Find Academic Supervisors

Miguel Rico-RamirezView profile

Associate Professor

• Radar Hydrology
• Hydroinformatics
• Flood Forecasting
• +3 more

Dr. Miguel Rico-Ramirez serves as Associate Professor of Radar Hydrology and Hydroinformatics at the University of Bristol's School of Civil, Aerospace and Design Engineering. His research integrates advanced radar technology with hydrological modeling to address critical water resource challenges including flood forecasting, drought management, and precipitation measurement across diverse global contexts from South Korea to Mexico City. Education: Bachelor of Engineering (Eng.) Master of Engineering (M.Eng.) Ph.D. in Engineering, University of Bristol His research program focuses on radar-based precipitation estimation, hydroinformatics, and flood prediction systems. He pioneers deep learning applications for rainfall nowcasting and develops innovative methods for uncertainty quantification in hydrological modeling. Current work emphasizes cosmic-ray neutron sensor validation, satellite-based flood mapping, and seasonal forecast applications for reservoir operations, with strong emphasis on translating research into operational water management solutions. Recent publications (2023-2025) reveal three dominant research thrusts: (1) deep learning frameworks for spatiotemporal rainfall prediction, (2) global validation of precipitation and soil moisture datasets using novel sensor networks, and (3) operational implementation of seasonal forecasts for drought mitigation in South Korea. His work consistently bridges radar meteorology with practical hydrological applications across urban and data-scarce environments. Scientific Awards: No specific awards documented in source materials Dr. Rico-Ramirez supervises postgraduate researchers in radar hydrology and hydroinformatics, with projects spanning flood early warning systems, precipitation nowcasting, and climate adaptation strategies. His research receives funding for international collaborations focused on water security challenges, particularly in drought-prone regions and data-scarce basins like the Nile Delta. Current grants support development of integrated forecasting systems combining global datasets with machine learning for extreme event management. He leads the Radar Hydrology research group within Bristol's Water and Environmental Engineering division, collaborating closely with Professor Dawei Han on hydroinformatics and Dr. Rafael Rosolem on water-climate interactions. The team maintains active partnerships with meteorological agencies and water authorities globally, particularly in flood forecasting system implementation across South Korea and Mexico.

Seung Eock KimView profile

Professor

• Structural Engineering
• Nonlinear Inelastic Analysis
• LRFD Design
• +3 more

Seung Eock Kim is a Professor in the Department of Civil and Environmental Engineering at Sejong University, Korea, where he has served since 1997. Previously, he held executive leadership as Senior Vice President (2015-2018) and brings industry experience from Daewoo Engineering. His academic credentials include a Ph.D. from Purdue University (1996), M.S. from KAIST (1990), and B.S. from Yonsei University (1983). Kim leads research in structural systems optimization with emphases on: Nonlinear inelastic analysis of steel/composite structures AI-driven structural design methodologies LRFD (Load and Resistance Factor Design) frameworks Advanced computational mechanics for infrastructure His recent publications (2024-2025) demonstrate strong focus on machine learning applications for structural health monitoring, nano-scale material characterization of steels, and sensor-based corrosion detection. This represents a strategic expansion into intelligent infrastructure systems beyond traditional mechanics. Awards and honors: National Research Laboratory designation (Ministry of Science, 2000) Elected Full Member of Korean Academy of Science and Technology (2011) He directs the Steel Structure Laboratory , where he developed the specialized nonlinear analysis software 3D-PAAP. His research has generated 132 SCIE-indexed publications with 1,599+ citations, including the influential CRC Press book LRFD Steel Design Using Advanced Analysis (1997).

• Air Pollution Control
• Odor Treatment Technologies
• Volatile Organic Compounds (VOCs) Removal
• +7 more

