Gieseler, Juan Ruben Gomez-Solano, Alessandro Magazzù, Isaac Pérez Castillo, Laura Pérez García, Marta Gironella-Torrent, Xavier Viader-Godoy, Felix Ritort, Giuseppe Pesce, Alejandro V. Arzola, Karen Volke-Sepulveda & Giovanni Volpe
    Advances in Optics and Photonics 13(1), 74-241 (2021)
    arXiv: 2004.05246
  24. Quantitative Digital Microscopy with Deep Learning
    Benjamin Midtvedt, Saga Helgadottir, Aykut Argun, Jesús Pineda, Daniel Midtvedt, Giovanni Volpe
    Applied Physics Reviews 8, 011310 (2021)
    doi: 10.1063/5.0034891
    arXiv: 2010.08260
  25. Optical trapping and critical Casimir forces
    Agnese Callegari, Alessandro Magazzù, Andrea Gambassi & Giovanni Volpe
    The European Physical Journal Plus (EPJP), 136, 213 (2021)
    doi: 10.1140/epjp/s13360-020-01020-4
    arXiv: 2008.01537
  26. Intercellular communication induces glycolytic synchronization waves between individually oscillating cells
    Martin Mojica-Benavides, David D. van Niekerk, Mite Mijalkov, Jacky L. Snoep, Bernhard Mehlig, Giovanni Volpe, Caroline B. Adiels & Mattias Goksör
    PNAS 118(6), e2010075118 (2021)
    doi: 10.1073/pnas.2010075118
    arXiv: 1909.05187
  27. Fast and Accurate Nanoparticle Characterization Using Deep-Learning-Enhanced Off-Axis Holography
    Benjamin Midtvedt, Erik Olsén, Fredrik Eklund, Fredrik Höök, Caroline Beck Adiels, Giovanni Volpe, Daniel Midtvedt
    ACS Nano 15(2), 2240–2250 (2021)
    doi: 10.1021/acsnano.0c06902
    arXiv: 2006.11154
  28. Improving epidemic testing and containment strategies using machine learning
    Laura Natali, Saga Helgadottir, Onofrio M. Maragò, Giovanni Volpe
    doi: 10.1088/2632-2153/abf0f7
    arXiv: 2011.11717
    Featured in:
    News of the Faculty of Science of Gothenburg University
    Swedish: Maskininlärning kan bidra till att bromsa framtida pandemier
    English: Machine learning can help slow down future pandemics
  29. Enhanced force-field calibration via machine learning
    Aykut Argun, Tobias Thalheim, Stefano Bo, Frank Cichos & Giovanni Volpe
    Applied Physics Reviews 7, 041404 (2020)
    doi: 10.1063/5.0019105
    arXiv: 2006.08963
    Featured in:
    “Machine Learning Outperforms Standard Force-Field Calibration Techniques”, AIP SciLight (November 6, 2020)
  30. Feedback-controlled active brownian colloids with space-dependent rotational dynamics
    Miguel Angel Fernandez-Rodriguez, Fabio Grillo, Laura Alvarez, Marco Rathlef, Ivo Buttinoni, Giovanni Volpe & Lucio Isa
    Nature Communications 11, 4223 (2020)
    doi: 10.1038/s41467-020-17864-4
    arXiv: 1911.02291
  31. Machine learning reveals complex behaviours in optically trapped particles
    Isaac C. D. Lenton, Giovanni Volpe, Alexander B. Stilgoe, Timo A. Nieminen & Halina Rubinsztein-Dunlop
    Machine Learning: Science and Technology, 1 045009, (2020)
    doi: 10.1088/2632-2153/abae76
    arXiv: 2004.08264
  32. Anisotropic dynamics of a self-assembled colloidal chain in an active bath
    Mehdi Shafiei Aporvari, Mustafa Utkur, Emine Ulku Saritas, Giovanni Volpe & Joakim Stenhammar
    Soft Matter, 2020, 16, 5609-5614
    arXiv: 2002.09961
  33. Gain-Assisted Optomechanical Position Locking of Metal/Dielectric Nanoshells in Optical Potentials
    Paolo Polimeno, Francesco Patti, Melissa Infusino, Jonathan Sánchez, Maria A. Iatì, Rosalba Saija, Giovanni Volpe, Onofrio M. Maragò & Alessandro Veltri
