Prof. Dr. Oliver Crönertz serves as Dean and Professor of Business Administration and IT-Supported Business Processes at the Faculty of Digital Transformation , HTWK Leipzig. His work bridges digital transformation with business management, focusing on interdisciplinary project management, digital business models, and sustainability. Current roles: Dean, supervising professor for HTWK Robots/nao Team Research areas: Digital Transformation, Business Analytics, Industry 4.0, Stoffstrommanagement Research Trends : Recent publications emphasize digital solutions for environmental management, business process optimization, and smart urban logistics. His work connects Industry 4.0 with financial sustainability and societal impacts of digitalization. Projects : Leads Mittelstand-Digital Zentrum Leipzig-Halle, involved in EXIST-Potentiale, Future Parking, and FAssMII (Feedback-based E-Assessment in STEM).
Stefanie Jegelka is an Associate Professor (currently on leave) at the Massachusetts Institute of Technology's Department of Electrical Engineering and Computer Science, and a Humboldt Professor at Technical University of Munich. At MIT, she is a member of CSAIL (Computer Science and Artificial Intelligence Laboratory), IDSS (Institute for Data, Systems, and Society), the Center for Statistics and Machine Learning, and is affiliated with the Operations Research Center. Her educational background includes a PhD from ETH Zurich and the Max Planck Institute for Intelligent Systems, followed by postdoctoral research at UC Berkeley's AMPlab and computer vision group. Her research program focuses on algorithmic machine learning, with particular emphasis on exploiting mathematical structure for discrete and combinatorial machine learning problems, robustness in learning systems, and developing methods for scaling machine learning algorithms to large datasets. She has made significant theoretical contributions to submodular optimization and its applications in machine learning. Jegelka's publication record demonstrates a consistent focus on the intersection of discrete mathematics and machine learning. Her work spans theoretical foundations of optimization with discrete structures, applications in computer vision, and practical algorithms for submodular function optimization. Her research has evolved from foundational work on submodular functions to broader applications in deep learning and robust machine learning systems, showing increasing impact through numerous workshop best paper awards and high-impact conference publications. NSF CAREER Award Google Research Award German Pattern Recognition Award (Mustererkennngspreis) ICML Best Paper Award Sloan Research Fellowship DARPA Young Faculty Award NSF BIGDATA Award ONR MURI NSF AI Institute for Optimization Professor Jegelka has advised several successful students including Keyulu (recipient of MIT's George M. Sprowls Ph.D. Thesis Award), Derek (NSF Fellowship recipient), Ching-Yao (IBM Fellowship recipient), and Nisha (now Assistant Professor at Georgia Tech). Her research has been generously supported by multiple NSF grants, DARPA awards, and industry funding from Google, Two Sigma, and Adobe. She has also organized multiple workshops and tutorials on discrete optimization and submodularity in machine learning. At MIT, Jegelka is affiliated with the Center for Statistics and Machine Learning and collaborates with researchers across CSAIL. Her work bridges theoretical computer science, optimization, and practical machine learning applications, with recent focus on high-dimensional learning dynamics and in-context learning as evidenced by her group's multiple papers at leading conferences like ICLR.
Stephan J. Goetz is a Professor in the Department of Agricultural Economics, Sociology and Education at the College of Agricultural Sciences, Pennsylvania State University. He is based at 207C Armsby Building, University Park, PA 16802, and can be reached at sjg16@psu.edu. His research spans agricultural economics, regional development, and rural policy, with a strong emphasis on human and social capital, innovation, and community well-being. His research interests focus on the role of markets and human capital in economic growth and poverty reduction. Key areas include regional food systems, self-employment, social network analysis, targeted regional development, agritourism, direct farm sales, and the digital divide. His work often integrates data science, spatial analysis, and policy evaluation to understand rural economic dynamics. The recent publications highlight a consistent trend in analyzing rural innovation, food system resilience, and socioeconomic impacts of technology and crises. His work combines empirical methods with optimization models, often using county-level U.S. data. Themes include food hub logistics, cloud computing in rural economies, pandemic-related food insecurity, and gender impacts in farming. While no specific awards are listed, his extensive publication record in high-impact journals reflects scholarly recognition. He has collaborated with researchers across disciplines, suggesting active grant-funded projects and likely student mentorship, though formal advisees are not named. He is involved in research on equitable communities and the built environment, and affiliated with initiatives related to health and environmental sustainability. His work with extension services indicates engagement with public outreach and community development programs.
