Francesco Latini | White matter | Best Researcher Award

Published on by Academic Awards

Assoc. Prof. Dr. Francesco Latini | White matter | Best Researcher Award

Assoc. Prof. Dr. Francesco Latini, Uppsala University Hospital, Sweden

Assoc. Prof. Dr. Francesco Latini, M.D., Ph.D., is an Associate Professor in Neurosurgery at Uppsala University Hospital, Sweden. His expertise spans general neurosurgery, neuro-oncology, and cerebrovascular diseases. With a deep interest in brain connectivity and gliomas, Dr. Latini has contributed significantly to advancing neurosurgical practices. He leads the Neurointermediate Intensive Care Unit and coordinates regional clinical processes for malignant brain tumors. 🌍🧠💉

Publication Profile

Google Scholar

Education

Dr. Latini graduated in 2006 from the University of Bologna, Italy. He completed his specialization in Neurosurgery in 2013 (cum laude) at the University of Ferrara, Italy. In 2021, he earned a Ph.D. in Medical Sciences from Uppsala University, focusing on the anatomy and behavior of low-grade gliomas. His training includes specialized fellowships in neurovascular surgery and neuro-oncology at various prestigious institutions worldwide. 🎓📚🏥

Experience

Dr. Latini’s career spans from Resident in Neurosurgery at S.Anna University-Hospital, Ferrara (2008-2013) to roles in Uppsala University-Hospital since 2014. He has held positions as a ward physician, junior consultant, and senior consultant in neurosurgery. Currently, he heads the Neurointermediate Intensive Care Unit and serves as the regional coordinator for malignant brain tumor clinical processes. He is also an associate professor in neurosurgery. 🏥🧑‍⚕️💼

Awards and Honors

Dr. Latini has received numerous awards for his contributions to neurosurgery, including recognition for his work in neuro-oncology and cerebrovascular diseases. He is highly regarded in both research and clinical practice and has been acknowledged for his clinical leadership in brain tumor management and neurosurgical innovation. His honors reflect his excellence in both teaching and surgical practice. 🏆🎖️🌟

Research Focus

Dr. Latini’s research primarily focuses on the role of white matter anatomy in the behavior and surgical treatment of low-grade gliomas. He explores the radiological and histopathological features of diffuse gliomas, aiming to develop new models for their treatment. His work bridges the gap between clinical neurosurgery and advanced imaging technologies, emphasizing preoperative planning and patient outcomes. 🧠🔬

Publication Top Notes

  • Expression of 19 microRNAs in glioblastoma and comparison with other brain neoplasia of grades I–III – Cited by: 118 – Year: 2014 🧠📑

  • Segmentation of the inferior longitudinal fasciculus in the human brain: A white matter dissection and diffusion tensor tractography study – Cited by: 117 – Year: 2017 🧠📊

  • Extension of diffuse low-grade gliomas beyond radiological borders as shown by the coregistration of histopathological and magnetic resonance imaging data – Cited by: 80 – Year: 2016 🧠🩻

  • The Prognostic Roles of Gender and O6-Methylguanine-DNA Methyltransferase Methylation Status in Glioblastoma Patients: The Female Power – Cited by: 58 – Year: 2018 🧠⚖️

  • New insights in the limbic modulation of visual inputs: The role of the inferior longitudinal fasciculus and the Li-Am bundle – Cited by: 55 – Year: 2014 🧠🔬

  • Awake surgery in low-grade gliomas harboring eloquent areas: 3-year mean follow-up – Cited by: 49 – Year: 2011 🧠💉

  • Time course of neurological deficits after surgery for primary brain tumours – Cited by: 47 – Year: 2020 🧠🕰️

  • Pattern of care and effectiveness of treatment for glioblastoma patients in the real world: Results from a prospective population-based registry – Cited by: 46 – Year: 2014 🧠📈

  • Brain interstitial nociceptin/orphanin FQ levels are elevated in Parkinson’s disease – Cited by: 46 – Year: 2010 🧠⚖️

  • Is the resection of gliomas in Wernicke’s area reliable? – Cited by: 45 – Year: 2012 🧠💬

  • miRNAs expression analysis in paired fresh/frozen and dissected formalin fixed and paraffin embedded glioblastoma using real-time PCR – Cited by: 39 – Year: 2012 🧠🔬

  • The use of a cerebral perfusion and immersion–fixation process for subsequent white matter dissection – Cited by: 34 – Year: 2015 🧠⚙️

  • Mobilization of the transcavernous oculomotor nerve during basilar aneurysm surgery: biomechanical bases for better outcome – Cited by: 34 – Year: 2014 🧠⚙️

  • New insights into the anatomy, connectivity and clinical implications of the middle longitudinal fasciculus – Cited by: 33 – Year: 2021 🧠🌐

  • Definition of miRNAs expression profile in glioblastoma samples: the relevance of non-neoplastic brain reference – Cited by: 32 – Year: 2013 🧠📚

Luca Faes | Computational neuroscience | Best Researcher Award

Published on by Academic Awards

Prof. Luca Faes | Computational neuroscience | Best Researcher Award

Professor, University of Palermo, Italy

Prof. Luca Faes is a Full Professor at the Department of Engineering, University of Palermo, Italy. He earned his MSc in Electronic Engineering (1998) from the University of Padova and a PhD in Electronic Devices (2003) from the University of Trento. His research focuses on biomedical signal processing, information dynamics, and physiological networks. He has held positions at institutions such as the Bruno Kessler Foundation, University of Trento, and has been a visiting researcher in the USA, Belgium, and Brazil. A recipient of multiple awards, including the IEEE Senior Member recognition, Prof. Faes has been named among the World’s Top 2% Scientists by Stanford University. He actively contributes to academic programs, Erasmus+ initiatives, and editorial boards in biomedical engineering.