    ACS Photonics 7(5), 1262–1270 (2020)
  34. Ordering of binary colloidal crystals by random potentials
    André S. Nunes, Sabareesh K. P. Velu, Iryna Kasianiuk, Denys Kasyanyuk, Agnese Callegari, Giorgio Volpe, Margarida M. Telo da Gama, Giovanni Volpe & Nuno A. M. Araújo
    Soft Matter 16, 4267-4273 (2020)
    arXiv: 1903.01579
  35. Delayed correlations improve the reconstruction of the brain connectome
    Mite Mijalkov, Joana B. Pereira & Giovanni Volpe
    PLoS ONE 15(2), e0228334 (2020)
  36. Machine learning for active matter
    Frank Cichos, Kristian Gustavsson, Bernhard Mehlig & Giovanni Volpe
    Nature Machine Intelligence 2(2), 94–103 (2020)
  37. Virtual genetic diagnosis for familial hypercholesterolemia powered by machine learning
    Anna Pina, Saga Helgadottir, Rosellina Margherita Mancina, Chiara Pavanello, Carlo Pirazzi, Tiziana Montalcini, Roberto Henriques, Laura Calabresi, Olov Wiklund, M Paula Macedo, Luca Valenti, Giovanni Volpe, Stefano Romeo
    European Journal of Preventive Cardiology (2020)
  38. Measurement of Anomalous Diffusion Using Recurrent Neural Networks
    Stefano Bo, Falko Schmidt, Ralf Eichborn & Giovanni Volpe
    Physical Review E 100(1), 010102(R) (2019)
    doi: 10.1103/PhysRevE.100.010102
    arXiv: 1905.02038
  39. Influence of Sensorial Delay on Clustering and Swarming
    Rafal Piwowarczyk, Martin Selin, Thomas Ihle & Giovanni Volpe
    Physical Review E 100(1), 012607 (2019)
    doi: 10.1103/PhysRevE.100.012607
    arXiv:  1803.06026
  40. Clustering of Janus Particles in Optical Potential Driven by Hydrodynamic Fluxes
    S. Masoumeh Mousavi, Iryna Kasianiuk, Denis Kasyanyuk, Sabareesh K. P. Velu, Agnese Callegari, Luca Biancofiore & Giovanni Volpe
    Soft Matter 15(28), 5748—5759 (2019)
    doi: 10.1039/C8SM02282H
    arXiv: 1811.01989
  41. Intracavity optical trapping of microscopic particles in a ring-cavity fiber laser
    Fatemeh Kalantarifard, Parviz Elahi, Ghaith Makey, Onofrio M. Maragò, F. Ömer Ilday & Giovanni Volpe
    Nature Communications 10, 2683 (2019)
    doi: 10.1038/s41467-019-10662-7
    arXiv: 1808.07831
  42. Subtypes of Alzheimer’s disease display distinct network abnormalities extending beyond their pattern of brain atrophy
    Daniel Ferreira, Joana B. Pereira, Giovanni Volpe & Eric Westman
    Frontiers in Neurology 10, 524 (2019)
    DOI: 10.3389/fneur.2019.00524
  43. Digital video microscopy enhanced by deep learning (Cover article)
    Saga Helgadottir, Aykut Argun & Giovanni Volpe
    Optica 6(4), 506—513 (2019)
    doi: 10.1364/OPTICA.6.000506
    arXiv: 1812.02653
    GitHub: DeepTrack
    Featured in:
    Deep Learning for Particle Tracking”, Optics & Photonics News (December 1, 2019)
  44. Controlling the dynamics of colloidal particles by critical Casimir forces (Back cover article)
    Alessandro Magazzù, Agnese Callegari, Juan Pablo Staforelli, Andrea Gambassi, Siegfried Dietrich & Giovanni Volpe
    Soft Matter 15(10), 2152—2162 (2019)
    doi: 10.1039/C8SM01376D
    arXiv: 1806.11403
  45. Light-controlled Assembly of Active Colloidal Molecules
    Falko Schmidt, Benno Liebchen, Hartmut Löwen & Giovanni Volpe
    Journal of Chemical Physics 150(9), 094905 (2019)
    doi: 10.1063/1.5079861
    arXiv: 1801.06868
  46. Active Matter Alters the Growth Dynamics of Coffee Rings (Back cover article)
