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Core Faculty

The Ellis Unit Genoa Team

Massimiliano Pontil

Unit Director, ELLIS Fellow
Bio

Lorenzo Rosasco

Unit co-Director, ELLIS Fellow, 
ELLIS Research Programme Director
Unit Directors

Paolo Frasconi

Fellow

Vittorio Murino

Fellow

Lorenzo Natale

Fellow
Unit Fellows

Arash Ajoudani

Scholar

Luca Oneto

Scholar

Alessandra Sciutti

Scholar
Unit Scholars

Chiara Bartolozzi

Unit Member

Sergio Decherchi

Unit Member

Alessio Del Bue

Unit Member

Ernesto De Vito

Unit Member

Tommaso Fellin

Unit Member

Luca Romeo

Unit Member

Daniele Pucci

Unit Member

Saverio Salzo

Unit Member

Claudio Semini

Unit Member

Alessandro Verri

Unit Member

Silvia Villa

Unit Member

Agnieszka Wykowska

Unit Member

Matteo Santacesaria

Unit Member

Luca Calatroni

Unit Member

Francesca Odone

Unit Member

Agnese Seminara

Unit Member

Nicoletta Noceti

Unit Member

Fabio Roli

Unit Member

Giovanni Alberti

Unit Member
Unit Members

Paolo Frasconi

Fellow

Paolo Frasconi is Professor of Computer Engineering at the University of Florence. He previously held academic positions at KU Leuven, University of Cagliari, University of Wollongong, and Massachusetts Institute of Technology. His research interests are in the area of machine learning (e.g., neural networks, graphical models, kernel machines, and relational learning) bioinformatics (e.g., protein structure and function, small molecules), neuroinformatics and medicine. He has also contributed applications to natural language processing, text, music, and pattern recognition. These activities are collected in over 150 refereed papers collecting over 19000 citations and an h-index of 47 (Google Scholar, 2021). He is an Action Editor for Machine Learning journal since 2010 and has been Associate Editor for Artificial Intelligence Journal, IEEE Transactions on Knowledge and Data Engineering, IEEE Transactions on Neural Networks. Among other services, he has been Associate Program Chair for IJCAI 2022, Program Chair for ECML PKDD 2016, Program Chair for ILP 2010, Vice-Chair for ICDM 2003.

Arash Ajoudani

Scholar

Arash Ajoudani is a tenured senior scientist at the Italian Institute of Technology (IIT), where he leads the Human-Robot Interfaces and physical Interaction (HRI²) laboratory. He also coordinates the AI for Manufacturing (AI4M) lab of the Leonardo labs, and is a principal investigator of the IIT-Intellimech JOiiNT lab. He received his PhD degree in Robotics and Automation from University of Pisa and IIT in 2014. 

He is a recipient of the European Research Council (ERC) starting grant 2019 (Ergo-Lean), the coordinator of the Horizon-2020 project SOPHIA, and the co-coordinator of the Horizon-2020 project CONCERT.  He is a recipient of the IEEE Robotics and Automation Society (RAS) Early Career Award 2021, and winner of the Amazon Research Awards 2019, of the Solution Award 2019 (MECSPE2019), of the KUKA Innovation Award 2018, of the WeRob best poster award 2018, and of the best student paper award at ROBIO 2013. His PhD thesis was a finalist for the Georges Giralt PhD award 2015 - best European PhD thesis in robotics. He was also a finalist for the Solution Award 2020 (MECSPE2020), the best conference paper award at Humanoids 2018, for the best interactive paper award at Humanoids 2016, for the best oral presentation award at Automatica (SIDRA) 2014, and for the best manipulation paper award at ICRA 2012. 

He is the author of the book "Transferring Human Impedance Regulation Skills to Robots" in the Springer Tracts in Advanced Robotics (STAR), and several publications in journals, international conferences, and book chapters. He is currently serving as the executive manager of the IEEE-RAS Young Reviewers' Program (YRP), and as chair and representative of the IEEE-RAS Young Professionals Committee. He has been serving as a member of scientific advisory committee and as an associate editor for several international journals and conferences such as IEEE RAL, ICRA, IROS, ICORR, etc. He is a scholar of the European Lab for Learning and Intelligent Systems (ELLIS). His main research interests are in physical human-robot interaction, mobile manipulation, robust and adaptive control, assistive robotics, and tele-robotics.

