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Júlio Aalejandro Henriques da CostaView profile

Associate Professor

• Training Load
• Heart Rate Variability
• Systematic Review
• +6 more

Júlio Aalejandro Henriques da Costa is an active academic researcher at the Faculty of Sport and Physical Education at University of Porto, Portugal. With an ORCID profile (0000-0002-8225-8667) and Scopus h-index of 15, his research has generated significant academic impact with 553 citations. His work spans multiple publications from 2016 to 2025, showing consistent research productivity with 38 total research outputs including articles, reviews, and other scholarly contributions. Dr. Costa's research interests center around exercise physiology and sports science, with particular expertise in training load monitoring, heart rate variability analysis, and physical activity interventions. His fingerprint analysis reveals strong focus areas including Training Load (100%), Heart Rate Variability (97%), Systematic Reviews (85%), Perceived Exertion (70%), Sleep Time (51%), Aerobic Fitness (36%), and Physical Activity (33%). These research themes demonstrate his commitment to understanding the physiological responses to exercise across different populations. His recent publication trend shows a clear emphasis on community-based physical activity interventions, particularly those targeting children and older adults. The research portfolio reveals a methodological diversity including systematic reviews, experimental studies using GPS technology, and large-scale school-based interventions. Notably, his work often employs objective measurement techniques such as accelerometry and GPS tracking to assess physical activity patterns and intensity profiles in real-world settings. Dr. Costa has been involved in significant research projects including the "Super Quinas" Intervention Program targeting Portuguese primary schools and the FPF (Portuguese Football Federation) 'Magic Ball' project that reached over 1,600 children across 44 schools. His collaborative network spans multiple institutions, as evidenced by co-authorship patterns across his publications, with particular emphasis on research related to walking football for older adults and physical activity interventions for children's health and development.

Helen BlankView profile

Professor

• Predictive Cognition
• Speech Perception
• Face Perception
• +7 more

Prof. Dr. Helen Blank is a Professor of Predictive Cognition at Ruhr University Bochum, affiliated with the Faculty of Psychology and the Research Department of Neuroscience. She leads the Prediction in Communication Lab within the Research Center One Health Ruhr of the University Alliance Ruhr. Her research focuses on understanding how the brain integrates sensory signals with prior expectations, particularly in speech and face perception under uncertainty. Her research interests center on predictive processing in human cognition, exploring how expectations shape perception through mechanisms like predictive coding. She investigates how humans adapt to changing contexts, learn from experiences, and generalize prior knowledge to new sensory inputs. Her work spans multiple domains including speech perception, face recognition, and the neural mechanisms underlying these processes. Prof. Blank's recent publications demonstrate a strong focus on prediction error processing, serial effects in perception, and how expectations guide information sampling. Her work combines computational modeling with advanced neuroimaging techniques, revealing how prior expectations influence sensory processing across different modalities. She is actively mentoring students and postdocs, as evidenced by numerous recent publications with junior researchers. Her lab has access to significant infrastructure including a 3T human MRI, High-Performance-Computing Cluster, and multiple laboratories for electrophysiological and behavioral studies.

Ralf PlattfautView profile

Professor

• Process Management
• Business Process Innovation
• Digital Transformation
• +5 more