    Tuğba Andaç, Pascal Weigmann, Sabareesh K. P. Velu, Erçağ Pinçe, Giorgio Volpe, Giovanni Volpe & Agnese Callegari
    Soft Matter 15(7), 1488—1496 (2019)
    doi: 10.1039/C8SM01350K
    arXiv: 1803.02619
  47. High-Performance Reconstruction of Microscopic Force Fields from Brownian Trajectories
    Laura Pérez García, Jaime Donlucas Pérez, Giorgio Volpe, Alejandro V. Arzola & Giovanni Volpe
    Nature Communications 9, 5166 (2018)
    doi: 10.1038/s41467-018-07437-x
    arXiv: 1808.05468
  48. Tuning phototactic robots with sensorial delays (Editors’ suggestion)
    Maximilian Leyman, Freddie Ogemark, Jan Wehr & Giovanni Volpe
    Physical Review E 98(26), 052606 (2018)
    DOI: 10.1103/PhysRevE.98.052606
    arXiv: 1807.11765
  49. Abnormal structural brain connectome in individuals with preclinical Alzheimer’s disease
    Joana B. Pereira, Danielle van Westen, Erik Stomrud, Tor Olof Strandberg, Giovanni Volpe, Eric Westman & Oskar Hansson
    Cerebral Cortex 28(10), 3638—3649 (2018)
    DOI: 10.1093/cercor/bhx236

    Featured in “Nuke med helps diagnose early Alzheimer’s from amyloid network topology”, HealthImaging, 14 Nov 2017
  50. Stability of graph theoretical measures in structural brain networks in Alzheimer’s disease
    Gustav Mårtensson, Joana B. Pereira, Patrizia Mecocci, Bruno Vellas, Magda Tsolaki, Iwona Kłoszewska, Hilkka Soininen, Simon Lovestone, Andrew Simmons, Giovanni Volpe & Eric Westman
    Scientific Reports 8, 11592 (2018)
    DOI: 10.1038/s41598-018-29927-0
  51. Optical tweezers and their applications
    Paolo Polimeno, Alessandro Magazzù, Maria Antonia Iata, Francesco Patti, Rosalba  Saija, Cristian Degli Esposti Boschi, Maria Grazia Donato, Pietro G. Gucciardi, Philip H. Jones, Giovanni Volpe & Onofrio M. Maragò
    Journal of Quantitative Spectroscopy and Radiative Transfer 218(October 2018), 131—150 (2018)
    DOI: 10.1016/j.jqsrt.2018.07.013
  52. Active Atoms and Interstitials in Two-dimensional Colloidal Crystals
    Kilian Dietrich, Giovanni Volpe, Muhammad Nasruddin Sulaiman, Damina Renggli, Ivo Buttinoni & Lucio Isa
    Physical Review Letters 120(26), 268004 (2018)
    DOI: 10.1103/PhysRevLett.120.268004
    arXiv: 1710.08680
  53. Biophotonics feature: introduction
    Paolo Campagnola, Daniel Cote, Francesco Pavone, Peter Reece, Vivek J. Srinivasan, Tomasz Tkaczyk & Giovanni Volpe
    Biomedical Optics Express 9(3), 1229–1231 (2018)
    DOI: 10.1364/BOE.9.001229
  54. Microscopic engine powered by critical demixing
    Falko Schmidt, Alessandro Magazzù, Agnese Callegari, Luca Biancofiore, Frank Cichos & Giovanni Volpe
    Physical Review Letters 120(6), 068004 (2018)
    DOI: 10.1103/PhysRevLett.120.068004

    Featured in:
    Focus: A Tiny Engine Powered by Light and Liquid Physics”, Physics 11, 16 (February 9, 2018)
    Laser + Critical Liquid = Micro-Engine”, Optics & Photonics News (February 12, 2018)
    Tiny engine powered by demixing fluid” Phys.Org (February 12, 2018)
    Расслаивание растворителя закрутило микрочастицы вокруг лазерного пучка”, N+1: научные статьи, новости, открытия (February 12, 2018)
    Tiny engine powered by remixing fluid”, Brinkwire (February 16, 2018)
  55. Dynamic control of particle deposition in evaporating droplets by an external point source vapor
    Robert Malinowski, Giovanni Volpe, Ivan Parkin & Giorgio Volpe
    The Journal of Physical Chemistry Letters 9(3), 659—664 (2018)