Chiara Bartolozzi

Unit Member

Chiara Bartolozzi is a Researcher at the Italian Institute of Technology. She earned a degree in Engineering at the University of Genova (Italy) and a PhD in Neuroinformatics at ETH Zurich, developing analogue subthreshold circuits for emulating biophysical neuronal properties onto silicon and modelling selective attention on hierarchical multi-chip systems.

She is currently leading the Event-Driven Perception for Robotics group, with the aim of applying the "neuromorphic" engineering approach to the design of robotic platforms as enabling technology towards the design of autonomous machines.

This goal is pursued by inducing a paradigm shift in robotics, based on the emerging concept of Event-Driven (ED) sensing and processing. Similarly to their biological counterpart, and differently from traditional robotic sensors, ED sensory systems sample their input signal at fixed (and relative) amplitude changes, intrinsically adapting to the dynamics of the sensory signal: temporal resolution is extremely high for fast transitory signals and decreases for slower inputs.

This approach naturally leads to better robots that acquire, transmit and process information only when needed, optimising the use of resources, leading to real-time, low-cost, operation.

Chiara has participated in a number of EU funded projects, she is currently coordinating the European Training Network "NeuTouch", where 15 PhD students are studying how touch perception works in humans and animals, in order to develop artificial touch perception systems for robots and hand prostheses. As the leader of the educational activities of the coordination and support action NEUROTECH, she is co-organising the Neuromorphic Colloquium, a series of online events to build up educational material for the next generation of neuromorphic researchers.

She is an IEEE member, actively supporting the CAS and RAS societies. In 2020, she has co-chaired "AICAS2020", on Circuits and systems for efficient embedded AI.

Vittorio Murino

Fellow

Vittorio Murino is a full professor at the University of Verona, Italy, and visiting scientist of PAVIS (Pattern Analysis and Computer Vision) department at the Istituto Italiano di Tecnologia, in Genova, Italy. From 2009 to 2019, he worked at the Istituto Italiano di Tecnologia in Genova, Italy, as director of the PAVIS (Pattern Analysis and Computer Vision) department. From 2019 to 2021, he joined the Ireland Research Centre of Huawei Technologies (Ireland) Co., Ltd. in Dublin, as Senior Video Intelligence Expert. 
His main research interests include computer vision, pattern recognition and machine learning, nowadays focusing on deep learning approaches, domain adaptation and generalization, and multimodal learning for (human) behaviour analysis and related applications, such as video surveillance and biomedical imaging. Prof. Murino is co-author of more than 400 papers published in refereed journals and international conferences. Finally, prof. Murino is IEEE Fellow, IAPR Fellow, and ELLIS Fellow.

Alessandra Sciutti

Scholar

Alessandra Sciutti is Tenure Track Researcher, head of the CONTACT (COgNiTive Architecture for Collaborative Technologies) unit of the Italian Institute of Technology (IIT). With a background in Bioengineering, she received her PhD in Humanoid Technologies from the University of Genova in 2010. After two research periods in USA and Japan, in 2018 she has been awarded the ERC Starting Grant wHiSPER (www.whisperproject.eu), focused on the investigation of joint perception between humans and robots. She published more than 70 papers in international journals and conferences and participated in the coordination of the CODEFROR European IRSES project. She is currently Associate Editor for several journals, among which the International Journal of Social Robotics, the IEEE Transactions on Cognitive and Developmental Systems and Cognitive System Research. The scientific aim of her research is to investigate the sensory and motor mechanisms underlying mutual understanding in human-human and human-robot interaction.

