جستجوی استاد راهنمای دانشگاهی

• Automation Engineering
• Sustainable Production
• Robotics
• +۳ مورد دیگر

Bengt Lennartson is a Professor of Automation at Chalmers University of Technology and Head of the Department of Systems and Control Engineering. His research focuses on automation engineering, sustainable production, robotics, and energy optimization, with over 280 international publications. Collaborations include industry leaders like Volvo, Daimler, Kuka, and TetraPak. IEEE Fellow for contributions to automation systems Specializes in hybrid/discrete-event systems Develops energy optimization strategies for robotic production lines Recent work explores Plug-and-Produce systems , digital twin calibration , and stochastic energy optimization in robotics. His team integrates AI with formal methods for safety verification and develops open-source educational tools like biomedical exoskeletons. Scientific awards include IEEE Fellowship , with articles addressing energy-efficient robot trajectories, safety-aware multi-agent control, and formal verification of cyber-physical systems.

• Partial Differential Equations
• Numerical Analysis
• Stochastic Differential Equations
• +۵ مورد دیگر

Anders Szepessy is a Professor in Mathematics and Numerical Analysis at the Department of Mathematics, KTH Royal Institute of Technology. His research centers on partial differential equations and numerical methods for differential equations, with significant contributions to molecular dynamics, quantum mechanics, and stochastic systems. His primary research domains include: Partial Differential Equations Numerical Analysis Stochastic Differential Equations Molecular Dynamics and Quantum Mechanics Optimal Control and Finite Element Methods Machine Learning Applications Recent publications reveal a pronounced shift toward integrating machine learning with computational physics, particularly in neural network approximations for molecular dynamics and quantum systems. His work on adaptive methods for high-dimensional stochastic and partial differential equations demonstrates consistent innovation in numerical analysis, with applications spanning quantum chemistry, fluid dynamics, and energy systems. Professor Szepessy actively contributes to academic instruction as course responsible and examiner for advanced mathematics courses including Analytical and Numerical Methods for Partial Differential Equations, Computational Methods for Stochastic Differential Equations and Machine Learning, and multiple degree projects in mathematics and scientific computing at KTH.

Frida Heskebeckمشاهده پروفایل

پژوهشگر

• Brain-Computer Interfaces
• Machine Learning
• Control Engineering
• +۷ مورد دیگر

Frida Heskebeck is a Doctoral student at the Department of Automatic Control , Lund Institute of Technology , Lund University , and a member of the LTH Profile Area: AI and Digitalization . She actively contributes to the research group on EEG-based Brain-Computer Interfaces (BCI) led by Prof. Bo Bernhardsson . Research Focus: Optimization of next-generation BCI using cloud computing and individualization of real-time systems. Teaching: Delivers lectures, webinars, and lab sessions for courses like Process Control and Systems Engineering (2024), Physiological Models and Computations (2023), and Automatic Control (2021, 2020). Awards: Recipient of the Pedagogical Prize for best teaching assistant in 2021 (M-guild and W-guild) and Best Master's Thesis in 2020. Research Trends: Her recent articles focus on BCI calibration, real-time control, and cloud integration. Broad keywords include Control Engineering , Machine Learning , and Neuroscience , with sub-fields like Domain Adaptation , Signal Processing , and Online Teaching . Scientific Distinctions: Teaching assistant of the year (awarded by the M-guild) 2021 Teaching assistant of the year (awarded by the W-guild) 2021 Best Master's Thesis 2020 Advising and Collaborations: Supervision of master's theses for Tom Andersen (2021) and Johanna Wilroth (2020), where the latter received a scholarship. She also held roles in the department's board and organized seminars like the AI Lund lunch seminar in 2024.