Publication Profile

Scopus

Orcid

Education

Prof. Luca Faes earned his Master’s degree (Italian Laurea) in Electronic Engineering cum laude from the University of Padova, Italy, in 1998 ⚙️. He then pursued a PhD in Electronic Devices at the University of Trento, Italy, in 2003 🏅. His academic journey laid the foundation for his expertise in biomedical engineering, signal processing, and complex system analysis 📡. With a strong background in electronic systems and bioengineering applications, he has made significant contributions to research and academia, shaping the field of biomedical signal processing and physiological network dynamics 🔬📊.

Professional Experience

Prof. Luca Faes has had a distinguished career in biomedical engineering and bioinformatics. He began as a Research Fellow (1999-2000) at ITC-irst, Trento, followed by a PhD at the University of Trento (2000-2003) 🎓. He held postdoctoral positions (2003-2013) at Trento’s Biophysics and BIOtech labs 🧬. Later, he became a Researcher (2014-2017) at FBK and Professor at the University of Palermo (2018-present) 🏅. His global research collaborations span USA, Belgium, and Brazil 🌍. Recognized as an IEEE Senior Member (2019) and among the World’s Top 2% Scientists (2021-2022), he is an esteemed expert in bioengineering and complex systems ⚙️📊.

Academic Contributions

Prof. Luca Faes has played a pivotal role in academic development and international collaborations. He has been a Doctorate Committee Member at CiMeC, University of Trento (2016-2017) and later at Palermo’s ICT Department (2018-present) 📚. He co-organized the Biomedical Engineering Master’s Program and serves as Vice Coordinator & Tutor for the Bachelor’s Program 🎓. As an Erasmus+ Coordinator, he has fostered partnerships with universities across Europe 🌍. He also leads the Biomedical Information Technologies Curriculum (2021-present) and organizes seminars with global scholars, strengthening biomedical and cybernetics engineering education 📡📊.

Teaching Contributions

Prof. Luca Faes has been actively involved in teaching since 1999, starting as a Teaching Assistant in General Physics II and Signal & Image Processing at the University of Trento 🎓. He has delivered specialized courses internationally, including Brazil 🇧🇷 (2015), IEEE MOOC (2016), and Portugal 🇵🇹 (2017). Since 2018, he has been a Tenured Professor at the University of Palermo, teaching Sensors, Biomedical Devices, and Statistical Analysis of Biomedical Signals 📊. His expertise in biomedical signal processing and sensor technology continues to shape future engineers in cybernetics and biomedical fields 🤖🔬.

🧠 Research Focus

Prof. Luca Faes specializes in computational neuroscience, biomedical engineering, and physiological signal processing. His research focuses on brain-heart interactions ❤️🧠, nonlinear dynamics 🔄, entropy measures 📊, and causal inference in physiological systems. He applies Granger causality and transfer entropy to analyze cardiovascular variability, cerebrovascular function, and neural synchronization. His work contributes to wearable health technology ⌚, autonomic regulation studies, and physiological stress assessment ⚡. He collaborates on machine learning 🤖 and high-order statistical modeling for biomedical applications. His interdisciplinary approach bridges neuroscience, physics, and AI-driven healthcare solutions. 🌍✨

Publication Top Notes

📄 Measures and Models of Brain-Heart Interactions – IEEE Reviews in Biomedical Engineering, 2025  🧠❤️

📄 Chaotic Dynamics and Synchronization under Tripartite Couplings – Chaos, Solitons and Fractals, 2024  🔄⚡

📄 Comparison of Feature Selection Methods for Physiological Stress Classification – Physiological Measurement, 2024  📊📈

📄 Disentangling High-Order Effects in Transfer Entropy – Physical Review Research, 2024 | 3 citations 🔗📡

📄 Assessing Granger Causality in Cerebrovascular Variability – IEEE Transactions on Biomedical Engineering, 2024 | 2 citations 🏥🧠

📄 Entropy Rate Measures for Time Series Complexity – Biocybernetics and Biomedical Engineering, 2024 | 4 citations 🔢📉

📄 Wearable Ring-Shaped Biomedical Device for Physiological Monitoring – Biosensors, 2024 | 3 citations ⌚📡

📄 Describing Cerebral Autoregulation via State Space Methods – Conference Paper, 2024 🏥📈

📄 Decomposing Transfer Entropy in Cardiovascular Interactions – Conference Paper, 2024 ❤️📊

📄 Gender Differences in Cardiovascular Variability Entropy – Conference Paper, 2024  🚻🫀