Lorenzo Rosasco

Unit co-Director, ELLIS Fellow, 
ELLIS Research Programme Director

Lorenzo Rosasco is full professor at the DIBRIS Department at the University of Genoa, a visiting professor at the Massachusetts Institute of Technology, and external collaborator at the Istituto Italiano di Tecnologia. He received his PhD from the University of Genoa in 2006 and has been visiting student at the Toyota Technological Institute at Chicago and at the Center for Biological and Computational Learning at MIT. He held a research scientist position at MIT between 2006 and 2009. He is the principal investigator of the Laboratory for Computational and Statistical Learning and a coordinator of the Machine Learning center of the University of Genova (MaLGa). In 2019 he obtained the ERC consolidator grant “Efficient algorithms for sustainable machine learning”. His research focuses on studying theory and algorithms for machine learning. He is known for his foundational work in machine learning as well as the development of sound large scale machine learning algorithms. He authored more than 100 peer-reviewed papers in international journals.

Alessio Del Bue

Unit Member
Alessio Del Bue is a tenured senior researcher leading the PAVIS (Pattern Analyisis and computer VISion) research line of the Italian Institute of Technology (IIT) in Genova, Italy. Previously, he was a researcher in the Institute for Systems and Robotics at the Instituto Superior Técnico (IST) in Lisbon, Portugal. Before that, he obtained his Ph.D. under the supervision of Dr. Lourdes Agapito in the Department of Computer Science at Queen Mary University of London. His current research interests are related to 3D scene understanding from multi-modal input (images, depth, audio) to support the development of assistive Artificial Intelligence systems. He is co-author of more than 100 scientific publications, in refereed journals and international conferences, member of the technical committees of important computer vision conferences (CVPR, ICCV, ECCV, BMVC, etc.), and he serves as an associate editor of Patter Recognition and Computer Vision and Image Understanding journals. Finally, Dr. Del Bue is an IEEE and ELLIS member.

Lorenzo Natale

Unit Member
Lorenzo Natale is Tenured Senior Researcher at the Italian Institute of Technology. He received his degree in Electronic Engineering (with honours) in 2000 and Ph.D. in Robotics in 2004 from the University of Genoa. He was later postdoctoral researcher at the MIT Computer Science and Artificial Intelligence Laboratory. He was invited professor at the University of Genova where he taught the courses of Natural and Artificial Systems and Antropomorphic Robotics for students of the Bioengineering curriculum. Since 2020 he is visiting Professor at the University of Manchester. Lorenzo Natale has contributed to the development of various humanoid platforms. He was one of the main contributors to the design and development of the iCub platform and he has been leading the development of the iCub software architecture and the YARP middleware. His research interests range from vision and tactile sensing to software architectures for robotics. He is author of more than 130 papers in international journals and conferences. He was principal investigator and co-principal investigator in several EU funded projects. He was general chair of IEEE ARSO 2018 and served as Program Chair of ICDL-Epirob 2014 and HAI 2017. He has been in the program committee of international conferences including ICRA, Humanoids, RSS and RO-MAN. He is associate editor for IEEE-Transactions on Robotics, IEEE Robotics and Automation Letters, the International Journal of Humanoid Robotics and Humanoid Robotics specialty of frontiers in Robotics and AI.

Luca Oneto

Unit Member
Luca Oneto was born in Rapallo, Italy in 1986. He received his BSc and MSc in Electronic Engineering at the University of Genoa, Italy respectively in 2008 and 2010. In 2014 he received his PhD from the same university in the School of Sciences and Technologies for Knowledge and Information Retrieval with the thesis "Learning Based On Empirical Data". In 2017 he obtained the Italian National Scientific Qualification for the role of Associate Professor in Computer Engineering and in 2018 he obtained the one in Computer Science. He worked as Assistant Professor in Computer Engineering at University of Genoa from 2016 to 2019. In 2018 he was co-funder of the spin-off ZenaByte s.r.l. In 2019 he obtained the Italian National Scientific Qualification for the role of Full Professor in Computer Science and Computer Engineering. In 2019 he became Associate Professor in Computer Science at University of Pisa and currently is Associate Professor in Computer Engineering at University of Genoa. He has been involved in several H2020 projects (S2RJU, ICT, DS) and he has been awarded with the Amazon AWS Machine Learning and Somalvico (best Italian young AI researcher) Awards. His first main topic of research is the Statistical Learning Theory with particular focus on the theoretical aspects of the problems of (Semi) Supervised Model Selection and Error Estimation. His second main topic of research is Data Science with particular reference to the problem of Trustworthy AI and the solution of real world problems by exploiting and improving the most recent Learning Algorithms and Theoretical Results in the fields of Machine Learning and Data Mining.