• Biomedical Engineering
• Microwave Technology
• Non-invasive Physiological Sensing
• +۷ مورد دیگر

Robin Augustine is an Associate Professor in Medical Engineering at Uppsala University, Sweden, affiliated with the Department of Electrical Engineering within the Faculty of Science and Technology. He serves as the Head of the Microwaves at the Medical Engineering (MMG) group at the FTE Division and holds the position of Senior Lecturer/Associate Professor in Solid-State Electronics. His work bridges biomedical engineering and microwave technology, focusing on developing innovative medical devices and diagnostic systems. Dr. Augustine holds a Ph.D. in Electronics and Optic Systems from Université Paris-Est Marne-la-Vallée, France, a Master's in Electronics with Robotics Specialization from Cochin University of Science and Technology, India, and a Bachelor's in Electronics Science from Mahatma Gandhi University, India. His doctoral thesis focused on electromagnetic modeling of human tissues and antenna-human body interaction in the Body Area Network (BAN) context. Prior to his current position, he served as a Postdoctoral Researcher at the University of Rennes 1, France, and has been a Senior Researcher at Uppsala University since 2011. Dr. Augustine's research spans multiple cutting-edge areas in biomedical engineering, with particular emphasis on medical microwave sensors , intra-body communication systems , and non-invasive diagnostic technologies . He pioneered the concept of human body-centric communication known as Fat-IBC (Fat-Intra Body Communication), which utilizes fat tissue as a communication channel for medical devices. His work in burn injury diagnosis using microwave technology has led to significant clinical applications, while his research in wireless power transfer systems for implantable biomedical devices addresses critical challenges in medical device longevity. Additional research interests include electromagnetic modeling of human tissues, anthropomorphic phantoms for medical testing, and AI-integrated diagnostic systems for conditions like ARDS and diabetes. Analysis of Dr. Augustine's recent publications reveals a strong focus on advancing intra-body communication through fat tissue , with multiple papers exploring Fat-IBC system design, performance optimization, and security. His research group is actively developing non-invasive diagnostic systems for various medical conditions including burn injuries, diabetes, and respiratory distress. The integration of machine learning with microwave sensing technologies represents another significant trend in his recent work, enabling more accurate medical diagnostics through advanced signal processing. Dr. Augustine serves as Principal Investigator (PI) for several major research projects including VR projects Osteodiagnosis (2017) and MuSkeldiagnosis (2024), as well as Vinnova projects BDAS, Fat-IBPT, and AI-DARDS. He is also PI of the H2020 FET OPEN project B-CRATOS, and serves as Work Package Leader (WPL) for H2020 RIA SINTEC (2019) and PERSIMMON (2024). As Co-PI, he contributes to SSF Framework Grants LifeSec, Zero-IoT, and BOS, along with the VR Back Scatter project (2023). Additionally, he leads R&D efforts for multiple Eurostars projects including SenseBurn, MAS, COMFORT, and DIAMPS. Dr. Augustine founded, chairs, and serves as CTO of Probingon AB, a Swedish Medtech company. He leads the Microwaves at the Medical Engineering Group (MMG), which comprises 4 PhD students, 6 senior researchers and a project manager. His research group collaborates extensively with clinical partners to translate engineering innovations into practical medical applications, with particular focus on developing technologies that improve diagnostic accuracy and patient outcomes while reducing healthcare costs.

• Social Anxiety Disorder
• Cognitive Behavioral Therapy
• Neuroimaging
• +۵ مورد دیگر

Professor Tomas Furmark is a prominent researcher at Uppsala University's Department of Psychology, specializing in Emotion Psychology. His work focuses extensively on social anxiety disorder, cognitive behavioral therapy, and neuroimaging techniques to understand the biological underpinnings of anxiety disorders. He maintains an active research program with numerous publications in high-impact journals. His research interests include: Social Anxiety Disorder and its neurobiological mechanisms Cognitive Behavioral Therapy (CBT) and internet-delivered treatments Neuroimaging (PET, fMRI) of anxiety disorders Serotonin and dopamine systems in anxiety Placebo effects in psychiatric treatment Memory reconsolidation in fear processing Professor Furmark's publication record demonstrates a consistent focus on understanding the neural mechanisms of social anxiety disorder through advanced imaging techniques. His recent work examines treatment mechanisms, biomarkers for treatment response, and the interplay between pharmacological and psychological interventions. He frequently collaborates with international research groups, particularly within the ENIGMA consortium for large-scale neuroimaging studies. His research has important clinical implications for understanding treatment mechanisms and developing more targeted interventions for anxiety disorders. Professor Furmark has contributed significantly to the understanding of how cognitive behavioral therapy induces neuroplastic changes and how placebo effects interact with biological treatments.

