Find Academic Supervisors

• Stochastic Analysis
• White Noise Analysis
• Non-Gaussian Analysis
• +3 more

Wolfgang Bock is an Associate Professor (Docent) in Stochastic Analysis at Linnaeus University, where he joined as a Senior Lecturer in August 2023 and was promoted to Associate Professor in December 2023. He serves as Program Director for the Master's Program in Mathematics and is a member of the Faculty Board. His academic career spans institutions in Germany, Portugal, and Sweden, with a strong focus on stochastic processes and their applications. His educational background includes: PhD in Stochastic Analysis (2013) from Technische Universität Kaiserslautern, Germany, supervised by Martin Grothaus Postdoctoral fellowship (2013-2014) at the Center of Mathematical Analysis and its Applications (CMAF) in Lisbon, Portugal Lecturer position (2014 onwards) at Technische Universität Kaiserslautern Permanent senior lecturer (Akademischer Rat) from 2015, responsible for Engineering Mathematics Bock's research centers on Stochastic Analysis, with particular expertise in White Noise Analysis, Non-Gaussian Analysis, and Mittag-Leffler Analysis. His work bridges theoretical mathematics with practical applications in epidemiology, especially in disease modeling for dengue and SARS-CoV-2. He has developed novel approaches to random time variation, non-linear Markov processes, and McKean-SDEs, contributing significantly to the understanding of complex stochastic systems. His recent publications demonstrate a consistent focus on extending classical Gaussian analysis to non-Gaussian settings, with increasing applications to real-world problems in epidemiology and physics. The research shows progression from theoretical foundations to practical applications, particularly in disease transmission modeling. Bock leads the Stochastic Analysis and Stochastic Processes research group and is also involved with the Computational Mathematics for Predictive Digital Twins (PreDiTwin) initiative. His research has attracted international collaborations across Europe, reflecting his commitment to enhancing Linnaeus University's international visibility in stochastic analysis.

• Acoustics
• Vibration Engineering
• Finite Element Analysis
• +5 more

Romain Rumpler is an Associate Professor at the Department of Vehicle Engineering and Technical Acoustics, KTH Royal Institute of Technology. His research focuses on numerical methods and modeling for coupled acoustics and vibration applications, including finite element modeling, design optimization, and acoustic metamaterials. He leads initiatives in transportation noise, such as noise impact assessment and traffic strategies. He is affiliated with the Centre for Eco2 Vehicle Design and has been funded by the Swedish Research Council, FORMAS, VINNOVA, and European programs like Shift2Rail and CIVITAS. His teaching includes courses like Building Acoustics and Community Noise and Noise and Vibration Control . Education: PhD in Vehicle Engineering and Technical Acoustics, KTH Royal Institute of Technology (2012) Research Interests: His work spans efficient finite element methods, acoustic material design, and urban noise mitigation. He develops experimental-numerical approaches for noise assessment and contributes to eco-friendly vehicle design through projects like the EU VAMOR initiative. Recent efforts include metamaterials for sound insulation and real-time noise mapping techniques. Articles Trends: Romain's publications emphasize transportation noise analysis, structural acoustics, and computational methods. Key themes include noise detection algorithms, parametric model reduction, and material characterization for vibration suppression. His work bridges theoretical models with practical applications in urban planning and vehicle engineering. Awards: 2022 Supervisor of the Year Award (Centre for Eco2 Vehicle Design) Grants & Advising: Funded projects include VR, FORMAS, and EU grants. He advises students on acoustic metamaterials and noise control, with a focus on sustainable transportation solutions. His team collaborates on agent-based noise impact models and low-frequency vibration mitigation. Labs & Projects: Associated with Digital Futures initiatives (DIRAC, GEOMETRIC, SENZ-Lab) and the Centre for Eco2 Vehicle Design. His work supports eco-efficient vehicle design and smart traffic strategies to reduce environmental impact.

• Control Systems
• Stochastic Optimal Control
• Power Electronics
• +4 more

Claes Breitholtz is a Professor of Automatic Control at Chalmers University of Technology , Sweden. His research focuses on modeling and control of distributed parameter systems and stochastic optimal control , with key applications in chemical reactor control and high-voltage direct current (HVDC) transmission systems . Key affiliations: Department of Signals and Systems, Chalmers University Email: claesbr@chalmers.se Research Interests His work addresses fundamental challenges in: Stability analysis of VSC-HVDC systems using Nyquist and eigenvalue methods Optimal control of stochastic systems with state constraints Model reduction techniques for complex industrial processes Gain scheduling in nonlinear systems like turbofan engines Publications span 1985–2017, covering both theoretical developments and industrial applications.