Luca Romeo

Unit Member
LUCA ROMEO is Associate Professor of Computer Science at the University of Macerata (UniMC), Department of Economics and Law. Additionally, he is affiliated with the Unit of Computational Statistics and Machine Learning at Fondazione Istituto Italiano di Tecnologia (IIT) in Genova, Italy. Dr. Romeo’s research centers on designing novel machine learning algorithms to address complex challenges in real-world domains. He has authored over 50 publications in leading conferences and journals. He serves as an Associate Editor for the Neurocomputing (Elsevier) journal and Medical & Biological Engineering & Computing (MBEC). Dr. Romeo is actively involved in the global AI research community, serving as a Senior Program Committee (PC) member for the International Joint Conference on Artificial Intelligence and as a member of the Ellis Society, a pan-European network of AI excellence.

Daniele Pucci

Unit Member

Daniele received the bachelor and master degrees in Control Engineering with highest honors from ”Sapienza”, University of Rome, in 2007 and 2009, respectively. In 2013, he earned the PhD title with a thesis prepared at INRIA Sophia Antipolis, France, with the supervision of Tarek Hamel, Salvatore Monaco, and Claude Samson. From 2013 to 2017, he has been a postdoc at the Istituto Italiano di Tecnologia (IIT) working within the EU project CoDyCo focusing on the balancing problem of the iCub humanoid robot. From August 2017 to August 2021, he has been the head of the Dynamic Interaction Control lab, a group of about 20 members focusing on the iCub locomotion walking problem. In this period, Daniele also laid the basis for the "Aerial Humanoid Robotics", a new branch of Robotics whose main aim is to achieve flying humanoid robots. Daniele has also been the scientific PI of the H2020 European Project AnDy, and now is: task leader of the H2020 European Project SoftManBot, coordinator of the joint laboratory between IIT and Honda JP, principal investigator (PI) in the Camozzi-IIT and Danieli Automation-IIT joint labs. Lastly, Daniele is the coordinator of the ergoCub project, a 5 million, three year joint project between INAIL and IIT.  Since September 2021, Daniele is the PI leading the  Artificial and Mechanical Intelligence  research line at IIT, a team composed of about forty members that combines AI and Mechanics to devise the next generation of the iCub humanoid robot. 

Claudio Semini

Unit Member

Claudio Semini (MSc 2005, PhD 2010) is the head of the Dynamic Legged Systems (DLS) lab at Istituto Italiano di Tecnologia (IIT) that developed a number of high-performance hydraulic robots, including HyQ, HyQ2Max, and HyQReal. He holds an MSc degree from ETH Zurich in electrical engineering and information technology. He spent 2 years in Tokyo for his research: MSc thesis at the Hirose Lab at Tokyo Tech and staff engineer at the Toshiba R&D centre in Kawasaki working on mobile service robotics. During his PhD and subsequent PostDoc at IIT, he developed the quadruped robot HyQ and worked on its control. Since 2012 he leads the DLS lab. Claudio Semini is the author and co-author of more than 100 peer-reviewed publications in international journals and conferences and he received several awards for them. He is also a co-founder of the Technical Committee on Mechanisms and Design of the IEEE-RAS Society. He is/was the coordinator/partner of several EU-, National and Industrial projects (including HyQ-REAL, INAIL Teleop, Moog@IIT joint lab, ESA-ANT, etc). His research interests include the construction and control of highly dynamic and versatile legged robots for field application in real-world operations, locomotion, hydraulic drives, and others.