Federico Miretti is an Assistant Professor at the Polytechnic University of Turin, affiliated with the Department of Energy and the interdepartmental center Cars@PoliTo. His research focuses on hybrid and electric vehicles, with emphasis on energy management strategies, battery state estimation, and sustainable transport solutions. PhD in Energetics from Polytechnic University of Turin Research areas include: Optimization-based Energy Management Strategies for hybrid propulsion systems Simulation and digital twinning of hybrid systems Thermal management for electrified vehicles Techno-economic assessment of mobility solutions Recent publications highlight advancements in battery temperature anomaly detection, wireless power transfer feasibility, and control algorithms for energy efficiency. His work aligns with SDGs 7 (Clean Energy) and 9 (Innovation). Teaching roles include: Fluid Machinery (2019-2025) Energy Management in Hybrid/Electric Vehicles (2021-2025) Projects: PRoSIT (2025): Predictive thermal management demonstrator Consulting contract with MIDAC SpA (2025): Battery Digital Twin development EBOAT project (2025-2026): Technical support for Vulkan
Marshall L. Fisher is the UPS Professor of Operations, Information and Decisions at the Wharton School, University of Pennsylvania. His research focuses on retailing and supply chain management, with notable work in dynamic pricing, omnichannel operations, and workforce optimization. Academic Affiliation: Wharton School, University of Pennsylvania Research Themes: Retail innovation, supply chain responsiveness, labor economics Recent Trends: Real-time pricing algorithms, inventory-demand interactions, digital transformation Scientific Recognition: INFORMS Kimball Medal (2007) POMS Fellow (2005) INFORMS Fellow (2002) NAE Election (1994) Academic Contributions: Pioneering work on Lagrangian relaxation in integer programming (1981), Edelman Prize-winning liquid gas optimization, and groundbreaking research on retail staffing and training effectiveness. His teaching includes courses on global supply chain management and AI in business.
Prof. Dr. Seyhan ÖZTÜRK is an Associate Professor at Kafkas University's Faculty of Economics and Administrative Sciences, Department of Accounting. She has held full-time academic positions since 2010, progressing from Research Assistant to Associate Professor (2019–present). She also serves as the Head of the Accounting Department. Education: PhD in Accounting and Finance, Atatürk University (2011–2015) Master's in Business Administration, Istanbul University (2005–2011) Bachelor's in Business Administration, Istanbul University (2005–2009) Research Interests: Her work centers on Accounting Ethics, Forensic Accounting, and Internal Control, with applications in sustainability, corporate governance, and digital transformation. She explores ethical dilemmas in accounting, fraud detection methodologies, and the impact of regulatory frameworks on financial transparency. Publications: Her recent articles (2020–2025) emphasize sustainability accounting, financial performance analysis, and technology's role in accounting education. Themes include ESG metrics, bibliometric studies on climate accounting, and ethical challenges in SME financial reporting. Advising & Grants: She has supervised 16+ graduate students (PhD/Master’s) in topics like accounting ethics and financial modeling. She led a research project (2019–2021) testing bankruptcy prediction models on the Borsa Istanbul exchange.
Prof. Dr. Bernd Skiera is a leading Marketing Professor at Goethe University Frankfurt since 1999 and a member of the managing board of the efl - The Data Science Institute. His work bridges information systems and marketing, with a focus on data-driven decision making and digital transformation.
