Letizia Bergamasco is a Ph.D. candidate in Computer and Control Engineering at Politecnico di Torino, currently in her 38th cycle (2022-2025). She is affiliated with the SMILIES research group (reSilient coMputer archItectures and LIfE Sciences) within the Department of Control and Computer Engineering (DAUIN), and collaborates with the LINKS Foundation. Bergamasco received her B.Sc. in Electronics Engineering (2018) and M.Sc. in ICT for Smart Societies (2020) with a Double Degree from Politecnico di Torino and Politecnico di Milano through the Alta Scuola Politecnica program. LINKS Foundation researcher since 2020 Focus on medical/industrial AI solutions Her research combines computer vision and AI for clinical applications, particularly in early dementia detection through facial expression analysis and pediatric pain assessment using camera-based vital parameter evaluation. Recent publications demonstrate her work in: Deep learning for cognitive impairment detection Digital twin architectures for energy optimization Neonatal pain assessment systems LLM applications in pediatric emergency diagnostics Current projects involve developing non-invasive biomarkers for dementia diagnosis and AI algorithms for infant monitoring systems. Bergamasco's work bridges computer engineering with healthcare applications, integrating multimodal data analysis and real-time processing systems.
جستوجوی استاد و پژوهشگر
استاد راهنما، استاد دانشگاه یا پژوهشگر مناسب برای مسیر پژوهشیتان را پیدا کنید و با او ارتباط بگیرید.
نمایش ۳۱-۴۵ از ۱۷۰ استاد راهنما
اطلاعات این پروفایلها از صفحات عمومی دانشگاهها جمعآوری شده و ممکن است بهروز نباشد.
Mario Milazzoمشاهده پروفایل
پژوهشگر
Dr. Mario Milazzo is a researcher at the BioRobotics Institute of Sant'Anna School for Advanced Studies , with a current appointment at Massachusetts Institute of Technology (USA). His work bridges robotics, biomaterials, and computational modeling through interdisciplinary projects. He earned a PhD in BioRobotics (2016) from Sant'Anna School for Advanced Studies after completing his Mechanical Engineering degree at the University of Pisa (2010). Research Areas: Multiscale modeling, industrial robotics, biomaterials, and bioinspired design using deep learning. Industry Collaborations: Ge Oil&Gas, Brembo, Magneti Marelli, Piaggio. His recent publications highlight trends in industrial robotics (autonomous platforms, path planning, electro-hydraulic systems) and biomedical applications (bone regeneration, protein nanostructures, tympanic scaffolds). Key methodologies include sonification, molecular modeling, and AI-driven material design. Scientific Awards : Marie Skłodowska-Curie Individual Fellowships (MSCA-IF-GF) with MIT, University of Antwerp, Tufts, and University of Pisa He has co-authored 25+ international journal papers , 9 patents , and 24 conference contributions , while serving as a reviewer for 20+ journals and guest editor for Polymers (MDPI). His leadership roles in industry projects and symposium organization demonstrate his translational research focus.
Marco Mor is a Full Professor of Medicinal Chemistry at the University of Parma and a leading researcher in drug design and enzyme inhibition. His work spans computational modeling, synthetic chemistry, and pharmacokinetic studies, focusing on endocannabinoid modulators and melatonin receptor ligands. He has coordinated major projects like ONCOPENTA and the national PRIN initiative ExECS , and serves as Director of the PhD School in Biological, Pharmaceutical, and Food Sciences at the University of Parma. Education : Laurea (M.S.) in Pharmaceutical Chemistry and Technology, University of Parma (1990). Appointments : Lecturer (1993), Associate Professor (2000), Full Professor (2001–present). His research group integrates molecular modeling, synthetic chemistry, and analytical methods to develop novel pharmacological agents targeting enzymes like FAAH, MGL, and NAAA. Key contributions include the design of the FAAH inhibitor URB597 and its derivatives, as well as MT2-selective melatonin agonists for sleep disorders. Current work explores covalent EGFR inhibitors with reduced toxicity and gut microbiome interactions in drug metabolism. Recent publications highlight his interdisciplinary approach, covering topics from histone deacetylase inhibitors for fibrosis to microbiome-genome interactions in probiotic characterization. Collaborations with international teams on projects like the Integrated Probiotic Database and MEGAnnotator2 genome pipeline reflect his broad scientific impact.