    DOI: 10.1021/acs.jpclett.7b02831
    arXiv: 1801.08218
  56. Altered structural network organization in cognitively normal individuals with amyloid pathology
    Olga Voevodskaya, Joana B. Pereira, Giovanni Volpe, Olof Lindberg, Erik Stomrud, Danielle van Westen, Eric Westman & Oskar Hansson
    Neurobiology of Aging 64, 15—24 (2018)
    DOI: 10.1016/j.neurobiolaging.2017.11.014
  57. Amyloid network topology characterizes the progression of Alzheimer’s disease during the predementia stages
    Joana B. Pereira, Tor Olof Strandberg, Sebastian Palmqvist, Giovanni Volpe, Danielle van Westen, Eric Westman & Oskar Hansson, for the Alzheimer’s Disease Neuroimaging Initiative
    Cerebral Cortex 28(1), 340—349 (2018)
    DOI: 10.1093/cercor/bhx294
  58. Metastable clusters and channels formed by active particles with aligning interactions
    Simon Nilsson & Giovanni Volpe
    New Journal of Physics 19, 115008 (2017)
    DOI: 10.1088/1367-2630/aa9516
    arXiv: 1706.01326
  59. Experimental realization of a minimal microscopic heat engine
    Aykut Argun, Jalpa Soni, Lennart Dabelow, Stefano Bo, Giuseppe Pesce, Ralf Eichhorn & Giovanni Volpe
    Physical Review E 96(5), 05216 (2017)
    DOI: 10.1103/PhysRevE.96.052106
    arXiv: 1708.07197
  60. The topography of the environment alters the optimal search strategy for active particles
    Giorgio Volpe & Giovanni Volpe
    Proceedings of the National Academy of Science USA 114(43), 11350—11355 (2017)
    DOI: 10.1073/pnas.1711371114
    arXiv: 1706.07785
  61. BRAPH: A graph theory software for the analysis of brain connectivity
    Mite Mijalkov, Ehsan Kakaei, Joana B. Pereira, Eric Westman & Giovanni Volpe
    PLoS ONE 12(8), e0178798 (2017)
    DOI: 10.1371/journal.pone.0178798
    bioRxiv: 106625
  62. Two-dimensional nature of the active Brownian motion of catalytic microswimmers at solid and liquid interfaces
    Kilian Dietrich, Damian Renggli, Michele Zanini, Giovanni Volpe, Ivo Buttinoni & Lucio Isa
    New Journal of Physics 19, 065008 (2017)
    DOI: 10.1088/1367-2630/aa7126
  63. Small Mass Limit of a Langevin Equation on a Manifold
    Jeremiah Birrell, Scott Hottovy, Giovanni Volpe & Jan Wehr
    Annales Henri Poincaré 18(2), 707—755 (2017)
    DOI: 10.1007/s00023-016-0508-3
    arXiv: 1604.04819
  64. Non-Boltzmann stationary distributions and non-equilibrium relations in active baths
    Aykut Argun, Ali-Reza Moradi, Erçağ Pinçe, Gokhan Baris Bagci, Alberto Imparato & Giovanni Volpe
    Physical Review E 94(6), 062150 (2016)
    DOI: 10.1103/PhysRevE.94.062150
  65. Active Brownian particles in complex and crowded environments (Invited review)
    Clemens Bechinger, Roberto Di Leonardo, Hartmut Löwen, Charles Reichhardt, Giorgio Volpe & Giovanni Volpe
    Reviews of Modern Physics 88(4), 045006 (2016)
    DOI: 10.1103/RevModPhys.88.045006
    arXiv: 1602.00081
  66. An SDE approximation for stochastic differential delay equations with colored state-dependent noise
    Austin McDaniel, Ozer Duman, Giovanni Volpe & Jan Wehr
    Markov Processes and Related Fields 22(3), 595-628 (2016)
    arXiv: 1406.7287
  67. Disrupted Network Topology in Patients with Stable and Progressive Mild Cognitive Impairment and Alzheimer’s Disease
    Joana B. Pereira, Mite Mijalkov, Ehsan Kakaei, Patricia Mecocci,