Hakan Aydin is a Professor and Director of the PhD Program in the Department of Computer Science at George Mason University's Volgenau School of Engineering. He has been teaching at George Mason University since 2001 and has established himself as a leading researcher in real-time embedded systems and energy-aware computing. Education: PhD in Computer Science from the University of Pittsburgh (2001) Hakan Aydin's research primarily focuses on sustainable computing, real-time embedded systems, fault tolerance, Internet-of-Things, and cyber-physical systems. His work bridges theoretical foundations with practical implementations, particularly in energy management for real-time systems. He has developed innovative techniques for reliability-aware power management, dynamic voltage scaling, and energy harvesting in wireless sensor networks. His research has significant implications for extending battery life in mobile devices, improving reliability in safety-critical applications, and enabling sustainable computing practices. Aydin's publications reveal a consistent research trajectory centered around energy efficiency and reliability in real-time systems. His work spans theoretical algorithm development, system-level implementation, and experimental validation. A notable trend is the evolution from single-processor systems to multicore and heterogeneous architectures, reflecting industry trends. His recent work increasingly addresses security aspects of real-time systems and the integration of IoT technologies. Scientific Awards: National Science Foundation CAREER Award (2006) George Mason University Computer Science Department Teaching Award (2006, 2009) Best Paper Award at IEEE Green and Sustainable Computing Conference (IGSC'20) Best Student Paper Award at IEEE International Conference on Embedded Software and Systems (ICESS'15) Best Paper Award at IEEE International Conference on Embedded Computing (EmbeddedCom'14) Best Paper Award at International Workshop on Highly-Reliable Power-Efficient Embedded Designs (HARSH'13) Best Paper Award at ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems (MSWIM'11) Hakan Aydin has advised seven PhD students to completion, including Vinay Devadas (2011), Baoxian Zhao (2012), Bo Zhang (2012), Mohammad Atiqul Haque (2016), Maryam Bandari (2016), Arda Gumusalan (2019), and Abhishek Roy (2021). His research has been generously supported by the National Science Foundation through multiple grants, including CSR: Small: Collaborative Research: Towards Reliability-Centric Real-time Computing on Heterogeneous Chip Multiprocessor Systems (2014-2017), CSR: Small: Energy Harvesting for Performance Sensitive Wireless Sensor Networks (2011-2015), and CSR: Small: Collaborative Research: Generalized Reliability-Aware Power Management for Real-Time Embedded Systems (2010-2014). Prof. Aydin has held significant leadership roles in the academic community, serving as the Technical Program Committee Chair of the IEEE RTAS 2011 and General Chair of IEEE RTAS 2012. He is also a member of the Editorial Board of Journal of Real-Time Systems (Springer). His work has established foundational principles in reliability-aware energy management for real-time systems, influencing both academic research and industrial practices in embedded computing.
Salim El Rouayheb is an Associate Professor in the Department of Electrical and Computer Engineering at Rutgers University. He leads the Coding and Securing Information (CSI) Lab, which focuses on information-theoretic security and privacy in distributed systems. His research spans multiple areas including secure machine learning, private information retrieval, and data synchronization. Dr. El Rouayheb received his Ph.D. in Electrical Engineering from Texas A&M University in 2009. Prior to joining Rutgers, he was an Assistant Professor at the Illinois Institute of Technology (2013-2017), a Research Scholar at Princeton University (2012-2013), and a Postdoctoral Researcher at UC Berkeley (2010-2011). His research interests focus on information-theoretic security in distributed systems, private information retrieval and search, secure machine learning algorithms, and data synchronization in distributed systems. He has made significant contributions to developing frameworks that provide information-theoretic privacy guarantees in various contexts including federated learning, genomic data analysis, and decentralized networks. His work often bridges theoretical foundations with practical applications, particularly in the areas of secure distributed computing and privacy-preserving algorithms. His recent publications demonstrate a strong trend toward applying information-theoretic principles to address privacy and security challenges in machine learning systems, particularly in federated and decentralized settings. Many of his papers explore random walk approaches for decentralized learning, secure matrix multiplication techniques, and privacy mechanisms that can be toggled "on and off" based on correlation patterns in data. His work spans both theoretical contributions in information theory and practical implementations for real-world systems. Dr. El Rouayheb has received several prestigious awards including the NSF CAREER Award (2016), Google Faculty Research Award (2018), and the Rutgers University Walter Tyson Junior Faculty Chair (2019). He has successfully secured multiple research grants including NSF SaTC, NSF CAREER, Google Faculty Research Awards, and Army Research Lab funding. His lab, the Coding and Securing Information (CSI) Lab, currently includes postdoc Xingran Chen, PhD student Zonghong Liu, and undergraduate researchers. The CSI Lab maintains an active research agenda with regular publications in top-tier venues and hosts the Shannon Channel, a series of online talks related to information theory. Dr. El Rouayheb is also involved in organizing workshops on coding theory and information security.
