Find Academic Supervisors

• Biochemistry
• Biotechnology
• Enzymology
• +6 more

Silvia Holler is a Researcher (RTD-A) at the Department of Cellular, Computational, and Integrative Biology (CIBIO) at the University of Trento. She specializes in biochemistry, biotechnology, and synthetic biology with a focus on enzymology, catalysis, and structural biology. Her work spans experimental and computational studies of protocells, droplet-based systems, and self-organizing soft matter. Teaching responsibilities include co-teaching the Biochemistry course at CIBIO, where she collaborates with scholars like Giovanni Piccoli and Martin Michael Hanczyc. The course covers foundational topics in biochemistry, enzymology, and molecular structures with practical skills in chromatography and enzymatic kinetics. Research interests emphasize artificial life systems, droplet engineering, and the physics of biological organization. Key themes include protocell formation, compartmentalized biochemistry, and ethical implications of synthetic biology innovations. Recent work explores self-organized patterns in soft matter, active matter dynamics, and computational modeling of multi-phase systems. Publications focus on droplet microfluidics, vesicle interactions, and agglomeration phenomena across scales. Collaborative efforts include editorial roles for artificial life conference proceedings and interdisciplinary projects combining biophysics with materials science. No scientific awards were explicitly mentioned in the provided materials. Her research lab activities are embedded within CIBIO's facilities, focusing on experimental setups for droplet-based synthetic biology and computational simulations of complex systems.

Kirsten Andrea SchnorrView profile

Researcher

• Ultrafast Science
• Atomic Physics
• Molecular Physics
• +6 more

Kirsten Andrea Schnorr is a Researcher at the Paul Scherrer Institute (PSI) in Switzerland, working within the Center for Photon Science and Laboratory for Femtochemistry. She joined the SwissFEL team in 2018 to develop the Maloja endstation for atomic, molecular, and non-linear physics, leading its design, construction, and operational commissioning for cutting-edge XUV/X-ray experiments. Her educational background includes: PhD in Physics (2014), Ruprecht Karl University Heidelberg, completed at the Max Planck Institute for Nuclear Physics under PD Dr. Robert Moshammer; thesis focused on XUV pump-probe experiments of electron rearrangement and interatomic Coulombic decay in diatomic molecules. Schnorr's research centers on photo-induced ultrafast relaxation mechanisms in atoms, molecules, and nanoparticles using time-resolved techniques at Free-Electron Lasers and High Harmonic Generation sources. She pioneers multi-color pump-probe schemes with ultrashort X-ray pulses to steer non-local decay processes like Interatomic Coulombic Decay and Electron Mediated Decay, enabling real-time observation of electron dynamics and proton transfer in molecular systems. Her publication trends (2025-2020) reveal dual expertise in fundamental molecular dynamics and instrumental innovation. Key themes include proton transfer in water dimers (Science Advances 2023), Coulomb explosion in iodinated compounds (2025), and engineering breakthroughs like compact gas attenuators (2023) and polarization control systems (2024), frequently published in Physical Review Letters, Nature Communications, and Journal of Synchrotron Radiation. Scientific awards: Peter Paul Ewald Fellowship from the Volkswagen Foundation (2015), supporting her research on non-linear relaxation processes at UC Berkeley's Physical Chemistry Department under Prof. Stephen Leone. No formal advisees or student supervision are documented. The Volkswagen Foundation fellowship served as her primary grant, funding postdoctoral work on real-time relaxation studies; no additional grants are specified. Her instrumental leadership at SwissFEL suggests mentorship of junior scientists, though no individual students are named. Schnorr directs the Maloja instrument at SwissFEL while contributing to the ATHOS beamline development. She collaborates extensively with PSI's detector teams (e.g., JUNGFRAU advancements) and international groups like UC Berkeley's Physical Chemistry Department, driving initiatives in ultrafast beamline technology and molecular dynamics experiments.