Professor Ji Hyeon Song is a distinguished researcher in the Department of Civil and Environmental Engineering at Sejong University, specializing in air pollution control and environmental engineering. With a Ph.D. from the University of Texas at Austin and extensive research experience, she has established herself as a leading expert in odor treatment technologies and VOCs removal. Her educational background includes: Ph.D. in Environmental Engineering, University of Texas at Austin (2001) M.S. in Environmental Engineering, Seoul National University (1993) B.S. in Environmental Engineering, Seoul National University (1991) Professor Song's research focuses on innovative solutions for air pollution challenges, particularly in biological treatments of air pollutants using microorganisms, advanced oxidation processes including catalytic ozone oxidation and electrochemical oxidation, and combined systems for air pollution control. Her work bridges fundamental science with practical applications for VOCs and odor control technologies. Her research has significant implications for environmental sustainability and public health. An analysis of her recent publications reveals a strong focus on catalytic oxidation processes for VOC removal, hydrogen sulfide treatment in wastewater systems, and innovative combined approaches for simultaneous pollutant removal. Her work consistently emphasizes practical engineering solutions that can be implemented in real-world environmental systems. Professor Song has maintained an active research program with consistent publication output over more than two decades, demonstrating sustained scholarly productivity and impact in her field. Her research group develops and tests various technologies including electrochemical oxidation systems, catalytic ozone processes, and biofiltration methods for air and water treatment applications. Current projects appear to be focused on optimizing catalyst systems for room-temperature pollutant removal and developing integrated approaches for simultaneous treatment of multiple contaminants.

Suyong LeeView profile

Professor

• Artificial intelligence for food systems
• Alternative food processing
• Food Texture Design
• +5 more

Suyong Lee is a Professor in the Department of Food Science and Biotechnology at Sejong University, leading research at the Carbohydrate Bioproduct Research Center. His work bridges food science, artificial intelligence, and advanced processing technologies to develop innovative food systems. His research focuses on Artificial intelligence for food systems , Alternative food processing , and Food Texture Design , with particular emphasis on hydrocolloids, oleogels, and plant-based analogues. His laboratory specializes in rheo-processing technologies that integrate machine learning with hyperspectral imaging for non-destructive food analysis. Analysis of his recent publications reveals strong trends in AI-driven food characterization, with 60% of his 2023-2025 work applying machine learning to predict food properties. His research spans from fundamental carbohydrate chemistry to applied product development, particularly in sugar reduction, fat replacement, and gluten-free systems. Over 130 peer-reviewed research papers More than 30 patent applications h-index of 47 with 6548 citations He actively supervises research in food texture engineering and maintains strong industry collaborations, particularly in developing plant-based meat and dairy alternatives using hydrocolloid-based technologies. His laboratory operates cutting-edge facilities for rheological analysis, hyperspectral imaging, and AI modeling of food systems.

• Textile Engineering
• Smart Textiles
• Electronic Textiles
• +7 more

André Catarino is an Assistant Professor in the Department of Textile Engineering at the University of Minho, Portugal, and Deputy Director of the 2C2T – Center for Textile Science and Technology since 2022. He is an integrated researcher at the center, with a strong focus on interdisciplinary research at the intersection of textiles, electronics, and materials science. Education: Postgraduate Specialization in Digital Business, University of Porto, Porto Business School (2020–2021) Ph.D. in Textile Engineering, University of Minho (2005) M.Sc. in Textile Engineering, University of Minho (1998) B.Sc. in Electrical and Computer Engineering, University of Porto (1992) Research Interests: André Catarino's research spans a wide range of domains, including smart and electronic textiles , wearable sensor systems , materials engineering , and functional textiles for health and sports . His recent work also delves into digital marketing and the application of artificial intelligence in textile systems. His expertise encompasses electronics, instrumentation, programming, fabric manufacturing, and textile characterization. He has led or participated in over 25 national and international research projects , including EU-funded initiatives like BE@T, GreenAuto, and Fashion Alive. His work has resulted in 4 Portuguese patents and 1 European patent , alongside numerous prototypes and technology transfers. Publications and Impact: With over 115 scientific publications , including journal articles, book chapters, and conference proceedings, his research output is both broad and impactful. His recent publications focus on smart vests for posture monitoring, textile-based EMG electrodes, and consumer behavior in fashion marketing. Student Supervision: He has supervised or co-supervised more than 45 master’s and doctoral dissertations , covering topics from wearable health monitoring systems to sustainable fashion design and digital marketing strategies. Labs and Teams: As Deputy Director of the 2C2T – Center for Textile Science and Technology , he leads a multidisciplinary team of researchers and engineers. The center is a hub for innovation in textile science, with a strong emphasis on integrating electronics, sustainability, and human-centered design into textile applications.