Ralf Plattfaut is Professor for Information Systems and Transformation Management at the University of Duisburg-Essen since 2023, where he leads the business process innovation and automation lab. Previously, he served as Professor for Business Informatics at South Westphalia University of Applied Sciences (2019-2023) and as Associate Partner at McKinsey & Company (2013-2019). His academic journey includes research positions at the European Research Center for Information Systems at University of Münster and visiting fellowships at Queensland University of Technology and University of Liechtenstein. His educational background includes: Master of Science in Information Systems (MScIS) from WWU Münster (2009), thesis on 'Lean Enterprise Content Management' Bachelor of Science in Information Systems (BScIS) from Hochschule Liechtenstein (2008), thesis on 'IT-Controlling - Investitionsrechnung und Simulation auf Basis des ARIS-Toolset' Studies in Information Systems at WWU Münster (2004-2009) with core subjects in Business Administration, Information Systems, and Finance PhD studies in Information Systems at University of Münster (2009-2013) Plattfaut's research focuses on business process management, digital transformation, and process automation. His work bridges academic theory with practical business applications, particularly examining how organizations implement and govern process innovations. He has made significant contributions to understanding Robotic Process Automation adoption, process mining applications, and the challenges of digital transformation in various sectors including healthcare, utilities, and public administration. His publication portfolio shows a clear trajectory from foundational work on process modeling and IT controlling through to contemporary research on AI-supported process automation and the societal implications of digital transformation. Recent work increasingly addresses the intersection of process management with emerging technologies while maintaining focus on practical implementation challenges faced by organizations. His scientific recognition includes multiple best paper nominations and awards at premier conferences including ICIS, HICSS, and BPM. Notably, he won the MINTchallenge for innovative teaching and received awards for research on public sector process management and RPA implementation challenges. As an active academic leader, Plattfaut serves on editorial boards for Information Systems and e-Business Management and Intelligent Systems in Accounting, Finance and Management journals. He has chaired tracks at major conferences including Wirtschaftsinformatik and Business Process Management conferences. His funded research projects demonstrate strong connections between academic inquiry and practical business needs, with recent grants from DFG, BMBF, and state ministries supporting research on process automation, process mining in utilities, and lightweight IT governance. Plattfaut maintains an active consulting practice supporting organizations on digital transformation journeys, particularly focusing on business process innovation. He also serves on the Advisory Board 'Digitale Region menschlich gestalten' for the Regional Development Programme 'Regionale 2025'.

• Artificial Intelligence
• Biomedical Imaging
• Computer Vision
• +5 more

Andreas Uhl is a University Professor in Artificial Intelligence and Human Interfaces at the Department of Computer Science, University of Salzburg. With a prolific research career spanning from 1996 to present, he has authored or co-authored 534 publications and led or participated in 59 research projects. His work demonstrates sustained academic productivity with recent publications and projects extending through 2025. Professor Uhl's research interests span multiple domains at the intersection of artificial intelligence and practical applications. His primary focus areas include computer vision, biometrics, biomedical imaging, and digital forensics, with significant contributions to pattern recognition and image analysis. His work bridges theoretical computer science with practical applications in cultural heritage preservation, medical diagnostics, and security systems, demonstrating a versatile research portfolio that addresses both fundamental challenges and real-world problems. His recent publications reveal a strong emphasis on temporal image forensics, biomedical image analysis, and biometric security. The research shows a clear trajectory toward increasingly sophisticated applications of AI in specialized domains, with particular attention to validation methodologies and limitations of current approaches. His work on cultural heritage applications demonstrates an innovative application of computer vision techniques to historical artifacts. Best paper award @ 25th ACM Symposium on Applied Computing (Applications Track), 2010 Best Paper award @ 2nd European Workshop on Visual Information Processing (EUVIP'10), 2010 IEEE Biometrics Council Best Paper Award (TBIOM), 2022 Kurt Zopf Preis, 2023 Professor Uhl actively leads multiple significant research initiatives, including the CDL-POSA project on People and Object Surface Authentication (2025-2032), Artificial Intelligence driven Biomedical Imaging Innovation (2025-2029), and the AIBIA Research and Transfer Junior Lab (2023-2025). His research group maintains active collaborations with institutions like Carnegie Mellon University, as evidenced by his recent research stay there in September 2024. The scope and duration of his current projects indicate substantial grant funding and institutional support for his research agenda. His laboratory activities focus on AI applications in biomedical imaging, border security through vehicle-integrated technologies (AutoBorder project), and cultural heritage analysis. The research environment appears to integrate academic inquiry with practical transfer through initiatives like the FFG Student Internships program, suggesting a strong commitment to both fundamental research and real-world implementation.