Carlos A. Ocampo MartínezView profile

Associate Professor

• Control Engineering
• Model Predictive Control
• Constrained Control Systems
• +12 more

Carlos A. Ocampo Martínez is an Associate Professor in the Department of Automatic Control (ESAII) at the Universitat Politècnica de Catalunya (UPC), BarcelonaTech, Spain. He is affiliated with the Institut de Robòtica i Informàtica Industrial, CSIC-UPC, a joint research center between UPC and the Spanish National Research Council. He has been with UPC since 2011 and served as Deputy Director of IRI from 2014 to 2018. Education: PhD in Control Engineering, Universitat Politècnica de Catalunya, 2007 MSc in Industrial Automation, National University of Colombia, 2003 BSc in Electronics Engineering, National University of Colombia, 2001 His research is centered on model predictive control (MPC) , particularly constrained and distributed MPC, with applications in energy, water, and smart manufacturing. He investigates large-scale systems management, partitioning strategies, and non-centralized control architectures. His work integrates IoT frameworks for smart industrial systems. Key domains include renewable hydrogen production, fuel cell vehicles, microalgae bioreactors, and solar thermal plants. The recent publications reflect a strong trend in applying control theory to sustainable energy systems and environmental management. There is a clear focus on integrating game theory, population dynamics, and optimization into MPC frameworks for distributed and coalitional control. Applications span hydrogen infrastructure, solar energy, water irrigation, and transportation electrification, demonstrating interdisciplinary impact. Scientific Awards: Juan de la Cierva Research Fellow Dr. Ocampo-Martínez actively supervises PhD students and leads research projects such as MASHED , which focuses on digitalized energy systems with hybrid storage. He has advised students on topics including alkaline electrolyzers, hydrogen production control, and alcohol steam reformers. His grant involvement emphasizes renewable integration, smart grids, and sustainable transport. He collaborates with researchers across Europe and contributes to high-impact journals and IFAC conferences. He is a key member of the Automatic Control research group at ESAII and contributes to the strategic direction of the Institut de Robòtica i Informàtica Industrial. His team integrates control theory, optimization, and real-world industrial applications, particularly in energy and water systems.

• Automation
• Robotics
• Control Systems
• +5 more

Prof. Igor Krčmar is a full professor at the Faculty of Electrical Engineering of the University of Banja Luka, specializing in Automation and Robotics . He holds a position in the Department of Automation and teaches courses at both undergraduate and graduate levels. His research focuses on control systems, neural networks, electrical drives, and adaptive control methodologies. He has authored several textbooks including Upravljanje u realnom vremenu (Real-Time Control) and Senzori i Aktuatori (Sensors and Actuators). His recent work emphasizes sensorless motor control, PI controller optimization for industrial systems, and machine learning applications in occupancy estimation. Over 25 years, he has published extensively in journals like IEEE Transactions on Industrial Electronics and conferences such as INFOTEH-JAHORINA and IcETRAN. His work bridges theoretical advancements with practical implementations in industrial automation and energy efficiency. Key contributions include: Development of discrete rotor flux estimators for high-speed drives Adaptive neural control algorithms for nonlinear systems Integration of fuzzy logic with hydrodynamic process control Optimization of PMSM drives for energy efficiency He collaborates internationally on EU-funded projects and serves on editorial boards of electrical engineering journals.

• Quantum Control Systems
• Quantum Information Processing
• Quantum Reservoir Computing
• +5 more