Maximilian Millerمشاهده پروفایل
پژوهشگر ارشد
Maximilian Miller is a Research Fellow at the BrombergLab , affiliated with the School of Environmental and Biological Sciences and Department of Biochemistry and Microbiology. He focuses on variant effect prediction , metagenome analysis , and high-performance computing infrastructure. PhD in Bioinformatics (2018) from Technical University Munich MSc and BSc in Bioinformatics (2012, 2009) from Ludwig-Maximilians-University Munich / Technical University Munich His research employs machine learning to understand how protein mutations relate to disease , with applications in precision medicine and microbiome studies . He develops tools like clubber for cluster computing and funtrp for functional tuning analysis. The most recent 15 articles span variant interpretation , metagenomic pipelines , and computational method assessment across bioinformatics , protein science , and environmental microbiology . Scientific recognition includes the CAMDA Fellowship for ISMB/ECCB 2019. His work addresses challenges in metagenome recovery (e.g., Deepwater Horizon oil-spill study), taxonomic vs. functional shifts , and predictor performance benchmarks through the Critical Assessment of Genome Interpretation (CAGI) framework.
Dr. Luigi Santangelo is affiliated with the University of Pavia. He focuses on High-Performance Computing (HPC), Cloud Computing, and Parallel Computing, with significant contributions to bioinformatics applications and network security. His research integrates cloud-based scheduling for protein analysis and hemodynamic simulations, emphasizing computational efficiency and cost analysis in cloud vs on-premise systems. His work spans hybrid parallel computing models (OpenMP-MPI) and enterprise network management tools like RedHat Directory Server and OpenNMS. Recent efforts prioritize optimizing cloud infrastructure for bioinformatics tasks, such as protein secondary structure analysis and geometric motif searches in proteins. No scientific awards or grants are listed, but his publications reflect a strong emphasis on practical HPC solutions and cybersecurity protocols like SPID digital identity systems. He has not listed formal advisees, though his collaborative research likely involves student contributions.
Jessica Gliozzoمشاهده پروفایل
پژوهشگر ارشد
- Bioinformatics
- Machine Learning
- Deep Learning
- +۳ مورد دیگر
Jessica Gliozzo is a research fellow in bioinformatics at the IRCCS Ca' Granda – Ospedale Maggiore Policlinico of Milan and collaborates with the AnacletoLab (Bioinformatics and Computational Biology laboratory). She holds a BSc in Medical Biotechnology from the University of Milan (2014) and an MSc in Molecular Biotechnology and Bioinformatics from the same institution (2016). Her primary research interests include: Bioinformatics Machine Learning Deep Learning applications in genomics Analysis of Next Generation Sequencing data Dr. Gliozzo's current research focuses on the analysis of Next Generation Sequencing (NGS) data from patients affected by primitive hematopoietic proliferative disorders of the skin. She is actively developing deep learning neural networks for the prediction and prioritization of regulatory variants in human diseases and creating network-based semi-supervised models to predict patients' clinical outcomes by leveraging heterogeneous biological data. Her recent publications demonstrate a strong trend toward integrating multi-omics data, developing knowledge graphs for RNA interactions, and applying advanced machine learning techniques to clinical problems, particularly in cancer research and genomic analysis. Her work spans computational biology, medical informatics, and artificial intelligence applications in healthcare, with a particular emphasis on dimensionality reduction techniques, network-based approaches, and resource-efficient computational methods. Network-based patient similarity analysis RNA knowledge graph construction Resource-limited medical image processing Large language models for protein science Multi-omics data integration Dr. Gliozzo has maintained extensive collaborations with researchers including Giorgio Valentini, Elena Casiraghi, Marco Mesiti, and Alessandro Petrini across numerous publications in reputable journals such as BMC Bioinformatics, Scientific Reports, and Frontiers in Bioinformatics, demonstrating consistent research productivity from 2017 through 2025.
Marinella Sciortino is a Professor at the University of Palermo , affiliated with the School of Basic and Applied Sciences and the Department of Mathematics and Computer Science . She serves as Director of the CINI Research Unit and is a member of the Academic Senate (2022-2024). Sciortino contributes to editorial and scientific committees for journals and conferences, including Theoretical Computer Science and the GRIN Committee . Research focuses on: Combinatorics on Words String Algorithms Automata Theory Symbolic Dynamics Data Compression Biological Sequence Analysis Her work includes groundbreaking studies on the Burrows-Wheeler Transform (BWT) , extending its application to multiple sequences and improving compression efficiency. She has supervised PhD student Giuseppe Romana and participated in numerous conference program committees (e.g., SPIRE , ICTCS , CiE ). Recent scientific contributions (2022-2020): BWT teaching methodologies String attractors Variant discovery in genomics Algorithmic perspectives on alternating BWT Positional clustering for SNP detection Mental rotation effects on computational learning Teaching roles include Laboratorio di Algoritmi (Computer Science) and Teoria dell'Informazione e Compressione Dati (Master's in Computer Science). Contact: marinella.sciortino@unipa.it , +39-091-238-91080.