Bruno Vellas, Magda Tsolaki, Iwona Kłoszewska, Hilka Soininen, Christian Spenger, Simmon Lovestone, Andrew Simmons, Lars-Olof Wahlund, Giovanni Volpe & Eric Westman, AddNeuroMed consortium, for the Alzheimer’s Disease Neuroimaging Initiative
    Cerebral Cortex 26(8), 3476—3493 (2016)
    DOI: 10.1093/cercor/bhw128
  68. Better stability with measurement errors
    Aykut Argun & Giovanni Volpe
    Journal of Statistical Physics 163(6), 1477—1485 (2016)
    DOI: 10.1007/s10955-016-1518-8
    arXiv: 1608.08461
  69. Nonadditivity of critical Casimir forces 
    Paladugu Sathyanarayana, Agnese Callegari, Yazgan Tuna, Lukas Barth, Siegfried Dietrich, Andrea Gambassi & Giovanni Volpe
    Nature Communications 7, 11403 (2016)
    DOI: 10.1038/ncomms11403
    arXiv: 1511.02613

    Featured in:
    2+1 is not always 3: In the microworld unity is not always strength”,
    Wenn 2 plus 1 nicht 3 ergibt”, Scinexx
    Физики доказали существование эффекта множества тел”,
    2+1 is not always 3”, Health Medicinet
    Nei colloidi 2 +1 non è uguale a 3”, Le Scienze
    Nei colloidi 2 +1 non è uguale a 3”, All News 24
    Wenn 2 plus 1 nicht 3 ergibt”, Scinexx
    2+1 ist nicht immer 3 – In der Mikro-Welt macht Einigkeit nicht immer”, idw – Informationsdienst Wissenschaft
  70. Effective drifts in dynamical systems with multiplicative noise: A review of recent progress (Invited review)
    Giovanni Volpe & Jan Wehr
    Reports on Progress in Physics 79(5), 053901 (2016)
    DOI: 10.1088/0034-4885/79/5/053901
    arXiv: 1511.05340
  71. Disorder-mediated crowd control in an active matter system
    Erçağ Pinçe, Sabareesh K. P. Velu, Agnese Callegari, Parviz Elahi, Sylvain Gigan, Giovanni Volpe & Giorgio Volpe
    Nature Communications 7, 10907 (2016)
    DOI: 10.1038/ncomms10907

    Featured in:
    Understanding the dynamics of crowd behavior”,
    Understanding the dynamics of crowd behavior”,
    Physics Explains Group Dynamics: When There’s Chaos, Individuals Disperse”, Medical Daily
    Ученые выяснили, как меняющаяся окружающая среда влияет на движение толпы”,
    Understanding the dynamics of crowd behaviour”, Nano
    Understanding the dynamics of crowd behaviour”, Noodls
    Understanding the dynamics of crowd behavior”, EurekAlert!
    Understanding the dynamics of crowd behavior”, Informs
    Understanding the dynamics of crowd behavior”, Nanowerk
  72. The small-mass limit for Langevin dynamics with unbounded coefficients and positive friction
    David P. Herzog, Scott Hottovy & Giovanni Volpe
    Journal of Statistical Physics 163(3), 659—673 (2016)
    DOI: 10.1007/s10955-016-1498-8
    arXiv: 1510.04187
  73. Engineering sensorial delay to control phototaxis and emergent collective behaviors
    Mite Mijalkov, Austin McDaniel, Jan Wehr & Giovanni Volpe
    Physical Review X 6(1), 011008 (2016)
    DOI: 10.1103/PhysRevX.6.011008
    arXiv: 1511.04528

    Featured in “Focus: Sensing Delays Control Robot Swarming
    Physics 9, 13 (January 29, 2016)
  74. Polar POLICRYPS diffractive structures generate cylindrical vector beams
    Domenico Alj, Sathyanarayana Paladugu, Giovanni Volpe, Roberto Caputo & Cesare Umeton
    Applied Physics Letter 107(20), 201101 (2015)
    DOI: 10.1063/1.4935605
    arXiv: 1509.07671
  75. Optical trapping and control of a dielectric nanowire by a nanoaperture
    Mehdi Shafiei Aporvari, Fardin Kheirandish & Giovanni Volpe
    Optics Letters 40(20), 4807—4810 (2015)
    DOI: 10.1364/OL.40.004807