Johan Henrikssonمشاهده پروفایل

دانشیار

• T-cell biology
• Cancer immunotherapy
• CAR T-cell engineering
• +۷ مورد دیگر

Johan Henriksson is Associate Professor at Umeå University, Sweden, where he leads the Johan Henriksson Group within the Department of Molecular Biology and the Laboratory for Molecular Infection Medicine Sweden (MIMS), a node of the Nordic EMBL Partnership for Molecular Medicine. He is also affiliated with UCMR (Umeå Centre for Microbial Research) and IceLab (Integrated Science Lab), emphasising cross-disciplinary collaboration. Research in a nutshell. Henriksson’s team explores how T cells function in health and disease, with a special emphasis on cancer and CAR T-cell immunotherapy. By integrating single-cell multi-omics, pooled CRISPR screens, synthetic biology, and machine learning, the group maps gene-regulatory networks that control T-cell identity and anti-tumour activity. They develop wet-lab protocols (e.g., molecular inversion probes for unbiased quantification) and open-source computational tools—including the Nando framework for gene-expression prediction and high-performance pipelines written in Rust—to extract robust biological knowledge from very large datasets. Major research directions. Discovery of a novel JUNB + CD4 T-cell state linked to memory formation, circadian rhythm, and CAR T-cell exhaustion. Single-cell telomere measurements for early cancer detection, particularly pancreatic cancer. Pooled CRISPR screening in primary human T cells and in Plasmodium falciparum to uncover essential regulators. Extension of single-cell technologies to microbial systems in collaboration with Laura Carroll, Kemal Avican, and Linas Mažutis. Development of the Bascet/Zorn pipeline for reference-free comparative genomics across mixed microbial communities. Advocacy and engineering of the Rust programming language for safe, high-performance bioinformatics. Collaborative network. Henriksson actively collaborates with experts who contribute complementary biological insight: Isabelle Magalhães (CAR T-cell therapy), Nicole Boucheron (T cells in allergic asthma), Mattias Forsell (B-cell responses), Anna Överby (tick-borne encephalitis), Annasara Lenman (SARS-CoV-2), Tommy Löfstedt (machine-learning latent-space models), Ellen Bushell ( Plasmodium gene essentiality), and many others. Training & mentorship. The group currently hosts PhD students (e.g., Ionut Sebastian Mihai) and welcomes additional students and postdocs interested in combining wet-lab immunology with computational innovation, especially those eager to adopt Rust for large-scale data analysis.

• Hydrology
• Hydrogeology
• Climate Change Impact on Water Resources
• +۴ مورد دیگر

Roland Barthel serves as Professor in the Department of Geosciences at the University of Gothenburg's Faculty of Science and concurrently holds the position of Vice-Dean for the Faculty Office of Natural Sciences and Technology. Previously Head of Department (2018-2022), he specializes in groundwater resources within the context of climate change impacts across Sweden and Europe. His research integrates hydrological science with socioeconomic factors to address critical water challenges including drought, scarcity, and extreme weather events. Barthel emphasizes the societal dimensions of water management, particularly regarding unregulated private wells that constitute a significant portion of Sweden's drinking water supply. His interdisciplinary approach bridges natural and social sciences to develop implementable solutions requiring consideration of economic, political, and social frameworks alongside physical system understanding. Analysis of his publication record reveals a dominant focus on data-driven methodologies for groundwater dynamics assessment, drought propagation analysis, and climate adaptation strategies. His work consistently emphasizes regional-scale studies in temperate and high-latitude environments, with increasing attention to interdisciplinary collaboration frameworks. Scientific recognition includes: Student Union's Pedagogical Award (2014) Student Union's Pedagogical Award (2016) As an educator, Barthel pioneered hydrology instruction at the university by developing the master's course Applied Hydrology (GVG460) and undergraduate Hydrology and Hydrogeology (GV2002). He leads Earth Sciences thesis supervision, chairs the program committee, and contributes to multiple geoscience courses. His teaching excellence earned three consecutive pedagogical award nominations with wins in 2014 and 2016. He currently participates in an EU Erasmus+ project developing digital teaching tools with European partners, addressing high market demand for groundwater specialists in Swedish infrastructure and environmental sectors.