Deepak R MishraView profile

Professor

• Remote Sensing
• Geospatial Technologies
• Coastal Ecosystems Monitoring
• +7 more

Deepak R Mishra is the Merle C. Prunty, Jr. Professor of Geography at the University of Georgia, where he serves as Professor and Head of the Department of Geography. He directs both the Center for Geospatial Research (CGR) and the UGA Small Satellite Research Laboratory (SSRL), demonstrating leadership across multiple significant research initiatives. His academic career spans geospatial science, remote sensing applications, and environmental monitoring with particular focus on coastal ecosystems. Dr. Mishra earned his PhD in Natural Resources from the University of Nebraska, Lincoln in 2006 and completed his M. Tech in Civil Engineering at the Indian Institute of Technology, Kanpur in 2002. His research focuses on combining field-based remote sensing with satellite technologies to monitor and study coastal and inland water resources. His work addresses critical environmental challenges including harmful algal blooms, salt marsh conservation, carbon sequestration in tidal wetlands, and sea level rise impacts. Dr. Mishra's research portfolio reveals strong trends in geospatial analytics for environmental monitoring, with increasing integration of artificial intelligence and small satellite technologies. His recent publications show a growing emphasis on climate change impacts on coastal ecosystems, particularly salt marsh vulnerability and carbon sequestration capacity. The work demonstrates innovative applications of remote sensing for tracking cyanobacterial blooms and developing early warning systems through platforms like CyanoTRACKER. Outstanding Service Award, SEDAAG 2019 Creative Research Medal, University of Georgia, 2017 Best Poster Award, TROPMET 2016, India Article ranked #4 in Altmetric Attention Score in Nature Climate Change 2016 Mississippi State University Faculty Research Award (2012) GRI Academic Faculty of the year (2011) Dr. Mishra has secured substantial research funding, including a $7.5 million NSF LTER grant and a $4.7 million Army Research Lab grant for autonomous navigation systems. His lab actively mentors graduate students including Tyler Lynn, Lishen Mao, and Chintan Maniyar, who contribute to projects spanning coastal monitoring, small satellite development, and AI applications. The Small Satellite Research Laboratory recently achieved a historic milestone with the launch of SPOC satellite to the International Space Station, marking UGA's first satellite deployment.

Saikat DuttaView profile

Assistant Professor

• Software Engineering
• Machine Learning
• Artificial Intelligence
• +5 more

Saikat Dutta is an Assistant Professor in the Department of Computer Science at Cornell University. He is affiliated with the Software Engineering Group and focuses on the intersection of Software Engineering and Machine Learning . His work aims to enhance the reliability of ML-based systems while applying ML techniques to solve software engineering challenges. PhD in Computer Science from University of Illinois Urbana-Champaign (Summer 2023) Postdoctoral Researcher at University of Pennsylvania Bachelor's in Computer Science and Engineering from Jadavpur University Research Interests: Dr. Dutta's research spans several key areas: Automated test generation and debugging for ML/DL libraries Using AI/ML for automated software engineering tasks Improving performance of regression tests in ML libraries Static and dynamic analysis for probabilistic programming Article Trends: His recent publications emphasize: Automated testing of ML systems Security vulnerability detection using LLMs Probabilistic program analysis Neurosymbolic learning frameworks Flaky test management in stochastic environments Stochastic regression test optimization Scientific Awards: Meta AI LLM Evaluation Research Grant (2025) Mavis Future Faculty Fellowship (2022-23) Facebook PhD Fellowship (2020-22) 3M Foundation Fellowship (2019-2020) Advising & Grants: Dr. Dutta actively recruits PhD students and postdocs. He leads research projects supported by grants from Meta AI and participates in program committees for top conferences like ICSE and ISSTA. His lab focuses on neurosymbolic systems and ML-based software verification.

Benjamin RicaudView profile

Associate Professor

• Machine Learning
• Graph Signal Processing
• Explainable AI
• +3 more

Benjamin Ricaud is an Associate Professor and Group Leader in Machine Learning at UiT The Arctic University of Norway's Department of Physics and Technology. His core affiliations include membership in the Machine Learning Group, Visual Intelligence center, and co-directorship of the Digital Technology Innovation Lab focused on Arctic-region tech startups. He also co-chairs the annual Northern Light Deep Learning conference. Ricaud's research spans: Fundamental ML : Graph signal processing, explainable AI, and generative models Applications : Microfossil classification, medical diagnostics (retinal aging), drug analysis, and climate data interpretation Emerging domains : Self-supervised learning and biological data analysis using Raman spectroscopy His recent publications (2020-2025) cluster in three domains: Graph ML methodologies (35%) Biomedical/biological applications (40%) Geoscience/climate informatics (25%) with consistent focus on interpretability and real-world data challenges. Teaching includes Image Processing (FYS-2010), Pattern Recognition (FYS-3012), and Machine Learning (FYS-2021). He leads outreach initiatives developing AI exhibits for Tromsø Science Centre.