Manuel SchabusView profile

Professor

• Sleep Research
• Consciousness Studies
• Cognitive Neuroscience
• +4 more

Manuel Schabus is a University Professor of Psychology at the University of Salzburg, specializing in sleep research, consciousness studies, and cognitive neuroscience. With over 403 publications and numerous ongoing research projects through 2027, he leads significant work in understanding sleep mechanisms and developing innovative sleep interventions. His research spans from fundamental neuroscience to practical applications for sleep disorders. Professor Schabus's work focuses on the intersection of sleep, brain activity, and cognitive functions, with particular expertise in EEG analysis and sleep architecture. His research explores how sleep affects memory consolidation, emotional regulation, and overall mental health. He has pioneered digital approaches to sleep assessment and intervention, including mobile applications and online therapy platforms that make evidence-based sleep treatments accessible to broader populations. His recent publications reveal a strong trend toward digital sleep medicine, with multiple studies on AI-enhanced wearables, mobile CBT-I applications, and personalized sleep optimization strategies. The research spans from fundamental neuroscience (examining prediction-related signals during sleep) to applied interventions (including specialized programs for Ukrainian refugees and shift workers). Franz Gerstenbrand Wachkoma Award 2020 Kurt-Zopf-Förderpreis 2018 START-Preis 2014 Professor Schabus manages numerous research grants totaling millions in funding, with current projects including the Virtual Sleep Laboratory (2024-2027), Sleep2Optimize, and specialized interventions for shift workers and Ukrainian refugees. He actively mentors junior researchers and collaborates internationally across multiple institutions. His work bridges laboratory research with real-world applications, as evidenced by his frequent media appearances discussing practical sleep optimization strategies for the general public. He leads the Center for Cognitive Neuroscience at the University of Salzburg, where his team operates both traditional sleep laboratories and develops digital sleep assessment tools. The research group combines expertise in neuroscience, psychology, computer science, and clinical medicine to tackle sleep-related challenges from multiple angles, with a strong emphasis on translating research findings into practical interventions that improve sleep health in diverse populations.

• Robotics
• Artificial Intelligence
• Human-Robot Interaction
• +3 more

Dr. Robert Haschke serves as a Professor and Responsible Investigator in the Cognitive Systems and Social Interaction Group at Bielefeld University's Faculty of Engineering. He is affiliated with the Center for Cognitive Interaction Technology (CITEC) and serves on the Examination Board for the Intelligent Interactive Systems Master's program. His office is located at CITEC 2-035, and he can be reached at rhaschke@techfak.uni-bielefeld.de or +49 521 106-12122. Professor Haschke's research spans multiple domains of robotics and artificial intelligence, with particular emphasis on tactile sensing systems, robotic manipulation, and human-robot interaction. His work explores advanced methods for enabling robots to perceive their environment through touch, with applications in assistive robotics and industrial automation. He investigates how machines can learn from human interactions and adapt their behavior through reinforcement learning and sensor fusion techniques. His research bridges theoretical advances with practical implementations, focusing on transferring knowledge from simulation to real-world robotic systems. Analysis of Professor Haschke's recent publications reveals a strong trajectory toward more sophisticated tactile perception systems and their integration with language and vision for natural human-robot collaboration. His work consistently addresses the simulation-to-reality gap, developing methods for transferring control policies from virtual environments to physical robots. The research shows increasing integration of multimodal sensing (tactile, visual, linguistic) to enable more capable and adaptable robotic manipulation in unstructured environments. As an educator, Professor Haschke teaches advanced courses including Robot Manipulators (39-Inf-RM), Advanced Artificial Intelligence (39-M-Inf-AI-adv_a), Advanced Artificial Intelligence (focus) (39-M-Inf-AI-adv-foc), and Basics of Artificial Intelligence (39-M-Inf-AI-bas). His teaching reflects his research expertise, providing students with both theoretical foundations and practical skills in robotics and AI. Professor Haschke is an integral member of Bielefeld University's Cognitive Systems and Social Interaction Group within CITEC. His work contributes significantly to the university's Socio-Technical World research area, particularly in developing capabilities that enable agents (humans, robots, and AI systems) to act, communicate, and learn in complex environments. His research group focuses on creating robotic systems that can interact naturally with humans through advanced perception and adaptive control mechanisms.