Najmeh Abiriمشاهده پروفایل

مدرس ارشد

• Machine Learning
• Deep Learning
• Generative Models
• +۵ مورد دیگر

Najmeh Abiri serves as a Senior Lecturer in the Department of Computer Science and Media Technology at Malmö University's Faculty of Technology and Society, specializing in Machine Learning research and instruction. Her research spans Deep Learning , Generative Models , and Uncertainty Quantification , with methodological focus on data imputation for noisy or incomplete datasets. She actively bridges theoretical advances with real-world applications through interdisciplinary collaborations. In partnership with the Swedish Veterinary Institute, she develops machine learning solutions for large-scale tick surveillance systems—including automated tick species classification , pathogen distribution modeling , and data quality control protocols —advancing public health monitoring through citizen science frameworks.

Erik Schaffernichtمشاهده پروفایل

مدرس ارشد

• Robotics
• Sensor Systems
• Machine Learning
• +۶ مورد دیگر

Erik Schaffernicht serves as a Senior Lecturer in the Department of Natural Sciences and Technology at Örebro University's School of Science and Technology. His research is primarily conducted through the Center for Applied Autonomous Sensor Systems (AASS) where he leads work in the Adaptive and Interpretable Learning Systems and Robot Navigation and Perception research groups. Dr. Schaffernicht's research spans multiple areas in robotics and artificial intelligence, with particular expertise in sensor systems, behavior trees, and gas distribution mapping. His work bridges theoretical computer science with practical applications in autonomous systems, environmental monitoring, and human-robot interaction. His research often involves developing novel algorithms for robot perception, control, and decision-making in complex environments. His recent publications demonstrate a strong focus on behavior trees for robot control, gas distribution mapping techniques, and applications of machine learning in robotics. The research shows increasing sophistication in using deep learning approaches for environmental sensing and robot navigation, with applications ranging from industrial safety to healthcare monitoring. Dr. Schaffernicht maintains an active research agenda with numerous publications in top robotics and AI venues, including IEEE Robotics and Automation Letters, Robotics and Autonomous Systems, and various IEEE conference proceedings. His work shows consistent collaboration with researchers across Europe, particularly with the AASS research center at Örebro University. His research projects include both ongoing work on automatic cognitive screening tests using eye-tracking technology and completed projects such as AIR (Action and Intention Recognition), RAISE (Robotic System for Air Quality Assessment), and SmokeBot (Mobile Robots for Disaster Site Inspection).

• Stochastic Control Theory
• Artificial Intelligence for Optimization
• Power Systems Engineering
• +۳ مورد دیگر

Magnus Perninge is an Associate Professor in Electrical Engineering at Linnaeus University (LNU), Sweden. He previously completed his undergraduate and PhD studies at KTH Royal Institute of Technology and held postdoctoral/researcher positions at Lund University. His teaching includes courses in Automatic Control (basic and advanced), Electric Power Systems , and Electrical Machines . He supervises Alexander Marcial , a doctoral student in Mathematics. Current Affiliation: Linnaeus University (School of Engineering & Faculty of Technology) Past Affiliations: KTH Royal Institute of Technology, Lund University Research Interests: Magnus specializes in the optimal control of stochastic systems with applications in electrical energy systems . He integrates artificial intelligence and machine learning to solve large-scale optimization problems in power systems, aiming to enhance efficiency and sustainability. His work bridges stochastic analysis , operations research , and renewable energy integration . Research Projects: Efficient Hydropower Planning : Optimizing Sweden's hydropower for future intermittent energy scenarios Sustainable Energy & Food Production : Enhancing rural farm energy systems Smart Electrification : Supporting SMEs in Kronoberg and Kalmar regions Research Groups: AI and Machine Learning for Optimization and Operations Research Stochastic Analysis and Stochastic Processes Waves, Signals and Systems