Sverker FinnströmView profile

Associate Professor

• Cultural Anthropology
• Conflict Studies
• Postcolonial Theory
• +5 more

Sverker Finnström is an Associate Professor at the Department of Cultural Anthropology and Ethnology, Uppsala University. With a focus on African societies, particularly in northern Uganda, his work bridges ethnographic fieldwork with theoretical approaches to vulnerability and postwar realities. Current affiliation: Uppsala University Academic rank: Associate Professor (since 2009) Research program: Engaging Vulnerability, focusing on war's lingering effects His ethnographic work in Acholiland since 1997 explores the intersections of war, existential uncertainty, and cultural resilience. Finnström emphasizes non-linear narratives and analytical vulnerability, challenging simplistic portrayals of conflict zones. Key themes include: Postwar societal dynamics Intergenerational trauma Local vs global peace efforts Critical analysis of humanitarian interventions Role of storytelling in reconciliation Magical thinking in global warfare Recent publications examine open-ended anthropological approaches and the enduring impact of war on everyday life. His 2008 book Living with Bad Surroundings and 2013 co-edited volume Virtual War and Magical Death have become foundational texts in the field. Awarded the Margaret Mead Award in 2009, Finnström has held positions at Gulu University, Stockholm University, and the Hugo Valentin Centre. He served as chair of the Swedish Anthropological Association (2013-2015) and contributes regularly to academic debates through book reviews and public commentary.

• System Identification
• Control Theory
• Bayesian Estimation
• +5 more

Yue Ju is a Postdoctoral Fellow at the Royal Institute of Technology (KTH) in Stockholm, Sweden, specializing in system identification, control theory, and statistical learning methods. Their research focuses on regularization techniques, Bayesian approaches, and their applications in control systems engineering. Dr. Ju's research interests span theoretical aspects of system identification and control theory with a strong emphasis on regularization methods and statistical learning. Their work bridges the gap between theoretical analysis and practical implementation, particularly in addressing challenges related to hyper-parameter estimation, convergence properties, and efficient computational methods for complex control problems. Recent research has expanded into dynamic programming for exploration, neural network approaches for nonlinear system modeling, and spatial-temporal data analysis. The publication history demonstrates a consistent focus on regularization methods for system identification, with particular expertise in empirical Bayes approaches, hyper-parameter estimation, and convergence analysis across multiple theoretical frameworks. Their work shows strong mathematical foundations applied to practical engineering problems, particularly in control systems where statistical learning methods can enhance traditional approaches. Dr. Ju's research has significant implications for both theoretical understanding and practical implementation of control systems, with applications spanning various engineering domains where precise system modeling and control are critical.

Patrick NormanView profile

Professor

• Theoretical Chemistry
• Molecular Response Theory
• Computational Spectroscopy
• +5 more

Patrick Norman is a Professor and Head of the Division of Theoretical Chemistry and Biology at KTH Royal Institute of Technology, Stockholm, Sweden. He also serves as Director of the PDC Center for High Performance Computing. His research focuses on advanced time-dependent molecular response theory methods, with applications in optical and X-ray spectroscopy. Coordinates VeloxChem and Gator HPC software projects Leads EU-EIC project OMICSENS (2023–2026) for lung cancer biosensors Principal Investigator in EU-ITN COSINE (2018–2021) and KAW network CoTXS (2014–2019) His theoretical work includes resonance convergent response theory via Liouville equations and Ehrenfest theorem, implemented in quantum chemistry software for linear/nonlinear spectroscopy. He co-authored the graduate textbook Principles and Practices of Molecular Properties (Wiley, 2018) and organizes international PhD schools on molecular response properties. Recent publications emphasize fragment state optimization, solvation effects, chiral luminescent materials, and amyloid ligand binding simulations. His work bridges quantum chemistry, HPC, and biomedical applications through tools like Gator and VeloxChem .

Zheng ZhaoView profile

Assistant Professor

• Computational Statistics
• Machine Learning
• Generative Diffusion Models
• +4 more

Zheng Zhao is an Assistant Professor in computational statistics and machine learning at Linköping University, leading a research team within the Division of Statistics and Machine Learning (STIMA) under the Department of Computer and Information Science (IDA). His work focuses on developing computationally and statistically efficient models for machine learning applications, particularly generative diffusion models and their use in signal/image processing. He also applies these methods to fields like astronomy (e.g., stellar magnetic field analysis) and climate science. His research team emphasizes practical applications of diffusion models and Bayesian methods, contributing to advancements in image restoration, sensor array analysis, and high-dimensional data modeling. Zhao collaborates with STIMA colleagues on interdisciplinary projects, leveraging statistical theory and computational techniques. Publications highlight his exploration of diffusion models, Bayesian neural networks, and probabilistic methods across domains like astrophysics and environmental science. His work bridges theory and application, addressing challenges in uncertainty quantification and overfitting mitigation. Zhao is actively involved in academic initiatives such as the international master's program in Statistics and Machine Learning (hosted by STIMA). His research has been applied in competitions like the NTIRE challenge, demonstrating real-world impact in image restoration.

