Prof. Laura Busse is a Professor at Ludwig Maximilian University of Munich (LMU), leading the Research Group in the Department of Biology II, Division Neurobiology. She holds roles as a Regular Member of MCN, Full Member of GSN, and Deputy Head of the GSN Examination Board. Her research focuses on cellular and systems neuroscience, particularly investigating how contextual information influences visual perception through neural circuits in mice. Key areas include feedback mechanisms, behavioral state effects, and thalamocortical interactions. Her work employs advanced techniques like high-density extracellular recordings and optogenetics to study active behavior in rodents. Current students include Simon Renner, Gregory Born, and others. Recent research highlights include studies on corticothalamic feedback effects, thalamic spatial integration, and the role of pupil dynamics in neural activity. She leads the Vision Circuits Lab (https://visioncircuitslab.org), exploring how sensory inputs and brain states shape visual processing. Her articles reveal trends in understanding thalamocortical communication, adaptive sensory systems, and the biological basis of neural network models. She coordinates the SPP2411 project on cortico-subcortical loops, emphasizing interdisciplinary neuroscience.
David Tindall is a Professor in the Department of Sociology at the University of British Columbia's Faculty of Arts. His research examines environmental contention, social movements, and climate change, with a focus on British Columbia and Canada. He investigates the interplay between social networks, movement identification, and participation, covering topics like forestry conflicts, wilderness preservation, and media representation of environmental issues. Research Interests: Tindall's work spans: Environmental movements and activism Social network analysis in conservation contexts Climate change perceptions and justice Gender dimensions of environmentalism Media framing of ecological conflicts His current SSHRC-funded project analyzes sociological aspects of climate change contention in Canada. Publications: Tindall's recent articles (2010-2002) focus on environmental networks, activism dynamics, and forest value conflicts, demonstrating consistent emphasis on social structural analyses of ecological issues in British Columbia. Grants: Holds active funding from the Social Sciences and Humanities Research Council (SSHRC) for research on personal networks and movement participation.
Daria Nemashkalo is a researcher affiliated with the Digital Society Institute and Radio Systems at the University of Twente. Her work focuses on electromagnetic interference (EMI) filter design, time-domain analysis, and multichannel systems, particularly in power electronics and three-phase applications. Key Research Areas: EMI filter performance, mode decomposition, common mode choke saturation, and time-domain measurement techniques. Contributions: Published extensively on EMI mitigation strategies and filter optimization, including work on multichannel testing and real-world implementation challenges. Collaborations: Active in electromagnetic compatibility symposia, notably with peers like Peter Koch and Frank Leferink.
Sanjay Srinivasan is a Professor of Petroleum and Natural Gas Engineering and the John and Willie Leone Family Chair in the Department of Energy and Mineral Engineering at Penn State University. He serves as Director of the EMS Energy Institute and leads the Penn State Initiative for Geostatistics and GeoModeling Applications. His research focuses on petroleum reservoir characterization, CO2 sequestration, and integration of seismic data in reservoir models through advanced geostatistical and machine learning methods. Ph.D., Petroleum Engineering, Stanford University M.S., Petroleum Engineering, University of Southern California B. Tech, Petroleum Engineering, Indian School of Mines Srinivasan’s work addresses reservoir recovery processes, unconventional reservoirs, and subsurface energy security. His methodologies include probabilistic modeling, data assimilation, and AI-driven workflows for fracture network mapping and porous media generation. Key applications span Gulf of Mexico deepwater plays and geological carbon storage. Recent publications highlight trends in: Reinforcement learning for geostatistical workflows and well optimization Physics-informed GANs for 3D porous media modeling Probabilistic integration of geomechanical and geostatistical inferences Machine learning approaches for seismic fracture identification CO2 sequestration in heterogeneous reservoirs Scientific awards include Distinguished Member (SPE, 2022), SPE Faculty Pipeline Award (2012), Cox Visiting Fellowship (Stanford, 2010), and SPE Southwest Region Reservoir Description Award (2009).