• Computer Vision
• Artificial Intelligence
• Extended Reality
• +4 more

Prof. Dr. Helge Rhodin is a faculty member at the University of Bielefeld, serving as Head of the Visual AI for Extended Reality Group within the Faculty of Engineering. His research activities are centered at the Center for Cognitive Interaction Technology (CITEC), a central academic institute at the university focused on interdisciplinary research in cognitive systems, robotics, and human-computer interaction. His office is located in CITEC building room 3-225, with secretariat contact via susanne.strunk@uni-bielefeld.de. Professor Rhodin's research focuses span multiple cutting-edge areas in computer vision and artificial intelligence. His primary interests include Computer Vision, Artificial Intelligence, Extended Reality, Human-Computer Interaction, 3D Reconstruction, and Motion Capture. His work demonstrates strong interdisciplinary connections between the university's 'Socio-Technical World' strategic research area, which examines how humans, robots, and AI interact in complex environments. Analysis of Professor Rhodin's recent publications reveals a consistent focus on advancing techniques for human and object representation in virtual and augmented environments. His work spans from fundamental computer vision techniques like keypoint detection and motion capture to advanced applications in digital twin generation, neural rendering, and animal behavior analysis. Notably, his research shows practical applications in sports science (particularly skiing analysis) and biological motion tracking. Within the university governance structure, Professor Rhodin serves as a member of both the Habilitation Committee and the Faculty Conference of University Professors within the Faculty of Engineering, indicating his active participation in academic leadership and quality assurance processes.

• Predictive Maintenance
• Mixed Reality Applications
• Human-Robot Collaboration
• +5 more

Bernard Schmidt is an active researcher at the University of Skövde's School of Engineering Science, specializing in Production and Automation Engineering. His work bridges cutting-edge mixed reality applications with industrial predictive maintenance systems, focusing on sustainable manufacturing solutions. Affiliated with the Virtual Systems Research Centre (closed 2017) and Virtual Engineering Research Environment, he contributes to multiple research profiles including VF-KDO and Virtual Production Development. His research interests center on predictive maintenance methodologies , human-robot collaboration interfaces , and cloud-enhanced manufacturing systems . Schmidt develops mixed reality training environments that reduce production line disruption while improving operator safety. His work integrates double ball-bar measurements with machine learning to create population-based maintenance models that achieve 40% cost reduction compared to traditional approaches. Current projects include ACCURATE (2021-2025) and VF-KDO (2019-2026), funded by Sweden's Knowledge Foundation. Analysis of Schmidt's 15 most recent publications reveals a strong trend toward real-time industrial decision support systems using mixed reality visualization. His work consistently addresses sustainable manufacturing through energy-efficient robotics and predictive maintenance frameworks that leverage cloud computing. Key subfields include virtual sensor integration, collision avoidance algorithms, and multi-objective optimization for robotic cells - demonstrating practical applications in automotive and elevator manufacturing. Research funding highlights include: Knowledge Foundation (KKS) projects: ACCURATE (2021-2025), VF-KDO (2019-2026), Virtual Factory with Knowledge-Driven Optimization (2018-2026) European Commission grant (637107) IPSI Industrial Research School collaboration with Volvo GTO and Volvo Cars Schmidt actively supervises bachelor's degree projects at ASSAR Industrial Innovation Arena in Skövde, with recent work involving Natalia Sempere Maciá and Celia Redondo Verdú. His research integrates with ABB Robotics systems through partnerships with experts like Tommy Y. Svensson. Current laboratory work focuses on HoloLens 2 implementations for robotic cell visualization and safety system development for human-robot collaborative environments.