• Neural Networks
• Genetic Algorithms
• System Identification and Control
• +7 more

FURUZUKI, Takayuki is a Professor at Waseda University's Faculty of Science and Engineering, Graduate School of Information, Production, and Systems. He holds a PhD from Kyushu Institute of Technology and maintains the NCLab research group (http://nclab.w.waseda.jp/nclab/). His professional memberships include the Institute of Electronics, Information and Communication Engineers, Institute of Electrical Engineers of Japan, Society of Instrument and Control Engineers, and IEEE. His educational background includes a PhD in Information Science from Kyushu Institute of Technology (1994-1997), a Master's degree in Electronics Engineering from Sun Yat-Sen University (1983-1986), and a Bachelor's degree in Electrical & Electronic Systems Engineering from Sun Yat-Sen University (1979-1983). Professor FURUZUKI's research spans neural networks, genetic algorithms, system identification and control, complex systems, bioinformatics, and combinatorial optimization. His work integrates soft computing techniques with medical informatics and control systems engineering, developing innovative approaches for problems ranging from brain tumor segmentation to music information retrieval. His research methodology often combines theoretical foundations with practical applications in healthcare, energy systems, and intelligent transportation. His recent publication record shows a strong focus on sequential recommendation systems, graph neural networks for medical imaging, music information retrieval, and power systems analysis. The consistent thread across his work is the application of advanced machine learning techniques to solve complex, real-world problems across diverse domains, with particular emphasis on handling missing data, improving model efficiency, and enhancing prediction accuracy. His scientific achievements have been recognized with several prestigious awards: ISCIIA2008 Excellent Paper Award (2008) Institute of Electrical Engineers of Japan Excellent Paper Award (2001) Guangdong Province Higher Education Science and Technology Progress Second Prize (1991) Guangdong Province Higher Education Science and Technology Progress Second Prize (1989) Chinese Ministry of Education Scientific and Technological Achievements Second Prize (1986) Professor FURUZUKI has maintained continuous research activity since joining Waseda University in 2003, with significant contributions to multiple research projects spanning neural computation, soft computing, and system engineering. His work demonstrates strong international collaboration, with publications involving researchers from various institutions worldwide. His research output includes over 410 papers with 3,623 citations and an h-index of 23 according to Scopus data. The NCLab research group, which he leads, focuses on neural computation and related areas, providing a platform for interdisciplinary research that bridges theoretical foundations with practical applications in healthcare, energy systems, and intelligent transportation. His laboratory environment fosters innovation in machine learning algorithms and their application to real-world problems, with particular emphasis on developing efficient, robust solutions for complex data analysis tasks.

Bryce WestlakeView profile

Associate Professor

• Digital Forensics
• Biometric Identification
• Child Sexual Abuse Material
• +4 more

Bryce Westlake is an Associate Professor in the Department of Justice Studies within the College of Social Sciences at San Jose State University. He is a leading researcher in digital forensics and child sexual abuse material detection, with significant contributions to both forensic science education and alternative sexuality studies. Education: Ph.D. in Criminology from Simon Fraser University (2015) Master's degree in Criminology from Simon Fraser University Bachelor of Arts degree in Psychology and Sociology (double major) from University of British Columbia Dr. Westlake's research spans two primary areas with significant societal impact. In digital forensics, he focuses on developing automated tools to detect, collect, analyze, and match child sexual abuse material disseminated online. His work involves international collaboration with researchers, law enforcement agencies, and government partnerships to create more effective detection systems. In his secondary research area, he explores alternative sexuality, particularly BDSM communities, conducting multi-phasic, kink-positive studies examining health and safety within these communities. His research aims to destigmatize participation through a deeper understanding of the social and emotional enrichment practitioners receive from activities. His recent publications demonstrate a clear trend toward increasingly sophisticated technical approaches to combating child sexual exploitation while simultaneously advancing understanding of alternative sexual practices. The technical publications focus on biometric identification, file structure analysis, and ethical web scraping methods, while his BDSM-related work emphasizes community safety, education pathways, and mental health benefits. This dual focus positions him uniquely at the intersection of technology, law enforcement, and human sexuality research. Scientific Awards: The Storytellers Award (Social Sciences and Humanities Research Council) - April 2014 Canadian Graduate Scholarship (Social Science and Humanities Research Council) - May 2012 Dr. Westlake has been heavily involved in developing the forensic science program at SJSU, creating six undergraduate courses, revising two graduate courses, and introducing one graduate course. In Fall 2020, he created and implemented a new concentration in digital evidence (computer forensics) for forensic science majors - one of the first in-person digital forensic bachelor of science degrees in the United States meeting FEPAC standards. He has developed and directs the Silicon Valley Digital Forensics Laboratory, which began accepting students for internships in Fall 2024. He was awarded a three-year $497,948 grant from the National Science Foundation in 2023 to study 'Training digital forensics examiners through hands-on education investigating live criminal investigations.' Through the Silicon Valley Digital Forensics Laboratory and partnerships with criminal justice agencies (district attorneys offices, law enforcement agencies, etc.), Dr. Westlake provides students with training and practical experience conducting digital forensic investigations from start (evidence collection) to finish (report writing and testimony). He also co-hosted the first annual Child Sexual Abuse Reduction Research Network workshop in Adelaide Australia in December 2023.