- Computer Science
- Security
- Distributed Systems
- +۳ مورد دیگر
Giuseppe Cattaneo is an Associate Professor at the Department of Computer Science , University of Salerno. His research spans multiple domains including Computer Security Distributed Systems Bioinformatics Mobile Communication Security Algorithm Engineering His work has produced significant contributions in cryptographic file systems, secure mobile messaging, and Hadoop-based bioinformatics solutions. Key research trends include Security protocols for mobile environments Scalable genomic data analysis Dynamic graph algorithm optimization Digital forensic countermeasures He has developed frameworks like GRACE for cryptographic visualization and FASTdoop for bioinformatics data processing. Professional activities involve Collaboration with international researchers Development of secure communication protocols Participation in algorithm engineering studies His recent 2021 publications focus on medical data analysis and thyroid cancer outcome prediction.
Riccardo Rizzoمشاهده پروفایل
پژوهشگر
Riccardo Rizzo is a researcher at the National Research Council of Italy ( CNR ), affiliated with the School of Medicine and Surgery at the University of Palermo. His work bridges mathematics, computer science, and biomedical applications. Research Interests Deep learning for medical imaging (MRI, X-ray, histopathology) Graph neural networks in bioinformatics and protein analysis Explainable AI for healthcare diagnostics Clustering algorithms in marine biology and metagenomics Scientific Contributions His recent publications highlight trends in interpretable machine learning for histopathological image classification, bacterial taxonomy, and ecological pattern recognition. Key methodologies include transformers, metric learning, and graph-based approaches. Contact Email: riccardo.rizzo@cnr.it Office: National Research Council of Italy, via Ugo La Malfa 153, Palermo
Alessandra Rustighi is a Fixed Term Researcher in the Department of Life Sciences at the University of Trieste, specializing in Cellular and Experimental Biology. She actively participates in departmental governance as a member of the Department's Board and Boards of Studies. Primary Research Focus: Biomedical applications of molecular nutrition and protein engineering Key Collaborations: Interconnected Nord-Est Innovation (iNEST) project, Trans2Care, Innov-H2O Scientific Expertise spans: Molecular Oncology Nutritional Biochemistry Biomaterial Development Signal Transduction Analysis Research Trends (from 2015-2023 publications): 2015-2017: Foundational work in cancer cell signaling and antibody engineering 2017-2020: Expansion into protein engineering with HELP/HUG bioreceptors 2020-2023: Development of targeted delivery systems and stress biomarkers for aquaculture Scientific Contributions include: Development of HUG bioreceptor for bilirubin analysis Creation of HELP polypeptide platform for biomaterials Identification of dietary phytochemical interactions with heme metabolism Establishment of fish blood biomarkers for welfare assessment
Emanuela Leonardiمشاهده پروفایل
استادیار
Emanuela Leonardi is an Assistant Professor (tenure track) in Biochemistry (SSD BIO/10) at the Department of Biomedical Sciences , University of Padua (Italy) , where she has held this position since October 2022. Her research focuses on Personalized Medicine , Neurodevelopmental Disorders , and Non-globular Domains in Human Diseases . PhD in Bioscience and Biotechnology (Curriculum: Biochemistry and Biophysics), University of Padova, 2012 MSc in Molecular Biology , University of Padova, 2008 BSc in Molecular Biology , University of Padova, 2005 Degree in Biomedical Laboratory Technician , University of Padova, 1998 Her recent publications highlight expertise in genetic variant interpretation , neurodevelopmental disorder diagnostics , and bioinformatics analysis of intrinsically disordered proteins , particularly through contributions to the CAGI (Critical Assessment of Genome Interpretation) and DisProt databases. Key collaborations span Human Genetics , Nucleic Acids Research , and computational genomics consortia.