• Colorectal Surgery
• Rectal Cancer
• Diverticulitis
• +۶ مورد دیگر

Maziar Nikberg serves as an Associate Professor and Chief Physician of Surgery at the Center for Clinical Research, Västmanland, affiliated with Uppsala University. Based at Västmanland Hospital Västerås, he maintains dual roles in clinical practice and academic research within surgical specialties. Dr. Nikberg's research spans colorectal surgery, rectal cancer treatment, diverticular disease management, and stoma-related complications. His work integrates clinical practice with academic inquiry, focusing on surgical outcomes, cancer recurrence patterns, and evidence-based management strategies for gastrointestinal conditions. His doctoral thesis on 'Rectal Cancer: Surgical Strategies and Histopathological Aspects' (2011) established his expertise in surgical oncology. Analysis of his recent publications reveals a strong emphasis on registry-based studies, randomized controlled trials, and comparative effectiveness research. His work frequently involves multicenter collaborations across Sweden and internationally, addressing practical clinical questions with direct implications for surgical guidelines. Key research themes include optimizing surgical techniques for colorectal procedures, understanding cancer metastasis patterns, and developing improved approaches to common gastrointestinal conditions. Dr. Nikberg has contributed to major clinical trials including the AVOD trial on antibiotic avoidance in diverticulitis and the HAPIrect trial comparing surgical approaches for rectal cancer. His research has been cited extensively across academic platforms and has influenced clinical practice through numerous high-impact publications in leading surgical journals.

Valeriy Vyatkinمشاهده پروفایل

استاد مهمان

• Industrial Automation
• IEC 61499
• Dependable Communication Systems
• +۲ مورد دیگر

Valeriy Vyatkin serves as a Visiting Professor and Chaired Professor at Luleå University of Technology, specializing in Dependable Communication and Computation Systems within the Department of Computer Science, Electrical and Space Engineering. His research focuses on industrial automation technologies with particular emphasis on the IEC 61499 standard. Professor Vyatkin's research spans dependable communication systems, distributed automation architectures, and the integration of emerging technologies like large language models in industrial contexts. His work bridges theoretical computer science with practical industrial implementation, addressing challenges in virtual commissioning, performance analysis, and control systems optimization. Recent publications demonstrate his innovative approach to applying advanced computational methods to traditional industrial automation problems. His research demonstrates a clear trend toward integrating cutting-edge computational paradigms with established industrial automation standards. This includes pioneering work on physics-informed machine learning for industrial processes and decentralized control systems for applications like vertical farming. His publications in IEEE venues highlight the significance and relevance of his contributions to the field. Professor Vyatkin maintains active collaborations with researchers from institutions including Aalto University in Finland, as evidenced by his co-authored publications. His work has practical implications for improving efficiency, reliability, and adaptability of industrial automation systems across multiple sectors including manufacturing, agriculture, and energy-intensive industries.