Lotty HooftView profile

Professor

• Evidence-Based Medicine
• Systematic Reviews
• Diagnostic Test Accuracy
• +3 more

Lotty Hooft is a Full Professor at Utrecht University, affiliated with the University Medical Center Utrecht (UMC Utrecht), where she contributes to strategic research programs in Child Health and Methodology development. She holds key external roles as a member of the independent advisory committee for the Advenzo funding scheme at Zorginstituut and the Cochrane Council and Methods Groups for Prognosis, Screening, and Diagnostic Tests. Her research focuses on Evidence-Based Medicine, specializing in Systematic Reviews and Diagnostic Test Accuracy, with clinical applications in Paediatric and Perinatal Medicine. She investigates methodological challenges such as bias in diagnostic studies using expert panels, stakeholder engagement in paediatric trial reporting, and neonatal outcomes in preterm infants. Her work bridges rigorous methodology with real-world clinical impact across diverse medical domains. Analysis of her 2025 publications reveals a cohesive trajectory in advancing diagnostic methodology—particularly in reference standard development and bias mitigation—while expanding into patient-centered paediatric research and neonatal care. Her contributions to sleep medicine diagnostics and workforce well-being further demonstrate cross-disciplinary relevance in improving healthcare systems and clinical practice. No scientific awards were documented in the provided materials. Professor Hooft actively shapes research funding through her Advenzo committee role, evaluating project proposals and subsidy applications, though specific grant awards or student mentorship details remain unreported. Her Cochrane involvement underscores leadership in global evidence synthesis standards, yet no laboratory or dedicated research team structure is specified in the current data.

Martin ScanlonView profile

Professor

• Food Science
• Food Processing
• Plant Material Science
• +3 more

Dr. Martin Scanlon is a Professor and Dean of the Faculty of Agricultural and Food Sciences at the University of Manitoba. His work focuses on physical and structural changes in plant materials during food processing, particularly in oilseed-based systems and cereal products. Education: Operative Miller Certificate (with Distinction), City & Guilds (London), England PhD (Food Science), University of Leeds, England BSc Hons (Food Science), University of Leeds, England His research spans modeling process-ingredient interactions, aerated food materials, ultrasonic analysis, and grain-legume science. Recent projects include novel canola oil extraction methods and mitigating acrylamide precursors in wheat. Analysis of his publications reveals expertise in sustainable processing (supercritical CO₂, microemulsions), dough rheology, antioxidant recovery, and bubble dynamics in cereal systems. No scientific awards are explicitly mentioned. Dr. Scanlon is not currently accepting graduate students and has not disclosed specific grant funding or lab affiliations in the provided texts.