Evita Papazikou serves as a Lecturer in Transport Engineering at the School of Engineering, University of the West of England (UWE Bristol), where she contributes to the Centre for Transport and Society and collaborates with the Bristol Robotics Laboratory's Connected & Autonomous Vehicles Centre. Her academic qualifications include: Civil Engineering (BEng and MEng) from Aristotle University of Thessaloniki MSc in Planning, Organisation, and Management of Transport Systems, Aristotle University of Thessaloniki PhD in Automated Systems and Driver Behaviour (Road Safety) from Loughborough University, sponsored by the Insurance Institute for Highway Safety with access to SHRP2 NDS data Dr. Papazikou's research focuses on road safety, connected and automated vehicles, driver behaviour analysis, and smart infrastructure. She investigates accident causation through statistical modeling, develops driver monitoring systems, and explores human factors in transportation. Her work integrates traffic simulation with mobility data fusion from vehicles, sensors, and infrastructure to enhance safety in future mobility systems, particularly in cooperative, connected, and automated environments. Her recent publications (2023-2025) reveal a concentrated research trajectory examining safety impacts of dedicated lanes for autonomous vehicles, parking policy implications in automated eras, and driver fatigue management. She consistently employs naturalistic driving data and traffic microsimulation to analyze driver-vehicle-environment interactions, with increasing emphasis on real-world intervention effectiveness and environmental sustainability in mobility systems. Scientific Awards: No specific awards were mentioned in the provided information. Dr. Papazikou has secured significant research funding through competitive programs including Horizon 2020, Innovate UK, and the Department for Transport. Her project portfolio demonstrates substantial industry collaboration, particularly with Ford, and includes: LEVITATE: Assessing societal impacts of Connected and Automated Vehicles SafetyCube: Developing an innovative road safety decision support tool i-DREAMS: Creating a smart driver and road environment assessment system DDRST: Building a data-driven road safety tool for hotspot identification TRIP: Developing a driver culpability assignment tool for road injury prevention She actively contributes to interdisciplinary research through her affiliations with the Centre for Transport and Society and the Bristol Robotics Laboratory's Connected & Autonomous Vehicles Centre, where she bridges engineering, human factors, and policy development for next-generation transportation systems.
Dr. Lida Derevnina is a leading researcher in plant-pathogen interactions and immune receptor networks at the University of Cambridge , affiliated with the School of Biological Sciences and the Department of Plant Sciences . She heads the Crop Pathogen Immunity Group at the Crop Science Centre , focusing on NLR (Nucleotide-binding and Leucine-Rich Repeat) immune receptor networks and pathogen effector functions to engineer durable crop resistance. Education: PhD in Plant Pathology and Phytopathology, University of Sydney (2008-2012) BSc in Agricultural Science, University of Sydney (2004-2007) Her research explores how pathogens evade plant immunity through effector proteins and how NLR networks can be bioengineered to counteract these mechanisms. This work bridges molecular biology, evolutionary genetics, and sustainable agriculture, with recent advances in resistosome activation models and effectorome characterization. Scientific awards include the Crop Science Centre Fellowship (2022) , Marie Skłodowska-Curie Individual Fellowship (2016) , and the Jeanie Borlaug Laube Women in Triticum Award (2012) . Her work has been published in top journals such as Science , Nature , and PLoS Biology . Dr. Derevnina is actively engaged in public outreach, including the Talking Biotech podcast and a YouTube video explaining plant immunity . Her laboratory collaborates on projects related to global food security and pathogen genomics.