Mario Mardirossian is an Associate Professor in Biochemistry at the University of Trieste , affiliated with the Department of Life Sciences . He actively participates in multiple research groups, including Host defence peptides - mode of action and biomedical applications (led by Prof. Scocchi) and Molecular microbiology (under Prof. Tossi). Research Focus : Antimicrobial peptides, bacterial biochemistry, and resistance mechanisms. Key Collaborations : Prof. Cescutti (University of Trieste), Tim Tolker-Nielsen (University of Copenhagen), Neil Ravenscroft (University of Cape Town). His work explores the structural and functional dynamics of host defense peptides and bacterial biofilms, particularly in Klebsiella pneumoniae and Burkholderia species. He contributes to projects funded by the Ministry of University and Research (PrAMP4KleBI) and collaborates with industrial partners on glycoconjugate vaccines. Advising : Mentors PhD student Riccardo Sola under the PrAMP4KleBI project. Labs & Teams : Works within Prof. Tossi’s host defense peptides group and Prof. Scocchi’s molecular microbiology team, utilizing advanced techniques like NMR spectroscopy, mass spectrometry, and molecular modeling.
Michele Loreti is Full Professor in Computer Science at the University of Camerino within the School of Science and Technology and serves as Director of the School of Advanced Studies. His career includes roles as Research Associate at University of Firenze (2002-2017) and Visiting Professor at IMT Institute for Advanced Studies (2012-2016). He holds a PhD in Mathematical Logic and Theoretical Computer Science from University of Siena (2001) and a Computer Science degree from University of Rome 'La Sapienza' (1997). Research interests: Formal tools for concurrent/distributed systems Quantitative analysis of collective adaptive systems Spatio-temporal model checking Process calculi and modal logics Programming languages for network-aware applications Runtime verification and dynamic system adaptation Article trends: His work focuses on formal verification of cyber-physical systems, spatio-temporal properties, stochastic process calculi, attribute-based communication, and tools like CARMA and muG for collective system analysis. Editorial roles: Assistant editor for Elsevier Journal on Logical and Algebraic Methods in Programming and member of the Reproducibility Board for ACM Transactions on Modelling and Computer Simulation.
Rosario Culmoneمشاهده پروفایل
استادیار
Rosario Culmone is an Assistant Professor at the University of Camerino, with a strong research focus in Internet of Things (IoT), sensor networks, and related technologies. His academic work spans multiple domains including smart city applications, blockchain implementations, and educational technology. Dr. Culmone's research interests center around IoT interoperability , sensor network optimization , and formal verification methods for intelligent environments. His work demonstrates a consistent focus on practical applications of distributed systems, with significant contributions to energy-efficient routing algorithms, blockchain-based certification systems, and ontology-driven frameworks for ambient assisted living. An analysis of his publication record reveals a clear trajectory from foundational work in wireless sensor networks and ECA rules verification toward more applied research in smart city technologies, food traceability using blockchain, and AI-enhanced educational systems. His most recent publications (2023-2025) show increased focus on practical implementations addressing real-world problems in security, education, and supply chain management. Dr. Culmone has developed several notable frameworks including the Share Pattern for IoT interoperability, NARUN for noise-adaptive routing, and IRON , a domain-specific language for programming IoT devices. His research bridges theoretical computer science with practical implementations across multiple application domains.
Andrea Secchi is a Full Professor in the Department of Chemical, Life and Environmental Sustainability Sciences at the University of Parma. He holds a Master's in Chemistry (1992) and a PhD in Chemical Sciences (1995) from the University of Parma. His research focuses on supramolecular chemistry, molecular recognition, and nanoscience, particularly involving calixarene-based systems, molecular machines, and functional nanomaterials. He has supervised over 60 theses and 8 PhD students in chemistry and materials science. His work bridges organic synthesis, materials science, and bioapplications, with over 94 peer-reviewed articles and a citation count exceeding 2,800. Education: PhD in Chemical Sciences, University of Parma (1995) Master's in Chemistry, University of Parma (1992) Research interests include calixarene functionalization for molecular machines, hybrid organic-inorganic nanomaterials, and NIR dye-plasmonic material interactions. His nanomaterials research spans gold/silver nanoparticles, magnetic nanoparticles, and self-assembled monolayers. Recent work explores applications in biosensing, drug delivery, and environmental analysis. Teaching roles since 2005 include courses in Physical Methods in Organic Chemistry, Organic Chemistry of Materials, and Environmental Chemistry at both undergraduate and graduate levels. Administrative roles include Chair of the Chemistry Course of Study Board, member of the Department Safety Committee, and international mobility committee. He collaborates with institutions in France, Germany, Belgium, and the UK on calixarene-based projects. Publications demonstrate expertise in calixarene derivatives, rotaxane/catenane synthesis, and nanomaterial functionalization. Over 2860 citations highlight impact in supramolecular and materials chemistry fields.