• Quantum Computing
• Quantum Information
• Theoretical Physics
• +3 more

Giulia Ferrini is an Associate Professor at Chalmers University of Technology's Department of Microtechnology and Nanoscience (MC2) and a Principal Investigator (PI) at the Wallenberg Centre for Quantum Technologies (WACQT). She holds a PhD from the University of Grenoble (France, 2011), focusing on Macroscopic quantum coherent phenomena in Bose-Josephson junctions . Prior to joining Chalmers, she conducted postdoctoral research at institutions including Laboratoire Kastler Brossel (Paris), University Paris-Diderot, and the University of Mainz, where she received a Marie Sklodowska Curie Individual Fellowship to explore quantum computation models. Her research centers on theoretical quantum information with continuous variables, particularly leveraging non-Gaussian resources and quantum error correction. She leads initiatives in quantum computing, including teaching the course Quantum Computing at Chalmers. Her work spans foundational studies in quantum state generation, error mitigation, and hybrid quantum-classical algorithms for optimization problems. Key contributions include advancements in Gottesman-Kitaev-Preskill (GKP) code applications, quantum resource theory, and noise resilience in quantum circuits. Ferrini’s projects are funded by the Swedish Research Council (VR) and the Knut and Alice Wallenberg Foundation, among others. She actively collaborates on quantum advantage assessments and practical implementations of continuous-variable quantum technologies.

Fredrik LindstenView profile

Associate Professor

• Machine Learning
• Statistical Machine Learning
• Approximate Bayesian Inference
• +7 more

Fredrik Lindsten is a Senior Associate Professor in Machine Learning and Head of the Division of Statistics and Machine Learning at Linköping University's Department of Computer and Information Science (IDA). His research focuses on statistical machine learning, emphasizing probabilistic modeling and uncertainty quantification in methods such as approximate Bayesian inference, representation learning, and graph-based approaches. Applications span weather forecasting, materials science, biochemistry, and automotive industry challenges. Education: MSc (2008), PhD (2013) in Automatic Control from Linköping University; Postdoctoral roles at University of Cambridge, UC Berkeley, and University of Oxford. Affiliations: WASP (Wallenberg AI, Autonomous Systems and Software Program), ELLIIT (Lab for Information and Communication Technology). Research Interests: Lindsten’s work bridges statistical methodology and machine learning, particularly in quantifying uncertainty in predictions. His team explores method development across diverse applications, including spatio-temporal models and graph-based techniques. Recent projects include probabilistic weather forecasting with graph neural networks and cryo-EM reconstruction techniques. Publications: Over 25+ peer-reviewed articles, with recent highlights in Nature Methods , NeurIPS , and Physical Review Materials , focusing on Bayesian methods, generative models, and computational statistics. Awards: Ingvar Carlsson Award (Swedish Foundation for Strategic Research), Benzelius Award (Royal Society of Sciences in Uppsala). Grants & Teams: Supervises 7+ PhD students; active in collaborative projects funded by WASP, ELLIIT, and VR (Swedish Research Council). Labs/Teams: Leads the Division of Statistics and Machine Learning (STIMA) at IDA, fostering interdisciplinary research in probabilistic machine learning.