Salem Lahlou is an Assistant Professor in the Machine Learning Department at the Mohamed bin Zayed University of Artificial Intelligence (MBZUAI), having joined in September 2024. He previously served as a Senior Researcher at the Technology Innovation Institute (TII) in 2024. His academic background includes a PhD from Mila and Université de Montréal (UdeM) under Yoshua Bengio (2023), with prior studies in applied mathematics at École Polytechnique and statistical learning at École Normale Supérieure Paris-Saclay. His research focuses on developing more capable and reliable AI systems through three interconnected pillars: Novel Method Development : Core contributions to Generative Flow Networks (GFlowNets), uncertainty estimation techniques (DEUP), and curriculum learning frameworks Large Language Model Advancement : Enhancing reasoning capabilities and alignment through preference optimization and trace-based learning Community Tooling : Creation of torchgfn library for GFlowNets and benchmarks including BabyAI, FinChain, and LLM-BabyBench Core research areas span Machine Learning, GFlowNets, Uncertainty Estimation, LLM Reasoning, Reinforcement Learning, and AI for Science. Recent publications (2023-2025) demonstrate strong emphasis on GFlowNet theory/improvements (8+ papers), LLM reasoning evaluation (FinChain, LLM-BabyBench), uncertainty quantification, and societal AI impacts. Key application domains include mathematical reasoning, financial systems, privacy preservation, and cognitive science. He currently advises graduate students including Junyi (privacy risks in SNNs) and Abhijith (LLM reasoning). His group collaborates with MBZUAI faculty (Nils Lukas, Alham Fikri, Mingming Gong, Martin Takac) and industry partners on projects involving Conversational AI, Personalization, and Affective AI.
Rhett C. Smith is a Professor of Chemistry at Clemson University, leading a research group dedicated to sustainable materials innovation since 2006. His work focuses on transforming industrial waste streams into high-performance composites through green chemistry approaches. His academic background includes: B.S. in Chemistry from the University of Toledo Ph.D. in Chemistry from Case Western Reserve University NIH Postdoctoral Fellowship at MIT Professor Smith's research pioneers waste valorization using elemental sulfur and biomass derivatives. Key areas include: Upcycling mixed plastic and food waste into structural materials Developing sulfur-based polymers for sustainable construction Creating circular economy solutions for agricultural byproducts His group's work bridges fundamental chemistry with commercial applications in South Carolina's industrial sector. Recent publications reveal a strong trend toward atom-economical processes using waste sulfur and biomass. The research emphasizes scalable technologies for plastic recycling and sustainable cement alternatives, with increasing focus on food waste upcycling and flame-retardant composites. Major recognitions include: National Merit Scholar and NIH Postdoctoral Fellowship Two-time InnoVision Award Finalist (2024 Sustainability category) Fats and Proteins Research Foundation Innovate Award Fred Bisplingoff Research Innovation Award Professor Smith has mentored over a dozen Ph.D. students to successful careers in national labs and industry. His group secured seven major grants in Spring 2024 from NSF, USDA, and industry partners to advance sustainable materials for structural applications. Current projects focus on upcycling post-consumer waste streams and developing carbon-negative building materials. The Smith Research Group operates as a collaborative hub within Clemson's chemistry department, recently expanding to include four faculty co-leaders (Tennyson, Ashlyn Smith, and Sauceda). The team maintains strong industry partnerships while promoting academic accessibility through open educational resources.
Vinod M. Vokkarane is a Professor in the Department of Electrical and Computer Engineering at the University of Massachusetts Lowell, where he serves as Director of the Center for Smart Cyber-Physical Systems (SCyPS) and Director of Advanced Computer Network Labs. Previously, he was an Associate Professor at University of Massachusetts Dartmouth from 2004 to 2013 and a Visiting Scientist at MIT's Research Laboratory of Electronics from 2011 to 2014. His extensive research portfolio spans multiple domains of advanced networking and cyber-physical systems. Dr. Vokkarane earned his educational foundation with a B.S. from University of Mysore, India (1999), followed by an M.S. (2001) and Ph.D. (2004) in Computer Science from the University of Texas at Dallas. His dissertation focused on optical burst-switched networks, establishing the foundation for his future research trajectory. His research interests center on Cyber-Physical Systems, Network Optimization, Reliability, Smart Grids, and Cyber-Security, with particular expertise in the design, analysis, and modeling of architectures, protocols, and algorithms for ultra-high speed networks including Optical networks, Grid/Cloud networks, and Big-data networks. His work bridges theoretical foundations with