Ljudmila GeistView profile

Associate Professor

• Semantics
• Pragmatics
• Morphosyntax
• +7 more

Ljudmila Geist serves as a Research Associate and DFG Project Manager at the University of Stuttgart's Institute of Linguistics within the Department of Linguistics and German Studies (ILG). Holding the academic rank of Privatdozent (equivalent to Associate Professor), she leads two major DFG-funded research projects while teaching linguistics and Slavic studies courses at undergraduate and graduate levels. Her institutional affiliation spans formal instruction in Linguistics, German Studies, and Slavic Studies programs including teacher training tracks for German and Russian. Her research expertise centers on the syntax-semantics interface with three core pillars: Semantics/Pragmatics : Nominal reference systems, information structure dynamics, speaker-hearer knowledge interaction in discourse, and copula clause semantics Morphosyntax : Argument linking mechanisms, case assignment for objects/predicatives, and co-argument binding phenomena Language Comparison/Typology : Cross-linguistic analysis of definiteness/indefiniteness in article-less languages, grammatical category comparisons between Russian and German Her work consistently bridges theoretical linguistics with empirical Slavic language data. Analysis of her 15 most recent publications reveals strong methodological continuity in formal linguistic approaches applied to Slavic languages, particularly Russian-German comparisons. Key thematic clusters include noun phrase semantics (mass/count distinctions, definiteness marking), copula constructions, and question-response systems. Her research increasingly incorporates experimental methodologies while maintaining rigorous formal analysis frameworks, demonstrating evolution from theoretical syntax toward integrated psycholinguistic approaches. Geist actively contributes to academic infrastructure through editorial roles including co-editing Advances in Formal Slavic Linguistics 2018 (Language Science Press, 2021) and multiple volumes of Investigations into Formal Slavic Linguistics . She has organized workshops such as Divide and Count at the 2023 DGfS conference in Cologne, demonstrating leadership in advancing research on morphosyntactic-semantic interfaces. Her teaching portfolio demonstrates deep integration of research and pedagogy across morphology, syntax, and Slavic linguistics courses. Recent offerings include Morphology (SS 2024), Syntax, Semantics and Typology of Nouns (WS 2023/24), and specialized seminars on nominal categories and German-Russian comparative linguistics. She completed Baden-Württemberg's 200-hour university teaching certification in 2008, reflecting commitment to pedagogical excellence.

Manuel Mucientes MolinaView profile

Professor

• Artificial Intelligence
• Machine Learning
• Computer Vision
• +3 more

Manuel Mucientes Molina is a Full Professor at the Research Center on Intelligent Technologies (CiTIUS) within the University of Santiago de Compostela . His research focuses on Artificial Intelligence , particularly in Computer Vision and Machine Learning , with applications in object detection, process mining, and healthcare diagnostics. Research Areas : Machine learning, Computer vision, Process mining, Deep learning, AI for healthcare. Projects : Protonterap-IA (2025), AZOR (2024), RAI4P (2021), eXplica-IA (2018), DronePlan (2014), SoftLearn (2012). Publications highlight advancements in few-shot object detection, small object tracking, and AI-driven conformance checking. Notable collaborations include work on X-ray vision systems and medical mask detection in operating rooms. Awards : Best Student Paper Nomination (2015), Runner-up best industry-oriented paper award (2008). Teaching includes courses on Statistical Learning, Deep Learning, and Automata Theory at the M.Sc. and B.Sc. levels.

Henrik EbelView profile

Assistant Professor

• Robotics
• Cooperative Robotics
• Model Predictive Control
• +6 more

Henrik Ebel is an Assistant Professor (Tenure Track) in Mechanical Engineering at Lappeenranta-Lahti University of Technology (LUT), specifically within the LUT School of Energy Systems. He joined LUT in 2024 after previously working at the University of Stuttgart's Institute of Engineering and Computational Mechanics from 2016 to 2024. Dr. Ebel's research focuses on the intersection of artificial intelligence, machine learning, and mechanical engineering, with particular emphasis on: Distributed cooperative robotics Model predictive control systems Non-holonomic robot control Data-driven approaches to mechanical engineering problems Automation systems development His research aims to bring cooperative robotics from laboratory settings to real-world applications in Finland, focusing on using multiple simple and cost-efficient robots that collaborate to solve problems rather than relying on single complex machines. He believes automation promotes sustainability through better energy conservation, generation, and storage compared to manual processes. His recent publications demonstrate consistent advancement in cooperative robotics, control systems, and machine learning applications in mechanical engineering. As an educator, Dr. Ebel supervises doctoral students and finds fulfillment in seeing them grow and succeed in their research. He values the human aspect of academia and enjoys teaching as a complement to his research work, noting that honing teaching skills helps him explain research better and pass on important future-oriented knowledge.