Sergio Decherchi

Unit Member

Sergio Decherchi obtained the Laurea degree summa cum laude in Electronic Engineering in 2007 from Genoa University, Italy, Europe. In 2011 he obtained a PhD in Electronic Engineering and Computer Science on Machine Learning and Data Mining from the same University while working at the Department of Biophysics and Electronic Engineering. From 2011 to 2016, he was Post Doctoral researcher at the Istituto Italiano di Tecnologia (IIT), Genoa, Italy, Europe, Department of Drug Discovery and Development (D3) where he designed, developed and applied computational intelligence/chemistry methods to drug discovery.  In 2014 Sergio co-founded BiKi Technologies s.r.l. a company dealing with Molecular Dynamics and machine learning methods for drug discovery. From 2017 to 2022 Sergio is a technologist in IIT. In 2022 he obtained the national habilitation as Associate Professor in computer science, and from 2023 he is the coordinator of the Data Science and Computation IIT facility. He is the author of more than 70 papers in peer-reviewed Journals and conferences in the fields of computational intelligence and computational chemistry. Sergio has received some awards, EU/national/private grants, delivered several invited talks/lectures and co-organized some workshops (e.g. ECAM/CECAM). He is a reviewer for EU and national funding agencies. He serves as Associate Editor for the Springer Journal, Cognitive Computation.

Saverio Salzo

Unit Member

Saverio Salzo is a tenured assistant professor at the Department of Computer, Control and Management Engineering of Sapienza University Rome and an external collaborator of the Italian Institute of Technology (IIT) in Genoa, Italy, within the research line of Computational Statistics and Machine Learning. Since 2020 he is also honorary lecturer at University College London (UCL). Previously, he was member of the Laboratory for Computational and Statistical Learning in IIT. He received his degree in pure Mathematics (with honours) from the University of Bari in 2001 and a PhD in Computer Science from the University of Genova in 2012. His research interests are broadly directed to devise and analyze efficient algorithms for optimization in large scale scenarios and novel statistical methods for data inference and analysis. In particular, he worked on nonsmooth optimization methods, stochastic algorithms, hyperparameter optimization via bilevel optimization, optimization methods for optimal transport, and support vector machines and kernel methods in Banach spaces. He co-authored 28 peer-reviewed papers in international conferences and journals.

Alessandro Verri

Unit Member
Alessandro Verri is full professor at the DIBRIS Department at the University of Genoa. He received his PhD from the University of Genoa in 1988. He has been a visiting professor at MIT for several years, then at the Heriot-Watt University (Edinburgh), at the INRIA - IRISA in Rennes and at Berkeley. He is a coordinator of the Machine Learning center of the University of Genova (MaLGa). He supervised more than 30 PhD students, and around 100 master students. His research interests are analytic methods for learning theory, learning algorithms for biomedical data analysis and image understanding, computational methods for the processing of visual information in 2D and 3D. He authored more than 130 peer-reviewed papers in international journals.

Silvia Villa

Unit Member
Silvia Villa is associate professor at the Department of Mathematics at the University of Genoa. She received her PhD in Mathematics from the University of Florence. She was previously a post-doctoral researcher at the Laboratory for Computational and Statistical learning and an assistant professor at the Department of Mathematics at Politecnico di Milano. She is a coordinator of the Machine Learning center of the University of Genova (MaLGa). She is in the international scientic committee of GdR Mathematiques de l’Optimisation et Applications ́and in the editorial board of Applied Mathematics and Computation and Journal of Non-smooth Analysis and Optimization. Her research interests are in convex optimization for inverse problems and machine learning. She authored 38 peer-reviewed papers in international conferences and journals.