practical implementations, often addressing critical challenges in network reliability, security, and efficiency. His research has received significant recognition through numerous best paper awards and substantial external funding. Analysis of his recent publications reveals a clear evolution toward increasingly sophisticated integration of cyber-physical systems with power infrastructure, particularly in the areas of grid resilience and observability. His work has expanded from fundamental optical networking research to address critical infrastructure challenges, with a growing emphasis on machine learning applications for network optimization and power system monitoring. The recent focus on PMU networks, disaster resilience, and cyber restoration demonstrates his strategic pivot toward addressing national security and critical infrastructure protection challenges. UMass Dartmouth Scholar of the Year Award (2011) UMass Dartmouth Chancellor's Innovation in Teaching Award (2010-11) University of Texas at Dallas Computer Science Dissertation of the Year Award (2003-04) Multiple Best Paper Awards including IEEE GLOBECOM 2005, IEEE ANTS 2010, ONDM 2015, ONDM 2016, and IEEE ANTS 2016 Texas Telecommunications Engineering Consortium Fellowship (2002-03) Dr. Vokkarane has successfully mentored numerous graduate students who have contributed significantly to his research projects, with several going on to successful careers in academia and industry. His research has been consistently supported by major funding agencies including NSF, DOE, and USMC, with recent projects totaling over $5 million in funding. Current projects include Unified Post-Disaster Restoration Planning for Cyber-Physical Power Distribution Systems (ONR, $550K), CyberCARE: Northeast University Cybersecurity Center (DOE, $3.5M), and Flexible Spectrum Allocation in Next-Generation Optical Networks (NSF, $350K). He leads the Center for Smart Cyber-Physical Systems (SCyPS) and Advanced Computer Network Labs at UMass Lowell, where his research teams work on cutting-edge problems in network architecture, cyber-physical security, and infrastructure resilience. His labs collaborate extensively with national laboratories and industry partners to translate theoretical advances into practical solutions for real-world infrastructure challenges.
Thomas Rüde is Universitätsprofessor for Hydrogeology at RWTH Aachen University , Germany, where he leads the Hydrogeology group within the Faculty of Georesources and Materials Engineering. Holding the chair since 2005, he also serves as Managing Director of the Vereinigung Aachener Geowissenschaftler e.V. and has previously been Vice-President (2008-2014) and Executive Council member (2000-2008) of the International Mine Water Association (IMWA). Education 2004 – Privatdozent (Dr. rer. nat. habil.), University of Munich 1995 – Dr. rer. nat., University of Karlsruhe 1991 – Diplom-Geologe, University of Karlsruhe Research focus Professor Rüde’s work centres on understanding and modelling flow and reactive transport in complex aquifer systems . Key themes include: Contaminant hydrogeology – behaviour of geogenic arsenic and uranium in groundwater Groundwater protection and remediation – risk assessment and mitigation strategies Mine-water management – acid mine drainage, dewatering-well clogging, post-mining landscapes Tracer and hydraulic testing – field experiments to quantify subsurface heterogeneity Numerical modelling – high-performance simulation of multi-aquifer systems and karst His research spans Europe (Germany, Austria, Netherlands), Latin America (Mexico, Indonesia) and South-East Asia, frequently in close collaboration with local universities and industry partners. Publication trends Since 2010, Rüde has published extensively on geogenic contamination (As, U, F) in sedimentary and volcanic aquifers, mine-water impacts , and karst hydraulics . Recent work (2022-24) highlights advanced environmental tracers (gadolinium), transboundary groundwater issues, and the sustainable management of post-mining landscapes under climate change. Numerical models range from site-scale dewatering optimisation to catchment-scale coupled flow-transport simulations. Scientific awards & recognition Best Teaching Award 2010 – RWTH Aachen University Best Teaching Award 2012 – RWTH Aachen University Best Teaching Award 2014 – RWTH Aachen University Supervision & academic service Since 1998 he has taught hydrogeology through lectures, seminars, laboratory and field courses, and computer-based modelling labs. To date he has supervised: 13 PhD candidates 34 Diploma students 57 MSc students 63 BSc students He is Chairman of the Study Commission for the BSc programme in Georesources Management at RWTH Aachen, ensuring curriculum development and quality assurance. Laboratory & field infrastructure His group operates modern hydrochemical laboratories for trace-element analyses and maintains field stations for tracer experiments in Germany, Mexico and Indonesia. High-performance computing resources (in collaboration with the Jülich Supercomputing Centre) enable large-scale groundwater modelling and Monte-Carlo uncertainty assessments.