Mikael OlofssonView profile

Associate Professor

• Telecommunications
• Electronics
• Mathematics
• +5 more

Mikael Olofsson is an Associate Professor and Head of Division at the Division of Electronics and Computer Engineering (ELDA), Department of Electrical Engineering (ISY), Linköping University. He is actively engaged in teaching and academic leadership, serving as director of studies for courses in Integrated Circuits and Systems since 2018. His research background lies at the intersection of telecommunications, electronics, and mathematics , particularly focusing on algorithms and architectures for arithmetic operations in finite fields . His PhD thesis, VLSI Aspects on Inversion in Finite Fields (2002), reflects this interdisciplinary focus. Though currently more focused on education, he continues to explore arithmetic-related algorithmic designs when time permits. The recent publications reflect a strong emphasis on signal theory and telecommunications education , including textbooks and pedagogical research. Topics span signal processing fundamentals, digital modulation, and Massive MIMO principles , indicating a consistent thread in communication systems education and foundational theory. Scientific Awards: No awards listed in the provided text. Advising and Grants: While no formal students or grant awards are listed, Mikael Olofsson plays a significant mentoring role through his extensive teaching and leadership as director of studies. He emphasizes the value of student discussions and strives to provide optimal learning opportunities, suggesting strong engagement in academic advising at the course and program level. Labs and Teams: He is affiliated with the Division of Electronics and Computer Engineering (ELDA), which conducts research in analog, digital, mixed-signal electronics, programmable systems, and processor design. This division is part of the broader Department of Electrical Engineering (ISY), known for strong industry and research collaborations.

• Numerical Analysis
• High-Performance Computing
• Parallel Computing
• +5 more

Carl C. Kjelgaard Mikkelsen is an Associate Professor at the Department of Computing Science, Umeå University. He specializes in numerical analysis and high-performance parallel computing, focusing on robust algorithms that cannot fail. He co-authored the StarNEig library for nonsymmetric eigenvalue problems and works on parallel constraint solvers for molecular dynamics and ultra-sparse linear systems. Research Interests: Numerical analysis, parallel computing, eigenvalue problems, linear systems, algorithm design. His recent publications emphasize robust task-based algorithms, GPU acceleration, and precision requirements in Newton's method. He teaches numerical analysis and scientific computing, emphasizing finite precision arithmetic and software documentation.

Stefan JohanssonView profile

Associate Professor

• Visualization
• Numerical Linear Algebra
• Computer Graphics
• +4 more

Stefan Johansson is an Associate Professor at Umeå University's Department of Computing Science, where he also serves as Deputy Head of Department overseeing finance and personnel. He maintains a part-time research affiliation with Curiosum Science Center, leading technical development for exhibitions and dome theaters. His research focuses on visualization , numerical linear algebra , and interactive educational tools . Current projects include VisA, which develops dome-theater visualizations of atmospheric data for science education. His work bridges computer graphics, software engineering, and didactic methods. Johansson's publications reflect dual expertise: earlier works emphasize matrix computations and control theory (2004-2017), while recent research shifts toward scientific visualization applications (2020-2025), particularly in geosciences and educational technology. Awards & Leadership Recognised University Teacher (Meritorious Teacher) 2021 Program Director, MSc in Computing Science (2022-2023) Deputy Director, Curiosum Science Center (2019-2021) He contributes to research groups in Matrix Computations with Applications and Parallel and Scientific Computing , and develops STEM curricula for primary/secondary schools.

Ninive von GreiffView profile

Professor

• Substance Abuse Treatment
• Recovery Processes
• Social Work
• +5 more

Ninive von Greiff is a Professor at the Department of Social Work at Stockholm University, specializing in addiction research and social work with people experiencing substance use disorders. Her work focuses on understanding recovery processes, gender perspectives in treatment, and long-term outcomes of substance abuse interventions. Department of Social Work, Stockholm University Member of the Addiction Research Group (ARG) Member of The Substance Use Group (SUG) Conducts research on recovery processes and social work interventions Professor von Greiff's research interests center on addiction treatment, recovery processes, and the social aspects of substance use disorders. She has extensively studied gender differences in recovery, the concept of recovery capital, and long-term follow-up studies of individuals treated for substance use disorders. Her work emphasizes the importance of social context, professional relationships, and individual agency in the recovery process. She investigates how factors like social networks, employment, mental health, and gender influence recovery trajectories and long-term outcomes. Her publication record shows a consistent focus on qualitative studies examining recovery processes over extended periods. A notable pattern in her research is the emphasis on understanding recovery as a dynamic, individualized process rather than a linear path. She frequently compares gender differences in recovery experiences and examines how social position influences recovery trajectories. Many of her studies employ longitudinal designs with five to thirty-year follow-ups, providing valuable insights into the long-term outcomes of substance abuse treatment. Professor von Greiff has been involved in numerous research projects including 'Preventing ill-health among close relatives of people with alcohol and drug problems,' 'Five-year follow-up – clients treated for alcohol/drug/psychosocial problems,' 'The future of social service work with substance use (FUSS),' and 'Recovery and identity – a 10-year follow-up.' Her work often involves collaborative research with colleagues like Lisa Skogens and Alain Topor, and she frequently publishes in journals such as Nordic Social Work Research, European Journal of Social Work, and Addiction Research and Theory.