Prof. Dr.-Ing. habil. Gero Mühl is a W2-Professor at the University of Rostock, where he holds the chair for "Architecture of Application Systems" since October 2009. His academic journey includes positions as a Heisenberg Fellow at the Technical University of Berlin (2009), postdoctoral research at TU Berlin (2002-2009), and doctoral studies at TU Darmstadt where he received his Dr.-Ing. degree with distinction in 2002. He completed dual Diplomas in Computer Science (Dipl.-Inform.) and Electrical Engineering (Dipl.-Ing.) from FernUniversität in Hagen in 1998. Prof. Mühl's research focuses on Self-Organizing Distributed Systems , with particular expertise in distributed systems, distributed algorithms, event-based systems, middleware, energy-efficient systems, organic computing, sensor networks, web services, and electronic commerce. His work bridges theoretical foundations with practical implementations in real-world distributed environments. His recent publications show a strong trend toward time-sensitive networking, content-based publish/subscribe systems, and P4 programmable data planes. These works address critical challenges in industrial communication, real-time systems, and network reliability. His research group has made significant contributions to making distributed systems more autonomous, reliable, and efficient. Scientific awards and recognitions include: Nomination for the Berlin Science Award for Young Scientists (2008) Heisenberg Fellowship by the German Research Foundation (DFG) (2008) Best paper award in System Software and Security at SAC 2015 Prof. Mühl has been actively involved in numerous research projects and collaborations, particularly focusing on self-organizing and self-stabilizing systems. His work on the REBECA publish/subscribe middleware represents a significant contribution to autonomous distributed systems. He has supervised numerous students and researchers, contributing to the development of the next generation of computer scientists specializing in distributed systems. His laboratory at the University of Rostock focuses on practical implementations of self-organizing distributed systems, with current projects investigating time-sensitive networking, publish/subscribe systems, and energy-efficient distributed computing. The team combines theoretical analysis with practical system development to address real-world challenges in industrial and commercial applications of distributed systems.
Graeme B. Dinwoodie is a University Distinguished Professor and Global Professor of Intellectual Property Law at Chicago-Kent College of Law, Illinois Institute of Technology, where he also serves as Co-Director of the Program in Intellectual Property Law. He has held prestigious academic positions at the University of Oxford (2009-2018), where he was Director of the Oxford Intellectual Property Research Centre and a Professorial Fellow of St. Peter's College, and Queen Mary College, University of London (2005-2009). Prior to his Oxford appointment, he led Chicago-Kent's intellectual property program for several years. Dinwoodie earned his J.S.D. from Columbia Law School, LL.M. from Harvard Law School, and LL.B. in Private Law (first class honors) from the University of Glasgow. He was the Burton Fellow at Columbia Law School (1988-89) and a John F. Kennedy Scholar at Harvard Law School (1987-88). Before entering academia, he practiced intellectual property law at Sullivan and Cromwell in New York. A leading international authority in trademark law, design law, and international intellectual property law, Dinwoodie's research focuses on the intersection of national and international IP systems, trademark theory and doctrine, and the evolving landscape of digital copyright. His work explores how trademark law serves consumer interests, the challenges of harmonizing IP systems across jurisdictions, and the role of international organizations like WIPO in shaping global IP norms. He has made significant contributions to understanding territoriality in trademark law and the impact of digital technologies on IP enforcement. Dinwoodie's extensive publication record reveals a consistent focus on the tension between national sovereignty and international harmonization in intellectual property law. His recent work examines the implications of Brexit for IP systems, the evolving role of internet intermediaries in IP enforcement, and the normative foundations of trademark law. He has increasingly focused on the practical application of IP law in digital contexts while maintaining his foundational work on international IP architecture. Scientific Awards and Recognition: Inducted into the IP Hall of Fame (2020) Recipient of the Ladas Memorial Award from the International Trademark Association (2008) Awarded the Pattishall Medal for Teaching Excellence in trademarks and trade identity law (2008) Three-time recipient of the Goldman Prize for Excellence in Teaching (University of Cincinnati) Elected to membership in the American Law Institute (2003) Named Norman and Edna Freehling Scholar (2001) Dinwoodie has served in significant advisory roles, including as a consultant to the World Intellectual Property Organization on private international law matters, an adviser to the American Law Institute Project on Principles on Jurisdiction and Recognition of Judgments in Intellectual Property Matters, and a consultant to the United Nations Conference on Trade and Development on the Protection of Traditional Knowledge. He currently serves as an adviser on the ALI's project on the Restatement of Copyright Law. He has held leadership positions as past chair of the Intellectual Property Section of the Association of American Law Schools and president of the International Association for the Advancement of Teaching and Research in Intellectual Property (ATRIP) from 2011 to 2013. As Co-Director of the Intellectual Property Program at Chicago-Kent, Dinwoodie helps shape one of the nation's leading IP law programs. His work with the Center for Design, Law & Technology reflects his commitment to addressing contemporary challenges at the intersection of law and innovation. Through his extensive scholarship, teaching, and professional service, Dinwoodie continues to influence both the theoretical foundations and practical applications of intellectual property law worldwide.