Dr. Hendra Nurdin is a Senior Lecturer in the School of Electrical Engineering and Telecommunications at the University of New South Wales (UNSW), where he has been employed since 2012. His academic journey began with a Sarjana Teknik (equivalent to a Bachelor of Engineering) in Electrical Engineering from Institut Teknologi Bandung, Indonesia, followed by an MSc in Engineering Mathematics from the University of Twente in the Netherlands, and culminated with a PhD in Engineering and Information Science from the Australian National University in 2007. His educational background includes: PhD in Engineering and Information Science, Australian National University, 2007 MSc in Engineering Mathematics, University of Twente, The Netherlands Sarjana Teknik (ST, equivalent to Bachelor of Engineering) in Electrical Engineering, Institut Teknologi Bandung, Indonesia Dr. Nurdin's research lies at the intersection of control engineering and systems theory with quantum physics and energy systems. He has made significant contributions to quantum control systems, quantum information processing, and microgrid control. His work combines theoretical advances in quantum stochastic processes with practical applications in quantum computing and renewable energy systems. He has developed novel approaches to quantum reservoir computing, quantum parameter estimation, and control of distributed energy resources. His recent publications reveal a strong focus on quantum reservoir computing, non-Markovian quantum systems, and the intersection of quantum information with machine learning. There's a clear trend toward practical implementations of quantum information processing systems, particularly exploring how quantum systems can enhance computational capabilities. His work bridges fundamental quantum theory with engineering applications, demonstrating how quantum phenomena can be harnessed for practical computing and sensing tasks. Dr. Nurdin has received recognition including an ARC APD Fellowship (2009-2011). His research has resulted in numerous publications in top-tier journals including Nature Communications, Physical Review series, and IEEE Transactions. He has successfully supervised multiple PhD students to completion, including Dr. Jiayin Chen (2022), Dr. Jiacheng Li (2021), Dr. Muhammad Ali (2021), and Dr. Zhan Shi (2016). Currently, he is supervising Mr. Wen Liu as a PhD candidate. His research is supported by various funding mechanisms including Sydney Quantum Academy scholarships and UNSW research grants, enabling him to pursue cutting-edge research in quantum systems and control. Dr. Nurdin is actively involved with the Sydney Quantum Academy, supervising research in quantum systems and control. His work contributes to Australia's growing quantum technology ecosystem, collaborating with researchers across multiple institutions to advance quantum information processing and quantum engineering applications.

• Electric Machines
• Permanent Magnet Motors
• Reluctance Motors
• +7 more

Lale Ergene is a Professor in the Department of Electrical Engineering at Istanbul Technical University (ITU), College of Engineering. Her research focuses on advanced electric machine design and control systems for industrial and automotive applications. She is actively involved in motor drive innovation, particularly in permanent magnet and reluctance motor technologies. Research Interests: Dr. Ergene specializes in electric machines, with emphasis on Permanent Magnet Synchronous Motors (PMSM), Interior Permanent Magnet (IPM) motors, and Permanent Magnet Assisted Synchronous Reluctance Motors (PMaSynRM). Her work spans sensorless control, field weakening techniques, finite element analysis, and motor optimization for electric vehicles and home appliances. She applies intelligent control methods such as neuro-fuzzy systems and real-time diagnostics. Recent Research Trends: Her recent publications (2023–2024) show a strong focus on improving motor efficiency and control robustness, especially in EV traction systems and white goods. Key themes include voltage distortion reduction, flux weakening enhancement, real-time parameter estimation using FFT, and lean sensorless control at zero/low speeds. Her work bridges theoretical modeling with industrial applications. Scientific Awards: Best Poster Paper AWARD (2016) Graduation Design and Project Competition 2nd Prize (2015) ITU 2014 Best Doctoral Thesis Award (2015) Advising and Grants: Dr. Ergene has supervised or is currently supervising 25 theses, indicating a strong mentoring role. She has led multiple funded projects, including TÜBİTAK and ITU BAP grants, focusing on FPGA-based neural network control, three-level inverter design, real-time model diagnostics, and sensorless control for washing machines and EVs. Her projects demonstrate sustained research funding and applied engineering impact. Labs and Research Teams: While specific lab names are not mentioned, her projects imply leadership in a motor control and electric machines research group at ITU, likely involving FPGA, real-time simulation, and embedded control systems. Her collaborations with researchers like A.F. Ergenc, M. Yilmaz, and A. Tap suggest an active, multidisciplinary team focused on next-generation motor drives.