    arXiv: 1507.04044
  76. Aberrant cerebral network topology and mild cognitive impairment in early Parkinson’s disease
    Joana B. Pereira, Dag Aarsland, Cedric E. Ginestet, Alexander V. Lebedev, Lars-Olof Wahlund, Andrew Simmons, Giovanni Volpe & Eric Westman
    Human Brain Mapping 36(8), 2980—2995 (2015)
    DOI: 10.1002/hbm.22822
  77. Formation, compression and surface melting of colloidal clusters by active particles (Cover article)
    Felix Kümmel, Parmida Shabestari, Celia Lozano, Giovanni Volpe & Clemens Bechinger
    Soft Matter 11(31), 6187—6191 (2015)
    DOI: 10.1039/C5SM00827A
  78. The Smoluchowski-Kramers limit of stochastic differential equations with arbitrary state-dependent friction
    Scott Hottovy, Austin McDaniel, Giovanni Volpe & Jan Wehr
    Communications in Mathematical Physics 336(3), 1259—1283 (2015)
    DOI: 10.1007/s00220-014-2233-4
    arXiv: 1404.2330
  79. A step-by-step guide to the realisation of advanced optical tweezers
    Giuseppe Pesce, Giorgio Volpe, Onofrio M. Maragò, Philip H. Jones, Sylvain Gigan, Antonio Sasso & Giovanni Volpe
    Journal of the Optical Society of America B 32(5), B84—B98 (2015)
    DOI: 10.1364/JOSAB.32.000B84
    arXiv: 1501.07894
  80. Computational toolbox for optical tweezers in geometrical optics
    Agnese Callegari, Mite Mijalkov, Burak Gököz & Giovanni Volpe
    Journal of the Optical Society of America B 32(5), B11—B19 (2015)
    DOI: 10.1364/JOSAB.32.000B11
    arXiv: 1402.5439
  81. Longterm influence of fluid inertia on the diffusion of a Brownian particle
    Giuseppe Pesce, Giorgio Volpe, Giovanni Volpe & Antonio Sasso
    Physical Review E 90(4), 042309 (2014)
    DOI: 10.1103/PhysRevE.90.042309
    arXiv: 1402.6913
  82. Speckle optical tweezers: Micromanipulation with random light fields
    Giorgio Volpe, Lisa Kurz, Agnese Callegari, Giovanni Volpe & Sylvain Gigan
    Optics Express 22(15), 18159—18167 (2014)
    DOI: 10.1364/OE.22.018159
    arXiv: 1403.0364
  83. Reply to comment on “Circular motion of asymmetric self-propelling particles”
    Felix Kümmel, Borge ten Hagen, Raphael Wittkowski, Daisuke Takagi, Ivo Buttinoni, Ralf Eichhorn, Giovanni Volpe, Hartmut Löwen & Clemens Bechinger
    Physical Review Letters 113(2), 029802 (2014)
    DOI: 10.1103/PhysRevLett.113.029802
    arXiv: 1407.4016
  84. Simulation of the active Brownian motion of a microswimmer
    Giorgio Volpe, Sylvain Gigan & Giovanni Volpe
    American Journal of Physics 82(7), 659—664 (2014)
    DOI: 10.1119/1.4870398
  85. Brownian motion in a speckle light field: Tunable anomalous diffusion and selective optical manipulation
    Giorgio Volpe, Giovanni Volpe & Sylvain Gigan
    Scientific Reports 4, 3936 (2014)
    DOI: 10.1038/srep03936
    arXiv: 1304.1433
  86. Stratonovich-to-Itô transition in noisy systems with multiplicative feedback
    Giuseppe Pesce, Austin McDaniel, Scott Hottovy, Jan Wehr & Giovanni Volpe
    Nature Communications 4, 2733 (2013)
    DOI: 10.1038/ncomms3733
    arXiv: 1206.6271
  87. Optical trapping and manipulation of nanostructures
    Onofrio M. Maragò, Philip H. Jones, Pietro Gucciardi, Giovanni Volpe & Andrea Ferrari
    Nature Nanotechnology 8(11), 807—819 (2013)
    DOI: 10.1038/nnano.2013.208
  88. Sorting of chiral microswimmers (Cover article)
    Mite Mijalkov & Giovanni Volpe
    Soft Matter 9(28), 6376—6381 (2013)
    DOI: 10.1039/C3SM27923E