Jörgen OlssonView profile

Professor

• Solid-State Electronics
• High-frequency MOS-based devices
• SOI-technology
• +4 more

Professor Jörgen Olsson is a faculty member at Uppsala University's Department of Materials Science and Engineering with a specialization in Solar Cell Technology. He serves as Deputy Head of Department and Director of Postgraduate Studies, while also participating in multiple university committees including the Doctoral Education Board (FUN), Teknat Faculty Advisory Committees for both Research and Education, and the Teknat Equal Opportunities Committee. Ph.D. in Electronics from Uppsala University (1996) Visiting Scientist at Digital Semiconductor, Hudson, MA (1997) Promoted to Professor in Solid-State Electronics (2008) Professor Olsson's research spans semiconductor device physics with evolving focus areas. Early work centered on high-frequency MOS-based devices, SOI-technology, and RF-power devices. His more recent research has shifted toward photovoltaics, particularly thin-film solar cells including CIGS and CZTS technologies. His publications demonstrate expertise in both fundamental semiconductor physics and practical device applications, with significant contributions to understanding device behavior under various conditions. Analysis of his recent publications (2016-2022) reveals a dual research trajectory: continued work on RF power devices and amplifiers for particle accelerators, alongside growing contributions to photovoltaic technology. His work bridges electrical engineering and materials science, with applications ranging from wireless communications to renewable energy. The consistent publication record demonstrates sustained research productivity across multiple domains of semiconductor device physics. Professor Olsson has served in significant academic leadership roles including Director of Postgraduate Studies and Deputy Head of Department. His extensive publication record (over 180 scientific papers) indicates substantial research activity and mentorship within his field. His work with the Doctoral Education Board suggests active involvement in graduate education and academic program development. At the Ångström Laboratory, Professor Olsson headed the Solid State Device Group, where research spanned semiconductor device fabrication, characterization, and modeling. His work connects fundamental device physics with practical applications in both electronics and renewable energy sectors, reflecting the interdisciplinary nature of modern materials science research.

• Quantum Physics
• Quantum Computing
• Quantum Technology
• +3 more

Göran Johansson is a Professor of Applied Quantum Physics at Chalmers University of Technology in Gothenburg, Sweden. Since January 1, 2025, he has served as the director of the Wallenberg Centre for Quantum Technology, a major research initiative spanning from 2018 to 2030. His academic career is centered on quantum physics research with a focus on both fundamental phenomena and practical quantum technology applications. Professor Johansson's research spans quantum physics, quantum technology, and quantum computing. He investigates fundamental quantum mechanical effects such as the dynamic Casimir effect, which describes photon generation from vacuum when a mirror accelerates at relativistic speeds. His applied research focuses on building quantum computers that leverage quantum superposition and entanglement to solve problems beyond the reach of classical supercomputers, with potential applications in drug discovery, artificial intelligence, and optimization problems like traffic planning. His work bridges theoretical quantum physics with practical implementation in superconducting circuits. An analysis of his recent publications reveals a strong focus on quantum computing hardware, particularly superconducting qubits and quantum processors. His research addresses key challenges in quantum computing including decoherence, quantum gate fidelity, quantum error correction, and quantum state engineering. There's a clear progression toward more complex quantum systems, with recent work exploring multi-qubit gates, quantum algorithms for practical applications, and integration of quantum processors. His publications consistently appear in top physics journals including Physical Review Letters, Physical Review A/B, and npj Quantum Information. Professor Johansson has received two significant awards for his contributions to quantum physics: Edlund Prize 2016 from the Royal Swedish Academy of Sciences Albert Wallin Science Prize 2015 from the Royal Society of Science and Letters in Gothenburg He leads or participates in multiple major research projects including the Wallenberg Centre for Quantum Technology (2018-2030), Quantum Networks with Delay and High-Impedance Transmission Lines (2022-2025), Quantum Information with Microwaves and Surface Acoustic Waves (2018-2021), and Quantum Plasmonics (2017-2022). These projects involve collaborations with numerous researchers across Chalmers and with external partners, supported by funding from the Swedish Research Council (VR) and the Knut and Alice Wallenberg Foundation. As director of the Wallenberg Centre for Quantum Technology, Professor Johansson oversees one of Sweden's largest quantum research initiatives, which includes a broad team of researchers working on quantum computing, quantum communication, and quantum sensing. His research group focuses on superconducting quantum circuits, exploring both fundamental quantum phenomena and practical implementations for quantum information processing. The group works extensively with microwave quantum optics and has made significant contributions to the understanding and manipulation of quantum states in superconducting systems.