Douglas D. HodsonView profile

Professor

• Computer Engineering
• Software Engineering
• Real-Time Distributed Simulation
• +7 more

Douglas D. Hodson is a Professor of Computer Engineering at the Air Force Institute of Technology (AFIT), Wright-Patterson AFB, Ohio, affiliated with the Department of Systems and Engineering Management within the Graduate School of Engineering and Management. He holds a PhD in Computer Engineering from AFIT (2009), an MBA and MS in Electro-Optics from the University of Dayton, and a BS in Physics from Wright State University. His research focuses on computer engineering, software engineering, real-time distributed simulation, and quantum communications , with a strong emphasis on Quantum Key Distribution (QKD) systems, modeling and simulation (M&S), and Live-Virtual-Constructive (LVC) environments. His work integrates cybersecurity, network performance, and advanced simulation frameworks such as AFSIM and SwarmSim. His recent publications (2021–2022) reflect a trend toward secure distributed systems, AI-driven classification, fog modeling in military simulations, and opinion dynamics in social systems. These works span disciplines including cybersecurity, artificial intelligence, defense modeling, and environmental effects in multi-domain operations. Scientific Awards and Honors: IEEE Senior Member (2021) Outstanding Achievement Award, World Congress in CSCE (2018) SOCHE Faculty Excellence Award (2017) Harold Brown Award (2015) Multiple AFIT Civilian Category III Awards (2014, 2013) Dayton Area Graduate Studies Institute Scholar (2003–2007) Rev. Raymond A. Roesch, S.M., Award of Excellence, University of Dayton MBA (1998) Advising and Grants: Dr. Hodson has advised numerous graduate students, many of whom are co-authors on his publications. His research has been supported by AFIT, AETC, and collaborative defense-focused grants, particularly in quantum communications and simulation technologies. He has led or contributed to teams receiving Air Force Modeling and Simulation Team Awards and QKD Research Team Awards. Labs and Teams: He is a key contributor to the AFIT Quantum Communications and Modeling & Simulation research teams, working on projects involving AFSIM, QKD system modeling, decoy state protocols, and swarm UAV simulation. His lab environment fosters interdisciplinary collaboration in cybersecurity, physics, and software engineering.

• Computer Vision
• Pattern Recognition
• Facial Analysis
• +5 more

Jorge Manuel M. C. Pereira Batista is an Associate Professor at the Department of Electrical and Computer Engineering , University of Coimbra, Portugal. He serves as a senior researcher at the Institute for Systems and Robotics (ISR-UC) and leads the Computer Vision Group. His career spans academic roles, research coordination, and industry collaboration. Academic Affiliation: University of Coimbra (Electrical & Computer Engineering Department) Research Institute: Institute for Systems and Robotics (ISR-UC) His research focuses on Computer Vision , Pattern Recognition , and applications of Differential Geometry in these fields. Key subdomains include facial analysis, visual surveillance, real-time vision systems, and machine learning integration. From 2010–2023, his recent publications highlight advancements in probabilistic models , transformer architectures , multi-branch learning , and biomimetic robotics . He has coordinated multiple funded projects such as: STORK : Avian protection systems NeuroCity : Intelligent street lighting 4D Facial Dynamics : Identity recognition iTRAFFIC : BRISA highway traffic monitoring His work bridges theoretical innovation (e.g., Riemannian manifold applications) with practical deployments in transportation, energy, and healthcare sectors.

Andrea TosinView profile

Professor

• Mathematical Physics
• Kinetic Theory
• Transport and Diffusion Equations
• +7 more