Karl Anderssonمشاهده پروفایل

استاد

• Cybersecurity
• 5G/6G Networks
• Internet of Things
• +۳ مورد دیگر

Professor Karl Andersson serves as Dean for the Faculty of Science and Technology and Head of Subject for Cyber Security at Luleå University of Technology in Skellefteå, Sweden. He holds positions in both the Department of Computer Science and the Department of Systems and Space Engineering, with research focus primarily in cybersecurity and next-generation network technologies. Dr. Andersson earned his Master's degree in Computer Science and Technology from the Royal Institute of Technology in Stockholm before working in industry with Capgemini Group as a consultant, project manager, business developer, and branch manager. He returned to academia to complete his PhD with a dissertation titled "On Access Network Selection Models and Mobility Support in Heterogeneous Wireless Networks." His postdoctoral work included research appointments at Columbia University in New York and as a JSPS Fellow at the National Institute of Information and Communications Technology in Tokyo. His research interests span cybersecurity, 5G/6G networks, Internet of Things, wireless network mobility, and explainable artificial intelligence. From 2017-2023, he led the Center for Distance-spanning Technology at LTU, focusing on fifth and sixth generation mobile networks, IoT, and data centers. His recent publications demonstrate a growing interest in applying machine learning to cybersecurity challenges and medical diagnostics. Professor Andersson's publication record shows a strategic evolution from wireless networking fundamentals to applied cybersecurity and machine learning solutions. His recent 2025 publications indicate active research in explainable AI frameworks, malicious URL detection, and medical applications of machine learning, suggesting an interdisciplinary approach that bridges cybersecurity with healthcare applications. Senior Member of IEEE Senior Member of ACM General Chair for IEEE Conference on Local Computer Networks (LCN) 2020-2021 Reviewer for numerous prestigious journals including IEEE Transactions on Mobile Computing and IEEE Transactions on Computers Member of editorial boards for Journal of Internet Services and Information Security and Journal of Wireless Mobile Networks, Ubiquitous Computing, and Dependable Applications As Dean for the Faculty of Science and Technology since January 2022, Professor Andersson oversees significant research funding and academic programs. His service as a reviewer for major conferences (ICC, Globecom, VTC, WCNC) and journals demonstrates his standing in the academic community. The Center for Distance-spanning Technology that he led from 2017-2023 likely secured substantial research grants in 5G/6G and IoT domains. Based in Campus Skellefteå at Forskargatan 1, Professor Andersson's work through the Department of Computer Science and Department of Systems and Space Engineering connects theoretical research with practical applications in next-generation networking and security. His leadership of the Center for Distance-spanning Technology positioned LTU as a significant player in 5G/6G research, while his recent publications suggest expanding collaborations with medical researchers applying AI to healthcare challenges.

• Pediatrics
• Pediatric Allergology
• Asthma Research
• +۵ مورد دیگر

Björn Nordlund is an Adjunct Senior Lecturer and Docent at Karolinska Institutet, affiliated with the Department of Women's and Children's Health, Division of Clinical Paediatrics. He serves as the Research Group Leader for the Prevention of asthma and allergy (PANDA) research group, focusing on early-life and digital intervention strategies for asthma and allergy prevention. His primary research interests encompass pediatric allergology, asthma prevention strategies, digital health applications for respiratory diseases, and early intervention approaches. Nordlund has developed several innovative projects including PreventADALL (a Nordic birth cohort study investigating early food introduction and skin care to prevent allergies), ADVERT (using home spirometry for asthma diagnosis), AI-assisted asthma prevention systems, and the APPETITE study (an app-based medical device for inhalation technique training). His recent publications demonstrate expertise in AI applications for asthma prediction, early intervention strategies for allergy prevention, and digital health tools for respiratory disease management. His research often involves large-scale multicenter studies across Scandinavia with significant clinical implications for childhood respiratory health. Grants from the Asthma and Allergy Association's Research Fund Project funding from ALF Medicine and HMT, Region Stockholm Swedish Heart-Lung Foundation support Vinnova – Medtech4Health funding Collaboration with The Jerring Foundation Nordlund actively supervises graduate students at master's and PhD levels while teaching clinical immunology and digital healthcare of respiratory diseases. His work bridges clinical practice with technological innovation, particularly through his founding of the Home Spirometry System 'AsthmaTuner,' which was ranked as the best digital technology for asthma in Europe in 2023 by the Federation of Allergy and Airway diseases patient organisations.