Zelmina Lubovac is a Senior Lecturer in BioInformatics at the School of Bioscience, University of Skövde. She serves as both a Course Coordinator for multiple undergraduate and graduate courses in bioinformatics and a Programme Coordinator for Master's level programs. Her academic work focuses on the intersection of computational methods and biological applications, particularly in disease analysis and biomarker discovery. Dr. Lubovac's research spans several key areas in bioinformatics and systems biology: Disease module identification in complex biological networks Multi-omics integration (genomics, proteomics, metabolomics) for biomarker discovery Machine learning applications in RNA-seq and other high-throughput biological data Development of bioinformatics software tools for network analysis miRNA analysis in cancer and neurological disorders Her recent publications (2022-2024) demonstrate a strong focus on applying computational approaches to understand disease mechanisms, particularly in pancreatic cancer and multiple sclerosis. She has developed several widely-used bioinformatics tools including MODalyseR, MODifieR, and TFTenricher that facilitate disease module analysis and gene network interpretation. Her work often involves collaborative research with clinical teams to translate computational findings into potential diagnostic applications. Dr. Lubovac has been involved in significant research projects including: BIO-AID (Biomedical AI-driven data analytics): Oct 2020 - Sep 2024 Systems Biology DMDPipe: Mar 2018 - Feb 2021 She actively contributes to both undergraduate and graduate education at the University of Skövde, coordinating multiple courses and programs in bioinformatics and bioscience, with a clear emphasis on preparing students for careers at the intersection of biology and computational science.
Antonio Alguacil Cabrerizo is an Assistant Professor (starting 2025) at Université de Sherbrooke, where he currently serves as a Postdoctoral Fellow (2023-2025). His academic trajectory includes dual doctoral degrees in Mechanical Engineering from Université de Sherbrooke and École Nationale Supérieure d'Aéronautique et de l'Espace, complemented by aerospace engineering degrees from ENSEEIHT and Universidad Politécnica de Madrid. His research integrates computational fluid dynamics with machine learning, focusing on: Aeroacoustic prediction and noise source identification Deep learning surrogates for fluid and acoustic systems Turbomachinery and airfoil aerodynamics Data-driven modeling of spatiotemporal physical systems This work advances computational efficiency in simulating complex wave propagation, turbulence effects, and fluid-structure interactions. Publication analysis reveals consistent focus on developing neural network-based computational methods for aeroacoustics and fluid dynamics. His 15 most recent works demonstrate progressive refinement in applying convolutional architectures to predict acoustic scattering, refraction phenomena, and turbomachinery noise with increasing physical accuracy and computational efficiency. Awards and recognition include: Top 5 in AIAA Best Student Paper in Aeroacoustics (2024) Graduate Scholarship Award from CFD Society of Canada (2022) Eureka Scholarship from Université de Sherbrooke (2021) Best Poster Prize at CRASH Day (2021) He secured a $70,000 CAD startup grant (2025-2028) from Université de Sherbrooke for establishing his research program. No student advising relationships or laboratory affiliations are currently documented.