Andrea Tosin is a Full Professor of Mathematical Physics at the Department of Mathematical Sciences "G. L. Lagrange" (DISMA), Politecnico di Torino. He serves as Coordinator of the Doctoral College of Mathematical Sciences and Deputy Coordinator of the Doctoral College of Pure and Applied Mathematics. His research bridges kinetic theory, transport equations, and applied mathematics with applications in multi-agent systems, traffic, social dynamics, and epidemiology. His research interests focus on: Kinetic theory and its applications to real-world systems Transport and diffusion equations in complex environments Modeling of vehicular traffic, crowd dynamics, and social behavior Epidemiological modeling with a focus on viral load and multi-scale dynamics Mathematical modeling of collective behavior in biological and social systems His recent publications demonstrate a consistent trend in developing and analyzing kinetic models for traffic flow, opinion dynamics, and epidemic spread, often incorporating uncertainty, network structures, and multi-population interactions. These works frequently involve rigorous mathematical derivations from microscopic models to macroscopic equations, with applications in safety, public health, and urban planning. His scientific awards include: SIMAI Biennial Award (2013) INDAM-SIMAI Award (2010) He actively supervises PhD students and postdoctoral researchers, including Martina Fraia, Emanuele Bernardi, Elisa Paparelli, and Mattia Sensi. He has secured significant research grants from national (PRIN, INdAM) and institutional (Politecnico di Torino, Google) sources. His research is supported by projects such as IMASED (Integrated Mathematical Approaches to Socio-Epidemiological Dynamics) and ANATOMY (A Unitary Mathematical Framework for Modelling Muscular Dystrophies). He also leads the "Modelli e Metodi della Fisica Matematica" research group at DISMA.

Rolf FindeisenView profile

Professor

• Model Predictive Control (MPC)
• Cyber-Physical Systems
• Battery Systems Optimization
• +5 more

Prof. Rolf Findeisen is a Professor in the Department of Control and Cyber-Physical Systems (CCPS) at Technische Universität Darmstadt. His work focuses on advancing control theory and its applications in cyber-physical systems, autonomous systems, and energy storage systems. Key areas include model predictive control (MPC), battery management systems, machine learning integration into control frameworks, and optimization of crystallization processes. He leads research on safety-critical systems, data-driven control methods, and interdisciplinary applications in robotics and biotechnology. His research spans theoretical advancements in MPC stability, stochastic control, and Gaussian process modeling, alongside practical implementations in autonomous vehicles, lithium-ion battery systems, and bioprocess optimization. Notable contributions include frameworks like HILO-MPC for integrating machine learning with control systems, and methodologies for safe exploration in autonomous navigation. Prof. Findeisen's publications emphasize energy-efficient trajectory planning, fault detection in battery systems, and real-time optimization of manufacturing processes. His work bridges academic theory with industrial applications, addressing challenges in scalability, safety, and computational efficiency. His lab collaborates on national projects like IN-Fly-Tec and INFLIGHT, focusing on innovative flight control systems and sensor technologies. Current research trends include hybrid intelligent optimization, cybergenetic control of microbial systems, and safe reinforcement learning for control systems.

Liya ZhaoView profile

Senior Lecturer

• Energy Harvesting
• Nonlinear Dynamics
• Smart Materials and Structures
• +14 more

Dr. Liya Zhao is a Senior Lecturer in the School of Mechanical and Manufacturing Engineering at the University of New South Wales (UNSW Sydney), where she leads the Dynamic Smart Structures and Energy Harvesting Laboratory. She previously held academic positions at the University of Technology Sydney (UTS), first as a Lecturer (2017) and later promoted to Senior Lecturer (2021), before joining UNSW in 2022. Her research is highly interdisciplinary, focusing on smart structures, nonlinear dynamics, and sustainable energy technologies. Education: Ph.D. in Structures & Mechanics, Nanyang Technological University, Singapore (2015) B.Eng. in Civil Engineering, Tongji University, China (2009) Research Interests: Dr. Zhao's work centers on energy harvesting from ambient sources (wind, vibration, human motion, waves), smart materials (piezoelectric, triboelectric), metamaterials, and nonlinear dynamics. She designs adaptive structures for broadband energy harvesting and vibration suppression, with applications in self-powered wireless sensor networks, structural health monitoring, and wearable devices. Her research integrates theoretical modeling, numerical simulation, and experimental validation. Publication Trends: Over the past decade, her research has evolved from fundamental electromechanical modeling toward multifunctional metastructures and real-world deployment. Her recent work emphasizes hybrid energy harvesting, nonlinear tuning for broadband response, and integration with self-powered sensing systems, reflecting a strong trend toward practical, sustainable technologies. Scientific Awards: ARC Discovery Early Career Researcher Award (DECRA), 2021–2024 World's Top 2% Scientists (Stanford University), 2020–2023 Nanyang Engineering Doctoral Scholarship (NEDS), NTU Singapore Grants & Supervision: Dr. Zhao has secured multiple competitive grants, including ARC Discovery Projects and internal university funding, as both sole and chief investigator. She actively supervises research students and welcomes motivated candidates in mechanics, dynamics, and energy systems. Her lab, Dynamic Smart Structures and Energy Harvesting Lab , fosters innovation through experimental and computational research. She also contributes to teaching, including Mechanics of Solids II and Introduction to Aircraft Engineering. Lab & Team: She leads a dynamic research group focused on next-generation smart structures, supported by state-of-the-art facilities at UNSW. Her team develops novel materials and systems for sustainable energy and sensing, aiming to bridge the gap between fundamental science and real-world applications.