• Wireless Communications
• Machine Learning
• Digital Twins
• +5 more

Pierluigi Salvo Rossi is a Professor at the Department of Electronic Systems , Norwegian University of Science and Technology ( NTNU ), with additional roles as Deputy Head of Department (since 2021) and Deputy Manager at the Center for Green Shift in the Built Environment (since 2022). He also serves as a part-time Research Scientist at SINTEF Energy's Gas Technology department. Education: Ph.D. in Computer Engineering, University of Naples “Federico II”, Italy (2005) Dr.Eng. (cum laude) in Telecommunications Engineering, University of Naples “Federico II”, Italy (2002) Research Interests span Wireless Communications , Digital Twins , Machine Learning , and Statistical Signal Processing , focusing on applications like Industrial IoT , Fault Detection , and Energy Systems . His recent Publications highlight trends in Federated Learning , Graph Signal Processing , and Multi-Sensor Anomaly Detection across domains from Natural Gas Pipelines to Subsea Leakages . Scientific Awards include: Exemplary Senior Editor, IEEE Communications Letters (2018) Department Ambassador, NTNU (2016) IEEE Senior Member (since 2011) Professional Roles encompass editorial leadership (e.g., IEEE Sensors Journal) and conference organization (e.g., General Chair for IEEE Sensor Array and Multichannel Signal Processing Workshop, 2022). He leads major funded research projects like PREFERENCE (RCN, 2023-2027) and AUTOSHIP (RCN, 2020-2028).

Imraan FaruqueView profile

Associate Professor

• Biologically-Inspired Flight Control
• Engineered Aerial Autonomy
• Unmanned Aerial Vehicles
• +2 more

Imraan Faruque is an Associate Professor in the Department of Mechanical and Aerospace Engineering at Oklahoma State University (OSU), part of the College of Engineering, Architecture and Technology (CEAT). His research focuses on biologically-inspired flight control systems, engineered autonomy for unmanned aerial vehicles (UAVs), and the integration of sensory feedback mechanisms in autonomous systems. Education: Faruque holds a Ph.D. and M.S. in Aerospace Engineering from the University of Maryland (2011 and 2010) and a B.S. in Aerospace Engineering from Virginia Tech (2006). Research Interests: His work emphasizes bio-inspired solutions for aerial autonomy, including swarm coordination, gust-aware flight control, and human-autonomy interaction. Key areas include unmanned systems design, visual feedback algorithms, and adaptive control strategies derived from insect flight dynamics. Awards: He has received notable accolades such as the ONR Young Investigator Award (2019), AIAA Hal Andrews Young Engineer/Scientist Award (2017), and multiple 'Best in Session' recognitions at major conferences. His team also secured 1st Place in the International Aerial Robotics Championship (2005). Publications: Faruque’s research spans topics like orbital debris management, swarm intelligence, and tornado sensing with UAVs. His work bridges biological principles and engineering, with applications in aerospace, robotics, and environmental monitoring.

• Mathematical Statistics
• Applied Statistics
• Probability Theory
• +6 more

Holger Dette is a Professor and Chair Holder of Stochastics (specializing in Statistics) at the Faculty of Mathematics, Ruhr University Bochum. He leads the prominent Group Dette within the Institute of Statistics, overseeing a team of researchers, doctoral students, and administrative staff including Birgit Tormöhlen as team assistant. His research group is deeply integrated within the university's mathematical ecosystem, collaborating with other research groups across algebra, analysis, numerics, and topology. Dette's research spans mathematical statistics with strong applications in real-world problems. His primary interests include optimal experimental design, time series analysis, functional data, change point problems, nonparametric regression, biostatistics, special functions, goodness-of-fit tests, and random matrices . His work bridges theoretical statistics with practical applications, particularly evident in his collaborations with pharmaceutical giants Novartis and Bayer AG in biostatistics, as well as Quasol, a spin-off company from his statistics institute. His recent publications (2024-2025) reveal a research program increasingly focused on high-dimensional and functional data analysis, privacy-preserving statistics, and novel methodological approaches to longstanding statistical problems. Dette's work shows strong interdisciplinary connections, particularly with biomechanics (analyzing joint angles during fatigue phases) and data science (addressing challenges in the era of big data). His research group is actively involved in multiple DFG-funded projects including the newly established 'Small Data' collaborative research center (Sonderforschungsbereich 1597) and the Spatio-temporal Statistics for the Transition of Energy and Transport (Transregio 391). Dette has received significant recognition including the prestigious Humboldt Research Award . His paper 'With Great Power Come Great Side Channels: Statistical Timing Side-Channel Analyses with Bounded Type-1 Errors' achieved second place at the CSAW'24 Applied Research Competition MENA. His research group has also secured multiple significant funding awards from the German Research Foundation (DFG). As an advisor, Dette supervises numerous doctoral and master's students including Pascal Quanz, Marius Kroll, and Carina Graw. His group offers statistical consulting services for scientists and students across bachelor's, master's, and doctoral phases. The group maintains strong industrial partnerships, particularly in biostatistics applications, demonstrating Dette's commitment to translating theoretical statistics into practical solutions for real-world challenges.