Luca Calatroni

Unit Member
Luca Calatroni is Associate Professor in the Department of Informatics, Bioengineering, Robotics and Systems Engineering (DIBRIS) at the University of Genoa (Italy), Principal Investigator of the Computational Imaging & Learning (CIL) unit at the Machine Learning Genoa Center (MaLGa), and an affiliated member of the Molecular Microscopy and Spectroscopy (MMS) team at the Italian Institute of Technology. He obtained his PhD in Applied Mathematics from the University of Cambridge (UK), and held postdoctoral positions at the University of Genoa as a Marie Skłodowska-Curie Fellow, at École Polytechnique (France) as a Lecteur Hadamard Fellow, and as a Research Scientist at CNRS–I3S in Sophia Antipolis (France). He has supervised or is currently supervising 6 postdoctoral researchers, 7 PhD students, and more than 10 Master’s students. His research focuses on variational and optimisation methods for imaging inverse problems, non-smooth and non-convex optimisation, and physics-inspired learning frameworks, with applications to computational microscopy. He has been awarded research grants, among which, at a national level, the ANR JCJC project TASKABILE, the ANR PRC project MICROBLIND (co-PI), and, at international level, the H2020 RISE project NoMADS (unit leader) and an ERC Starting Grant. He is Associate Editor of the Journal of Mathematical Imaging and Vision and Inverse Problems (since 2023), SIAM journal of Imaging Science (since 2026) and has served as Guest Editor for several journals, including the Cambridge Elements series (Cambridge University Press) and the Journal of Mathematical Neuroscience. Between 2020 and 2023, he was Director of the Italian group “Mathematics for Imaging, Vision and Applications” of the Italian Mathematical Union (UMI) during which he fostered collaborations and promoted the organisation of scientific events focusing on the use of advanced AI techniques for imaging and vision. Since 2024 he has been an elected member of the IEEE BISP Committee and since 2026 he is elected member of the Technical Activity Committee on Theoretical and Methodological Trends in Signal Processing of the EURASIP association.

Giovanni Alberti

Unit Member
Giovanni S. Alberti is professor in mathematical analysis at the Department of Mathematics of the University of Genoa and PI at the Machine Learning Genoa Centre (MaLGa). He received his PhD at the University of Oxford, and held two post-doctoral positions at the École Normale Supérieure in Paris and at ETH Zürich. His research focuses on partial differential equations, applied harmonic analysis, inverse problems and machine learning. He was the recipient of the Gioacchino Iapichino prize for Mathematical Analysis in 2017, of the Eurasian Association on Inverse Problems Young Scientist Award for distinguished contributions to inverse problems in 2018, of a ERC Starting Grant in 2021, and of the Calderón prize 2025. He is associate editor of the journals Inverse Problems, SIAM Journal on Imaging Sciences, Mathematical Foundations of Machine Learning, Numerical Functional Analysis and Optimization, and Communications on Analysis and Computation.

Fabio Roli

Unit Member
Fabio Roli is Full Professor of Computer Engineering at the Universities of Genova and Cagliari, Italy. He is Director of the sAIfer Lab, a joint lab between the Universities of Genova and Cagliari on Safety and Security of AI. Fabio Roli’s research over the past thirty years has addressed the design of machine learning systems in the context of real security applications. He has provided seminal contributions to the fields of ensemble learning and adversarial machine learning and he has played a leading role in the establishment and advancement of these research themes. He is a recipient of the Pierre Devijver Award for his contributions to statistical pattern recognition. He has been appointed Fellow of the IEEE, Fellow of the International Association for Pattern Recognition, Fellow of the Asia-Pacific Artificial Intelligence Association. Solo 400 characters Fabio Roli is Full Professor of Computer Engineering at the Universities of Genova and Cagliari, Italy. He is Director of the sAIfer Lab. He is a recipient of the Pierre Devijver Award for his contributions to statistical pattern recognition. He has been appointed Fellow of the IEEE, Fellow of the International Association for Pattern Recognition, Fellow of the Asia-Pacific Artificial Intelligence Association.