Tran Trung LuuView profile

Assistant Professor

• Ultrafast Optics
• Strong-Field Laser Physics
• Attosecond Science
• +7 more

Tran Trung Luu is an Assistant Professor at the Department of Physics , Faculty of Science , The University of Hong Kong . He earned his B.Sc. from Vietnam National University (2007), M.Sc. from Korea Advanced Institute of Science and Technology (2010), and Ph.D. from Ludwig-Maximilians-Universität München (2015). Currently, he leads research in Ultrafast Optics , Strong-Field Laser Physics , and Attosecond Science , with a focus on probing coherent lattice vibrations and electron-phonon coupling in solids using high-harmonic spectroscopy. Education: B.Sc. in Physics, Vietnam National University (2007) M.Sc. in Physics, Korea Advanced Institute of Science and Technology (2010) Ph.D. in Physics, Ludwig-Maximilians-Universität München (2015) Research Interests revolve around Ultrafast Optics and Strong-Field Laser Physics , particularly Attosecond Science applications in condensed matter. His work bridges Nonlinear Spectroscopy with Quantum Dynamics in Solids , utilizing High-Harmonic Generation to study Electron-Phonon Coupling and Anharmonic Phonon Scattering . Publications highlight trends in Coherent Lattice Dynamics , Time-Resolved Photoelectron Spectroscopy , and Optical Manipulation of Bandgaps . Scientific Awards include the ISUILS Young Researcher Award (2015) and an ETH Postdoctoral Fellowship (2015) . As a Principal Investigator , he has secured grants such as RGC ECS project 27300820 and GRF project 17315722 , totaling over HKD 2,819,760. He actively supervises PhD and MPhil students in Ultrafast Optics projects and contributes to invited lectures on Attosecond Science at institutions like Phenikaa University and ETH Zurich.

• Laser Modification of Materials
• Thin Films of Semiconducting Oxides and Nitrides
• Glassy Materials and Applications
• +7 more

Daniel G Georgiev is a Professor in the Department of Electrical Engineering and Computer Science at the University of Toledo's College of Engineering. He has been on faculty since Fall 2006, following prior roles as a research faculty member at Wayne State University's Center for Smart Sensors and Integrated Microsystems (SSIM). Education : M.S. in Engineering Physics (Quantum Electronics and Laser Equipment) from Sofia University (1994), Ph.D. in Electrical Engineering (Electronic Materials and Devices) from the University of Cincinnati (2003). Research Interests : Dr. Georgiev's work focuses on laser modification and micro-structuring of materials, thin films of semiconducting oxides/nitrides (e.g., NiO, Zn3N2), glassy materials, metal whiskers (Sn, Cu), wide bandgap semiconductors (GaN, Zn3N2), photovoltaics, and biomedical device applications. His expertise spans device fabrication, material characterization, and radiation effects. Article Trends : Recent publications emphasize GaN-based power electronics, hybrid edge termination structures, threshold switching in nanocircuitries, and material innovations via reactive sputtering. Subfields include laser microstructuring, whisker suppression in Sn films, and doping strategies for nitride semiconductors. Collaborations : Co-authorship with researchers across institutions, including contributions to biomedical implants, II-VI nanocrystals, and chalcogenide glasses.