    arXiv: 1212.6504
  89. Circular motion of asymmetric self-propelling particles
    Felix Kümmel, Borge ten Hagen, Raphael Wittkowski, Ivo Buttinoni, Giovanni Volpe, Hartmut Löwen & Clemens Bechinger
    Physical Review Letters 110(19), 198302 (2013)
    DOI: 10.1103/PhysRevLett.110.198302
    arXiv: 1302.5787

    Featured in “Synopsis: Round and Round in Circles”, Physics (May 9, 2013)
  90. Simulation of a Brownian particle in an optical trap
    Giorgio Volpe & Giovanni Volpe
    American Journal of Physics 81(2), 224—230 (2013)
    DOI: 10.1119/1.4772632
  91. Thermophoresis of Brownian particles driven by coloured noise
    Scott Hottovy, Giovanni Volpe & Jan Wehr
    EPL (Europhysics Letters) 99(6), 60002 (2012)
    DOI: 10.1209/0295-5075/99/60002
    arXiv: 1205.1093
  92. Active Brownian motion tunable by light
    Ivo Buttinoni, Giovanni Volpe, Felix Kümmel, Giorgio Volpe & Clemens Bechinger
    Journal of Physics: Condensed Matter 24(28), 284129 (2012)
    DOI: 10.1088/0953-8984/24/28/284129
    arXiv: 1110.2202
  93. Noise-induced drift in stochastic differential equations with arbitrary friction and diffusion in the Smoluchowski-Kramers limit
    Scott Hottovy, Giovanni Volpe & Jan Wehr
    Journal of Statistical Physics 146(2), 762—773 (2012)
    DOI: 10.1007/s10955-012-0418-9
    arXiv: 1112.2607
  94. Microswimmers in patterned environments
    Giovanni Volpe, Ivo Buttinoni, Dominik Vogt, Hans-Jürgen Kümmerer & Clemens Bechinger
    Soft Matter 7(19), 8810—8815 (2011)
    DOI: 10.1039/C1SM05960B
    arXiv: 1104.3203
  95. Reply to comment on “Influence of noise on force measurements”
    Giovanni Volpe, Laurent Helden, Thomas Brettschneider, Jan Wehr & Clemens Bechinger
    Physical Review Letters 107(7), 078902 (2011)
    DOI: 10.1103/PhysRevLett.107.078902
    arXiv: 1101.3916
  96. Force measurement in the presence of Brownian noise: Equilibrium distribution method vs. drift method
    Thomas Brettschneider, Giovanni Volpe, Laurent Helden, Jan Wehr & Clemens Bechinger
    Physical Review E 83(4), 041113 (2011)
    DOI: 10.1103/PhysRevE.83.041113
    arXiv: 1009.2386
  97. Influence of rotational force fields on the determination of the work done on a driven Brownian particle
    Giuseppe Pesce, Giovanni Volpe, Alberto Imparato, Giulia Rusciano & Antonio Sasso
    Journal of Optics 13(4), 044006 (2011)
    DOI: 10.1088/2040-8978/13/4/044006
    arXiv: 1006.4534
  98. Fractal plasmonics: Subdiffraction focusing and broadband spectral response by a Sierpisky nanocarpet
    Giorgio Volpe, Giovanni Volpe & Romain Quidant
    Optics Express 19(4), 3612—3618 (2011)
    DOI: 10.1364/OE.19.003612
  99. Influence of noise on force measurements
    Giovanni Volpe, Laurent Helden, Thomas Brettschneider, Jan Wehr & Clemens Bechinger
    Physical Review Letters 104(17), 170602 (2010)
    DOI: 10.1103/PhysRevLett.104.170602
    arXiv:  1004.0874
  100. Novel perspectives for the application of total internal reflection microscopy
    Giovanni Volpe, Thomas Brettschneider, Laurent Helden & Clemens Bechinger
    Optics Express 17(26), 23975—23985 (2009)
    DOI: 10.1364/OE.17.023975
    arXiv: 0909.5131
  101. Quantitative assessment of non-conservative radiation forces in an optical trap
    Giuseppe Pesce, Giorgio Volpe, Anna Chiara De Luca, Giulia Rusciano & Giovanni Volpe
    EPL (Europhysics Letters) 86(3), 38002 (2009)