Luca Calatroni

Unit Member
Luca Calatroni is Associate Professor in the Department of Informatics, Bioengineering, Robotics and Systems Engineering (DIBRIS) at the University of Genoa (Italy), Principal Investigator of the Computational Imaging & Learning (CIL) unit at the Machine Learning Genoa Center (MaLGa), and an affiliated member of the Molecular Microscopy and Spectroscopy (MMS) team at the Italian Institute of Technology. He obtained his PhD in Applied Mathematics from the University of Cambridge (UK), and held postdoctoral positions at the University of Genoa as a Marie Skłodowska-Curie Fellow, at École Polytechnique (France) as a Lecteur Hadamard Fellow, and as a Research Scientist at CNRS–I3S in Sophia Antipolis (France). He has supervised or is currently supervising 6 postdoctoral researchers, 7 PhD students, and more than 10 Master’s students. His research focuses on variational and optimisation methods for imaging inverse problems, non-smooth and non-convex optimisation, and physics-inspired learning frameworks, with applications to computational microscopy. He has been awarded research grants, among which, at a national level, the ANR JCJC project TASKABILE, the ANR PRC project MICROBLIND (co-PI), and, at international level, the H2020 RISE project NoMADS (unit leader) and an ERC Starting Grant. He is Associate Editor of the Journal of Mathematical Imaging and Vision and Inverse Problems (since 2023), SIAM journal of Imaging Science (since 2026) and has served as Guest Editor for several journals, including the Cambridge Elements series (Cambridge University Press) and the Journal of Mathematical Neuroscience. Between 2020 and 2023, he was Director of the Italian group “Mathematics for Imaging, Vision and Applications” of the Italian Mathematical Union (UMI) during which he fostered collaborations and promoted the organisation of scientific events focusing on the use of advanced AI techniques for imaging and vision. Since 2024 he has been an elected member of the IEEE BISP Committee and since 2026 he is elected member of the Technical Activity Committee on Theoretical and Methodological Trends in Signal Processing of the EURASIP association.

Agnese Seminara

Unit Member
Agnese Seminara is a modeler she uses physics and machine learning to understand behavior in organisms from bacteria and fungi to mammals, salamanders, fish and other marine creatures. She is particularly interested in sensory systems and how they support various behaviors from navigation, to prey capture, target localization and locomotion. She leverages her background in the statistical physics of fluids to characterize the random environment living systems evolved in and elucidate adaptations to read the distorted information brought by fluids. Her group develops reinforcement learning algorithms that are trained in virtual environments representing the realistic physics of fluids animals live in. Predictions regarding the computational basis of behavior can be tested against experiments with live animals navigating in the Laboratory (conducted in close collaboration with wet labs at Harvard). Agnese has a B.Sc and M.Sc in physics from the University of Genoa, Italy (2004), a PhD in physics from University of Nice, France (2007). She was a Postdoctoral fellow at Harvard University (2008-2010) and Institut Pasteur, France (2010-11), a lecturer of Applied Mathematics at Harvard (2012), a PI at CNRS (researcher 2013-2018 and research director 2019-21). She moved back to University of Genoa in 2021 as a full professor of fluid dynamics. Awards and Grants: ERC Consolidator Grant 2019; NIH RO1 2019; CNRS Research and supervision award 2018; CNRS Bronze Medal 2017; Rita Levi Montalcini young investigator (declined) 2012; Marie Curie Outgoing fellowship 2008; L’Oreal-Unesco for Women in Science 2006.

Nicoletta Noceti

Unit Member
Nicoletta Noceti is Associate Professor of Computer Science at the University of Genova and a founding member of the MaLGa – Machine Learning Genoa Center, where she co-leads the Machine Learning and Vision Unit with Prof. Francesca Odone. She received her PhD in Computer Science from the University of Genova in 2010. Her research focuses on the design and development of advanced methods that integrate Computer Vision and Machine Learning for image and video understanding, with a particular emphasis on the complex problem of human motion representation learning. Over the years, she has investigated both the theoretical foundations of Computer Vision and Image Processing and their application to real-world scenarios, including human–machine interaction, natural interfaces, robotics, video surveillance, Ambient Assisted Living, and biomedical imaging. In these domains, she has developed expertise in the analysis of heterogeneous and high-dimensional data and has established strong collaborations with national and international universities and research institutes. She has authored more than 100 scientific publications and has coordinated or contributed to numerous national and international research projects, as well as technology transfer initiatives and development projects in collaboration with SMEs and large companies.