• Dendrochronology
• Climate Change Research
• Tree Ring Analysis
• +4 more

Evgeny Aleksandrovich Vaganov is a distinguished academic serving as the scientific director of Siberian Federal University (SFU) and a member of both the Academic Council of SFU and the Scientific and Technical Council. As an Academician of the Russian Academy of Sciences, he holds one of the highest scholarly honors in Russia. His primary research address is at Akademgorodok, 50A, building 2, office 511 in Krasnoyarsk. Dr. Vaganov earned his education at Krasnoyarsk State University, specializing in Biophysics in 1971. His academic journey has led him to become a leading expert in dendrochronology and environmental science. Vaganov's research focuses on the analysis of tree rings as indicators of climate change and environmental conditions, with significant contributions to ecological modeling. His work bridges the gap between traditional dendrochronology and modern climate science, developing innovative methods to extract climate signals from wood anatomy. He has pioneered approaches in quantitative wood anatomy and developed models like VS-Cambium-Developer to understand cambium functioning under environmental stress. His extensive publication record demonstrates a clear progression from traditional tree-ring width analysis to more sophisticated dendroanatomical and dendrochemical approaches. Recent work emphasizes high-resolution analysis of wood cells, soil carbon dynamics, and the development of process-based models that connect daily meteorological conditions with tree growth patterns. His research spans multiple Siberian ecosystems, from the Western Sayan Mountains to Central Siberian forests. Diploma "Golden Badge of Public Recognition" (Russia) Laureate of the Alexander von Humboldt Foundation Prize (Germany) Laureate of the V. N. Sukachev Prize of the Presidium of the Russian Academy of Sciences Honorary badge "Silver Sigma" for many years of creative work Medal of the Order "For Merit to the Fatherland", 2nd degree Order of Friendship Honorary citizen of Krasnoyarsk As scientific director of SFU, Vaganov oversees significant research initiatives, particularly those related to forest-climate interactions and carbon cycling. His work on Russian forests' contribution to climate change mitigation has informed national policy discussions related to the Paris Climate Agreement. He has led major projects examining the carbon budget of Siberian forests and the role of Russian forests in global carbon cycling. Vaganov's research group operates within Siberian Federal University's extensive research infrastructure, conducting field studies across Siberia's diverse forest ecosystems. His team utilizes advanced laboratory techniques for wood anatomy analysis and maintains long-term ecological monitoring sites throughout the region. Current work focuses on developing high-resolution climate proxies from wood anatomy and understanding forest responses to increasing climate variability.

• Mathematical Finance
• Stochastic Processes
• Affine Processes
• +5 more

Christa Cuchiero is a Professor at the Department of Statistics and Operations Research, Faculty of Business, Economics and Statistics, University of Vienna. Her research spans Mathematical Finance, Stochastic Processes, and Machine Learning applications in finance. She has over 48 publications, including recent work on signature-based models for SPX/VIX options, polynomial McKean-Vlasov SDEs, and infinite-dimensional Wishart processes. Her projects include 'Dynamic Uncertainty Modeling in Finance' and a long-term study on 'Universelle Strukturen in Finanzmathematik' (2020–2028). Research Interests: Signature methods for financial modeling Affine and polynomial processes Machine learning in finance Measure-valued stochastic differential equations Volterra equations and rough path theory Portfolio optimization and risk management Scientific Awards: Bruti-Liberati Visiting Fellowship (2018) Fellow at the Center for Advanced Study (CAS), Norwegian Academy of Science and Letters (2024) ETH Medal for Ph.D. thesis (2012) Recent Publications (2023–2025) focus on signature methods, stochastic portfolio theory, energy markets, and robust calibration techniques. Her work integrates advanced mathematical theory with practical financial applications, emphasizing nonlinear SPDEs, polynomial models, and machine learning frameworks.