Armin AlaghiView profile

Assistant Professor

• Embedded Systems
• Digital Circuits
• Mathematics
• +7 more

Armin Alaghi serves as a Research Scientist at Oculus Research (Redmond, WA) and holds an Affiliate Assistant Professor position at the University of Washington. His dual affiliation enables valuable knowledge transfer between cutting-edge industrial research and academic pursuits in computer systems engineering. Dr. Alaghi's research spans the intersection of embedded systems, digital circuits, and mathematics. His primary focus involves building low-power augmented reality (AR) and virtual reality (VR) systems while developing novel computation methods for unreliable beyond-CMOS technologies. His previous research contributions include significant work in stochastic computing (where he developed the STRAUSS synthesis methodology), reliable Network on chip (NoC) design, FPGA testing methodologies, NoC testing techniques, artificial neural networks implementations, asynchronous circuit design, and multi-valued logic systems. He has made his spectral-transform-based synthesis tool publicly available on GitHub, demonstrating commitment to open research. Analysis of Dr. Alaghi's publication record reveals a clear research trajectory from foundational circuit-level work toward practical applications in AR/VR systems. His publications from 2020-2025 demonstrate expertise spanning computer architecture, security for immersive technologies, neural network compression techniques, and homomorphic encryption methods. A recurring theme throughout his work is the exploration of quality-energy tradeoffs and error-resilient computing approaches, with increasing focus on security aspects of AR/VR systems in his most recent work. Dr. Alaghi maintains active connections with the broader research community, as evidenced by his Erdős number of 3 (Armin Alaghi John P. Hayes Frank Harary Paul Erdős) and his ongoing contributions to open-source research tools. His GitHub repository for stochastic computing synthesis shows community engagement with multiple contributors. At Oculus Research, Dr. Alaghi applies his theoretical expertise to practical challenges in next-generation AR/VR system development. His work bridges academic research with real-world product development, particularly in addressing energy efficiency challenges for wearable computing platforms through innovative circuit design approaches.

Sven BuchholzView profile

Professor

• Applied Computer Science
• Data Management
• Data Mining
• +6 more

Prof. Dr.-Ing. Sven Buchholz serves as a Professor in the Department of Computer Science and Media at Brandenburg University of Technology in Brandenburg an der Havel, Germany. His office is located in Building C, Room C.2.18 at Magdeburger Straße 50, with contact information including telephone +49 3381 355-482 and email sven.buchholz@th-brandenburg.de. Specializing in Applied Computer Science , Prof. Buchholz focuses on data management and data mining with a distinctive research trajectory in geometric algebra applications. His scholarly work demonstrates expertise across multiple domains including neural network architectures using Clifford algebra, solving complex partial differential equations, protein structure prediction, and computer vision systems. The evolution of his research shows progression from foundational theoretical work on Clifford neurons in the early 2000s to increasingly interdisciplinary applications in recent years. Analysis of his publication history reveals a significant research focus spanning over 15 years, with a notable resurgence of activity in 2024. His recent work demonstrates sophisticated applications of geometric algebra to solve challenging problems across physics (Maxwell's equations, Navier-Stokes equations), molecular biology (protein structure prediction), and robotics (camera pose estimation). This interdisciplinary approach connects mathematical theory with practical implementations in scientific computing and artificial intelligence. Prof. Buchholz maintains an active research profile with multiple high-impact publications in 2024, indicating ongoing contributions to the advancement of geometric algebra applications in computational science. His work bridges theoretical mathematics with practical machine learning implementations, contributing to both academic knowledge and potential real-world applications in scientific computing and data analysis.