Professor John D. Cressler is a tenured faculty member at the Georgia Institute of Technology, holding a position within the School of Electrical and Computer Engineering in the College of Engineering. His research focuses on cutting-edge semiconductor technologies, particularly silicon-germanium heterojunction bipolar transistors (SiGe HBTs) for mixed-signal applications spanning RF, microwave, mm-wave, analog, and digital domains. His research interests center on atomic-scale bandgap engineering for next-generation semiconductor devices, with emphasis on SiGe HBT technology development, radiation-hardened circuits for space applications, cryogenic electronics, and device-circuit interactions. His team explores fundamental device theory, broadband noise analysis, profile optimization, 2-D/3-D simulation, compact modeling, and radiation effects. Current projects include Europa-surface mission electronics, D-band/sub-THz systems, and radiation-tolerant receiver designs. Analysis of his 15 most recent publications (2024-2025) reveals a dominant focus on radiation-hardened electronics for space applications (40% of works), millimeter-wave circuit design (30%), and SiGe HBT reliability optimization (30%). Key trends include Europa mission electronics development, D-band/sub-THz circuit innovation, and advanced radiation mitigation techniques using SiGe BiCMOS technology. Professor Cressler teaches multiple courses including ECE 3040 (Microelectronic Circuits), ECE 3450 (Semiconductor Devices), ECE 6444 (Silicon-Based Heterostructure Devices and Circuits), and the interdisciplinary IAC 2002 course on Science, Engineering and Religion. His research is supported by industrial collaborations and Georgia Tech facilities including the Georgia Electronic Design Center (GEDC), NanoTECH, and C-STAR.
Professor Ingrid Undeland leads the Marine research group at the Division of Food and Nutrition Science, Department of Life Sciences at Chalmers University of Technology. She is a distinguished researcher with expertise spanning marine food science, lipid chemistry, and blue biorefining, having established herself as a leading figure in sustainable seafood research and marine biotechnology. Her educational background includes food science studies from Linnaeus University and a PhD in bioscience from Chalmers University of Technology and SIK (now RISE). Between 1999-2002, she was a post-doctoral fellow at University of Massachusetts Marine Station, which significantly shaped her research trajectory in marine food science. Professor Undeland's research focuses on pioneering next-generation seafood through innovative value chains from seaweed, small pelagic fish, fish side streams, mussels, and microalgae. Her specialized expertise lies in marine lipids and proteins, particularly their stabilization, isolation from complex sources, and nutritional properties including digestibility. She has extensive experience with antioxidant strategies using plant-derived side streams or extracts and fundamental studies of fish hemoglobins as pro-oxidants. Her work also encompasses innovative technologies for biomass fractionation and nutrient recycling to build blue biorefineries, along with in vitro digestion models and general seafood analytics. Beyond marine research, she explores filamentous fungi as sustainable alternative food protein sources. The trends in her recent publications reveal a strong emphasis on valorizing marine resources through advanced processing techniques. Her work increasingly focuses on sustainable extraction methods for seaweed proteins, particularly Ulva fenestrata, and developing antioxidant strategies using berry side streams to stabilize fish proteins. There's a growing interest in understanding the nutritional properties and digestibility of alternative marine proteins, along with environmental assessments of processing technologies. Her research consistently bridges fundamental science with practical applications for creating sustainable seafood value chains. Swedish representative in Nordic Lipidforum, WEFTA, and EuCheMS Editorial board member of Journal of the Aquatic Food Product Technology Member of the National Committee for Nutrition and Food Science at the Royal Swedish Academy of Sciences Co-founder of the startup company AquaFood H-index of 47 according to Google Scholar Professor Undeland has an extensive record of academic mentorship, having supervised or currently supervising 23 PhD students, 14 postdoctoral researchers, and examining over 25 MSc students. Her research is supported by numerous grants, including the WaSeaBi Project which focuses on valorizing seafood side-streams through holistic value chain design. She collaborates with various industry partners and academic institutions across Europe. Her laboratory includes technicians Dr. Karin Larsson and Dr. Rikard Fristedt, and she leads a dynamic research team working on multiple projects related to marine biorefining and sustainable seafood development. Her research group operates within well-equipped facilities at Chalmers University, with specialized laboratories for marine food analysis, protein extraction, lipid oxidation studies, and in vitro digestion modeling. The team also maintains cultivation systems for seaweed and filamentous fungi, enabling integrated research from raw material production to final product development.