Nakul Gopalan serves as an Assistant Professor at Arizona State University's School of Computing and Augmented Intelligence (SCAI) in Tempe, where he founded and leads the Logos Robotics Lab since joining in August 2022. His academic foundation was established through a PhD in Computer Science from Brown University completed in 2019. Education: PhD in Computer Science, Brown University (2019) Research Focus: Dr. Gopalan pioneers work at the critical intersection of language grounding and robot learning, developing algorithms that enable robots to interpret natural language instructions and learn from human demonstrations. His research directly addresses real-world usability challenges by focusing on hierarchical reinforcement learning, task planning, and human-robot collaboration frameworks that empower non-expert users to train robots for home and office environments. Key innovations include plannable representations for natural language instruction following and transfer learning techniques for robotic task execution. Publication Evolution: Recent publications (2023-2025) demonstrate accelerating specialization in language-conditioned robot learning, with 80% of his latest work exploring compositional instruction following, novice-user teaching interfaces, and explainable AI for robotics. His research trajectory shows a deliberate shift from foundational language grounding (2017-2020) toward practical human-robot collaboration systems, evidenced by increased focus on hardware-software co-design, cross-embodiment transfer, and clinical applications of explainable AI in neurology support systems. Scientific Recognition: Best Paper Award at RoboNLP workshop (Association for Computational Linguistics) 2017 RSS 2023 Best Student Paper Finalist Mentorship & Service: As lab director, Dr. Gopalan actively mentors graduate researchers while teaching core courses including Data Structures and Algorithms (CSE 310) and specialized seminars on robot learning. His significant service contributions include organizing the RSS 2021 "Robotics for People" workshop, serving as Action Editor for ICRA 2023/2024, and extensive reviewing for top-tier robotics conferences (RSS, ICRA, CORL) and AI venues (NeurIPS, AAAI). Research Infrastructure: The Logos Robotics Lab operates as his primary research vehicle, focusing on natural language interfaces for robot training, hierarchical task decomposition, and real-world deployment of language-grounded learning systems. Current projects integrate large language models with robotic control frameworks to enable zero-shot task generalization across different robot embodiments.
Matthew J. Graham is a Research Professor of Astronomy at the California Institute of Technology (Caltech), serving as the Project Scientist for the Zwicky Transient Facility (ZTF). His work bridges astronomy, machine learning, and data science, focusing on time-domain sky surveys that produce hundreds of thousands of public transient alerts per night. Previously, he has worked on the Catalina Real-time Transient Survey (CRTS), NOAO DataLab, Virtual Observatory, and Palomar-Quest Digital Sky Survey. Dr. Graham's primary research interests involve applying machine learning and advanced statistical methodologies to astrophysical problems, particularly the variability of quasars and other stochastic time series. His work addresses the unprecedented data volumes generated by 21st-century astronomy while expanding our ability to work with complex information systems beyond simple correlations. His current projects include real-time low latency inferencing via the NSF-funded A3D3 Institute, reinforcement learning for optimizing astrophysical follow-up campaigns, neural differential models for supermassive black hole variability, and functional analysis of multivariate time series. Analysis of Graham's recent publications reveals a strong focus on time-domain astronomy, particularly leveraging the capabilities of the Zwicky Transient Facility. His work spans multiple areas including gravitational wave counterpart identification, active galactic nuclei variability, supernova characterization, and machine learning applications for transient detection. A notable trend is the integration of artificial intelligence techniques to handle the massive data streams from modern sky surveys, enabling real-time analysis and decision-making that would be impossible with traditional methods. Dr. Graham has been instrumental in developing infrastructure for time-domain astronomy, including the alert distribution system for ZTF and data processing pipelines for handling massive transient datasets. His work on the Catalina Real-time Transient Survey established important methodologies for identifying variable and transient sources that continue to influence the field. As Project Scientist for ZTF, Graham leads a major international collaboration involving Caltech, IPAC, and numerous partner institutions worldwide. The facility represents a significant advancement in time-domain astronomy, providing unprecedented coverage of the dynamic sky and enabling discoveries across multiple areas of astrophysics.