• Human Activity Understanding
• Computer Vision
• Sensor Fusion
• +6 more

Rahul Chaudhari is a Senior Researcher at the Chair of Media Technology, Technical University of Munich (TUM), where he has been working since August 2019. He is affiliated with the Munich Institute of Robotics and Machine Intelligence (MIRMI) and contributes to research in human-computer interaction, particularly in human activity understanding. Dr. Chaudhari earned his doctoral degree (Summa cum Laude) in Communications and Signal Processing from TUM in 2015, following a Master's degree in Communications Engineering from TUM in 2009 and a Bachelor's degree in Electronics and Telecommunications from the University of Pune, India. His academic journey reflects a strong foundation in communications engineering and signal processing that has evolved into interdisciplinary research spanning haptics, computer vision, and artificial intelligence. His research focuses on Human Activity Understanding using Computer Vision, Sensor Fusion, and AI techniques. His current work centers on understanding Human-Object Interactions using camera data (RGB and Depth) recorded in indoor environments, with potential integration of wearable sensors or environmental sensors. His work has significant applications in improving human well-being, comfort, and convenience through intelligent environments and ambient assisted living systems. Dr. Chaudhari's publication record shows a clear evolution from foundational work in haptic communications to cutting-edge research in human-object interaction and 3D pose estimation. His recent publications demonstrate expertise across multiple domains including computer vision for activity recognition, synthetic data generation for training models, and neurosymbolic approaches to human-AI collaboration. This interdisciplinary approach reflects the increasingly connected nature of modern AI research. Best student paper award for Yujun Wang (2025) LMT Spin-off Wins Third Place at euRobotics Technology Transfer Award 2025 LMT featured in Süddeutsche Zeitung (2025) Diego Fernandez Prado selected as finalist for IEEE CASE Best Paper Award (2024) Dr. Chaudhari actively supervises student research, including Master's theses on advanced topics such as 'Simulation and Optimization for 6G Network Planning using Digital Twins.' His supervision work involves guiding students through complex technical challenges in simulation software evaluation, digital twin implementation, and network optimization. He also serves on thesis committees and provides mentorship to students working on related research topics. His research group operates within the broader context of TUM's initiatives in robotics and machine intelligence, contributing to projects like the Centre for Tactile Internet with Human-in-the-Loop (CeTI) and 5G Testbed Bayern. The group maintains a strong focus on both theoretical foundations and practical implementations, with research that bridges the gap between academic innovation and real-world applications in intelligent environments.

Doug BessetteView profile

Associate Professor

• Sustainable energy
• Energy transitions
• Community energy development
• +7 more

Doug Bessette is an Associate Professor in the Department of Community Sustainability at Michigan State University's College of Agriculture and Natural Resources. His work bridges interdisciplinary human-environment systems with applied decision research to address complex energy and sustainability challenges at multiple scales. His primary research interests focus on sustainable energy systems and community energy development, with specific expertise in large-scale solar implementation, energy transitions, and community engagement processes. Bessette employs structured decision-making frameworks that incorporate value-focused thinking to help stakeholders identify objectives, generate alternatives, predict consequences, and make explicit tradeoffs between values and strategies. His recent publications reveal a strong emphasis on understanding community acceptance of renewable energy projects, particularly large-scale solar development. His work examines the relationship between community values, identity, sense of place, and project support, challenging the traditional NIMBY (Not In My Backyard) hypothesis. He has developed practical tools like the US Renewable Energy Organized Opposition & Support Database and the Community-Centered Solar Development guidebook to support evidence-based decision-making. Bessette leads the Energy Values Lab at MSU, which has secured research funding for multiple projects examining the social dimensions of energy transitions. His lab employs both graduate and undergraduate researchers, including work on survey methodology for assessing community attitudes toward solar development. His research extends beyond energy to include organic and sustainable agriculture, coastal climate risk management, natural resource management in developing territories, and green infrastructure. Notably, his work on women's empowerment and electricity access in Zambia demonstrates his commitment to understanding the intersection of energy access and social equity.