    DOI: 10.1209/0295-5075/86/38002
    arXiv: 0902.4178
  102. Thermal noise suppression: How much does it cost?
    Giovanni Volpe, Jan Wehr, Dmitri Petrov & J. Miguel Rubi
    Journal of Physics A: Mathematical and Theoretical 42(9), 095005 (2009)
    DOI: 10.1088/1751-8113/42/9/095005
    arXiv: 0711.0923
  103. Mie scattering distinguishes the topological charge of an optical vortex: A homage to Gustav Mie
    Valeria Garbin, Giovanni Volpe, Enrico Ferrari, Michel Versluis, Dan Cojoc & Dmitri Petrov
    New Journal of Physics 11, 013046 (2009)
    DOI: 10.1088/1367-2630/11/1/013046
  104. 10-fold detection range increase in quadrant-photodiode position sensing for photonic force microscope
    Sandro Perrone, Giovanni Volpe & Dmitri Petrov
    Review of Scientific Instruments 79(10), 106101 (2008)
    DOI: 10.1063/1.2993177
  105. Stochastic resonant damping in a noisy monostable system: Theory and experiment
    Giovanni Volpe, Sandro Perrone, J. Miguel Rubi & Dmitri Petrov
    Physical Review E 77(5), 051107 (2008)
    DOI: 10.1103/PhysRevE.77.051107
  106. Surface plasmon optical tweezers: Tunable optical manipulation in the femtonewton range
    Maurizio Righini, Giovanni Volpe, Christian Girard, Dmitri Petrov & Romain Quidant
    Physical Review Letters 100(18), 186804 (2008)
    DOI: 10.1103/PhysRevLett.100.186804
  107. Singular point characterization in microscopic flows
    Giorgio Volpe, Giovanni Volpe & Dmitri Petrov
    Physical Review E 77(3), 037301 (2008)
    DOI: 10.1103/PhysRevE.77.037301
    arXiv: 0711.0923
  108. Brownian motion in a non-homogeneous force field and photonic force microscope
    Giorgio Volpe, Giovanni Volpe & Dmitri Petrov
    Physical Review E 76(6), 061118 (2007)
    DOI: 10.1103/PhysRevE.76.061118
    arXiv: 0711.0923
  109. Back-scattering position detection for photonic force microscopy
    Giovanni Volpe, Gregory Kozyreff & Dmitri Petrov
    Journal of Applied Physics 102(8), 084701 (2007)
    DOI: 10.1063/1.2799047
  110. Real-time actin-cytoskeleton depolymerization detection in a single cell using optical tweezers
    Anna Chiara de Luca, Giovanni Volpe, Anna Morales Drets, Maria Isabel Geli, Giuseppe Pesce, Giulia Rusciano, Antonio Sasso & Dmitri Petrov
    Optics Express 15(13), 7922—7932 (2007)
    DOI: 10.1364/OE.15.007922
  111. Torque detection using Brownian fluctuations
    Giovanni Volpe & Dmitri Petrov
    Physical Review Letters 97(21), 210603 (2006)
    DOI: 10.1103/PhysRevLett.97.210603

    Featured in “Focus: Hidden Twists and Turns
    Physical Review Focus 18, 17 (December 1, 2006)
  112. The lag phase and G1 phase of a single yeast cell monitored by Raman microspectroscopy
    Gajendra P. Singh, Giovanni Volpe, Caitriona M. Creely, Helga Grötsch, Isabel M. Geli & Dmitri Petrov
    Journal of Raman Spectroscopy 37(8), 858—864 (2006)
    DOI: 10.1002/jrs.1520
  113. Surface plasmon radiation forces
    Giovanni Volpe, Romain Quidant, Gonçal Badenes & Dmitri Petrov
    Physical Review Letters 96(23), 238101 (2006)
    DOI: 10.1103/PhysRevLett.96.238101
  114. Dynamics of a growing cell in an optical trap
    Giovanni Volpe, Gajendra Pratap Singh & Dmitri Petrov
    Applied Physics Letters 88(23), 231106 (2006)
    DOI: 10.1063/1.2213015
  115. Raman imaging of floating cells
    Caitriona M. Creely, Giovanni Volpe, Gajendra P. Singh, Marta Soler & Dmitri Petrov
    Optics Express 13(16), 6105—6110 (2005)
    DOI: 10.1364/OPEX.13.006105
  116. Real-time detection of hyperosmotic stress response in optically trapped single yeast cells using Raman microspectroscopy
    Gajendra P. Singh, Caitriona M. Creely, Giovanni Volpe, Helga Grötsch & Dmitri Petrov
    Analytical Chemistry 77(8), 2564—2568 (2005)
    DOI: 10.1021/ac048359j
  117. Generation of cylindrical vector beams with few-mode fibers excited by Laguerre-Gaussian beams
    Giovanni Volpe & Dmitri Petrov
    Optics Communications 237(1), 89—95 (2004)
    DOI: 10.1016/j.optcom.2004.03.080