Nidhi Singal serves as Professor of Disability and Inclusive Education at the University of Cambridge's Faculty of Education and holds the position of Vice President at Hughes Hall. Her academic leadership extends to roles as Trustee of the Cambridge Trust and UKFIET, alongside significant contributions to global education initiatives through the World Bank, UNESCO, and UNPRPD. Her educational background includes a PhD and MPhil from the University of Cambridge, complemented by an M.A. and B.A. (Honours) in Applied Psychology from the University of Delhi. This clinical psychology foundation informs her distinctive approach to educational research. Singal's research centers on educational equity for marginalized groups in Southern contexts, with particular emphasis on children with disabilities in South Asia and Africa. She pioneers culturally-sensitive methodological frameworks that challenge power imbalances in North-South research partnerships and prioritize ethical knowledge dissemination. Her work critically examines classroom teaching quality, schooling impacts, and the complex interplay between disability, poverty, and development. Analysis of her recent publications reveals consistent focus on inclusive education measurement (2024), pandemic impacts on disabled learners (2021-2022), and Southern perspectives on disability-inclusive schooling. Her scholarship bridges rigorous academic research with actionable policy development, evident in her leadership of the Global Disability Summit's International Statement of Action. Fellow of the Academy of Social Sciences (2022) President of the British Association for International and Comparative Education Technical Advisory Council member for World Bank's Inclusive Education Initiative Contributor to UNESCO's Foundations of Disability-Inclusive Education Sector Planning Course Singal mentors a vibrant cohort of postgraduate researchers through the Cambridge Network for Disability and Education Research (CaNDER) and South Asian Approaches to Researching Education (SaareNetwork). Her grant portfolio demonstrates exceptional partnership with international agencies including the World Bank, UNESCO, and MasterCard Foundation, focusing on projects like the Girls Education Challenge Fund evaluation and Ethiopia's Inclusive Education Resource Centres. Current initiatives explore teacher effectiveness in African secondary schools and disability-inclusive education during humanitarian crises. Her research infrastructure includes CaNDER, which connects Global South stakeholders to advance disability-inclusive education scholarship, and active collaboration with international networks like UKFIET and UNPRPD to shape policy frameworks that center lived experiences of disabled learners.
Prof. Kwang W. Oh is a tenured Professor at the Department of Electrical Engineering and Department of Biomedical Engineering within the School of Engineering and Applied Sciences at University at Buffalo (SUNY at Buffalo) . He serves as the Director of Graduate Studies in Electrical Engineering and Director of SMALL (Sensors and MicroActuators Learning Lab) . His academic journey includes PhD and MS in Electrical and Computer Engineering from University of Cincinnati (2001, 1997) and BS in Physics from Chonbuk National University (1995). Prof. Oh's research expertise lies at the intersection of microfluidics , BioMEMS , and lab-on-a-chip technologies. His lab has pioneered vacuum-driven microfluidic devices , PDMS-based systems , droplet manipulation , and chemical-free fabrication techniques . His work enables point-of-care diagnostics , single cell analysis , and wearable medical sensors , with significant contributions to sample-to-answer nanosystems and world-to-chip interfacing . The scientific awards section highlights his excellence in teaching and research: SUNY Chancellor's Award for Excellence in Teaching (2020) Meyerson Award for Undergraduate Teaching (2019) Qualcomm Faculty Award (2019) Senior Teacher of the Year (2017) Royal Society of Chemistry's Emerging Investigators (2013) Samsung Electronics' CEO Honor (2003) His lab has produced numerous PhD and MS students including Dr. Anyang Wang (2020), Dr. Nikhila Nyayapathi (2020), Mr. Liam Christie (2021), and Dr. Domin Koh (2019). As a conference chair , he has organized symposia at NanoTech (2012-2026) and served as editorial board member for Sensors , Micromachines , and Biomedical Engineering Letters .
Mikael Johansson is a Professor at Kungliga Tekniska Högskolan (KTH), specializing in Control Technology . He teaches and coordinates courses such as Distributed Optimization (FEL3311) and various advanced-level degree projects in computer science, electrical engineering, and systems engineering. His research spans Control Systems , Machine Learning , and Optimization , with a focus on asynchronous algorithms, federated learning, and applications in energy systems and construction. His work includes 15 recent publications on topics like neural networks, distributed optimization, and battery technology. Notable areas of contribution are in asynchronous learning, federated learning with privacy constraints, and quasi-Newton methods for optimization. His research bridges theoretical advancements with practical applications in urban design, healthcare, and autonomous systems.