Francesca Odone

Unit Member
Francesca Odone is a Full Professor of Computer Science at the University of Genova and a founding member of MaLGa (Machine Learning Genoa Center), where she leads the Machine Learning and Vision Unit together with Prof. Nicoletta Noceti. She received her PhD from the University of Genova in 2002 and was a visiting student at Heriot-Watt University (Edinburgh) under a Marie Curie Scholarship. Since 2005, she has supervised 17 PhD students, 16 postdoctoral researchers, and around 50 Master’s students. She is currently supervising 7 PhD students (in Computer Science and Robotics) and 2 research grant holders. She has authored over 100 papers in international conferences and journals. Her research interests lie in computer vision and machine learning, with a particular focus on human-centric computer vision and learning interpretable representations from visual data. She designs methodologies that operate under constraints on computational resources and data availability, and her research is often connected to applied tasks in robotics, ambient-assisted living, rehabilitation, and video surveillance. She has been involved in numerous research projects and has served as scientific coordinator for technology transfer contracts with SMEs, large companies, and hospitals.

Matteo Santacesaria

Unit Member
Matteo Santacesaria is an Associate Professor of Mathematical Analysis at University of Genoa and faculty member of MaLGa center. He received his PhD at Ecole Polytechnique, and held post-doctoral positions at University of Grenoble, University of Helsinki and Politecnico di Milano. His research focuses on applied mathematics, with a special emphasis on machine learning for inverse problems in medical imaging and electrochemistry.

Ernesto De Vito

Unit Member
Ernesto De Vito is full professor at the Department of Mathematics at the University of Genoa. He received his PhD from the University of Genoa in 1995. He has been assistant professor at the Department of Mathematics at the University of Modena, and then associate professor at the Department of Mathematics of the University of Genoa. He is a coordinator of the Machine Learning center of the University of Genova (MaLGa). His research activity focuses on machine learning theory and applied harmonic analysis. He co-authored 60 papers in international reviewed journals and more than 10 in proceedings of international conferences. He wrote two books and supervised more than 35 master students and8 Ph.D. students. Since 2008 he is a member of the panel of the PhD Program in Mathematics and Applications, University of Genoa. He is the coordinator of the focus group "Mathematics of artificial intelligence" of the Italian mathematics union.

Agnieszka Wykowska

Unit Member

Agnieszka Wykowska is PI of the Social Cognition in Human-Robot Interaction (S4HRI) research line at the Italian Institute of Technology, Genova. She is also affiliated with the Luleå University of Technology, Sweden as adjunct professor in Engineering Psychology and with University of Manchester as Visiting Professor. She obtained PhD in Psychology from the Ludwig-Maximilians-University in Munich (LMU) in 2008. Her background is cognitive neuroscience (M.Sc. in neuro-cognitive psychology, LMU, 2006) and philosophy (M.A. in philosophy, Jagiellonian University Krakow, Poland, 2001). In 2016 she has been awarded an ERC Starting Grant “Intentional Stance for Social Attunement”: InStance Her research focuses on social cognitive neuroscience and human-robot interaction. She uses behavioral measures (eyetracking, psychophysics) and EEG in HRI research. She is Editor-in-Chief of International Journal of Social Robotics and an Associate Editor of Frontiers in Psychology (section Cognition). She is Core Member of the Ellis Society (European Laboratory for Learning and Intelligent Systems) and a Board Member of the Association of ERC Grantees (AERG). She has served as guest (co-)editor of a special issue of the Philosophical Transactions of the Royal Society B titled “From social brains to social robots: Applying neurocognitive insights to human-robot interaction (2018/2019), and she repeatedly serves as Program Committee member for various conferences, such as “International Conference on Social Robotics”, or “Human-Robot Interaction”.

Tommaso Fellin

Unit Member

Tommaso Fellin graduated in Physics at the University of Padova and is currently senior principal investigator at the Italian Institute of Technologies (IIT) in Genova, Italy. Dr. Fellin is head of the Optical Approaches to Brain Function Laboratory, co-head (together with Dr. S. Panzeri) of the Neural Coding Laboratory, and currently serves as Associate Director for the Technologies for Life Sciences Research Domain at the IIT. Dr. Fellin is also recipient of the European Research Council (ERC) consolidator grant NEURO-PATTERNS and co-founder of the start-up SmartMicroOptics. His research activity focuses on the study of the brain microcircuits involved in the processing of sensory information and on the development of innovative optical methods to probe their function. His laboratory has recently applied machine learning approaches to perform fast image analysis to extract neuronal signals from large cellular populations.