Zicheng Chi is an Assistant Professor in the Department of Electrical Engineering and Computer Science at Cleveland State University. His research focuses on Internet of Things (IoT) and cyber-physical systems, with expertise in wireless networks, embedded systems, and RF sensing. Ph.D. in Computer Engineering, University of Maryland, Baltimore County (2020) M.E. in Microelectronics and Solid Electronics, South China University of Technology (2011) B.S. in Electronic Information Science and Technology, Lanzhou University (2007) Chi's work explores fundamental networking and energy challenges in IoT, including LTE backscatter systems, cross-technology communication protocols, and interference-negligible RF sensing. His research bridges communication efficiency and security in heterogeneous IoT environments. Recent publications demonstrate expertise in high-throughput backscatter (2024), secure asymmetric communication (2024), vehicle-to-vehicle perception (2023), and tactical IoT protocols (2022). His work spans wireless network optimization, security mechanisms, and energy-efficient system design. Best Paper Award Candidate, SenSys 2019 Best Paper Runner-up, SenSys 2018 Chi teaches graduate and undergraduate courses in computer networks, data communication, and system programming. His NSF-funded SWIFT project investigates spectrum coexistence in IoT systems.
Dr. Jianbing Li is a Professor and Professional Engineer (P.Eng.) in the Environmental Engineering Program at the University of Northern British Columbia (UNBC), holding prestigious fellowships from CSCE, CSSE, EIC, and Engineers Canada. His research program addresses critical environmental challenges with significant real-world impact, particularly in northern and remote communities of British Columbia. Education: PhD in Environmental Systems Engineering, University of Regina Research Focus: Dr. Li's work centers on environmental pollution control , petroleum waste management , soil and groundwater remediation , environmental modeling , risk assessment , and oil spill response . His innovative approaches integrate machine learning, advanced materials, and sustainable engineering principles to develop practical solutions for complex environmental problems, with particular emphasis on resource recovery from waste streams. Publication Trends: Analysis of his 15 most recent publications (2023-2025) reveals a strategic focus on oil spill response technologies, wastewater treatment innovations, and waste valorization. Key advancements include nano/micro bubble flotation systems, chitosan-based adsorbents, and machine learning models for pyrolysis optimization, demonstrating his leadership in translating laboratory research to field applications. Scientific Recognition: 2024 Fellow of Engineers Canada and Engineering Institute of Canada 2023 CSCE Dr. Albert E. Berry Medal (Canada's top environmental engineering award) Multiple UNBC Research Excellence Awards (2010, 2014, 2019, 2023) 2013 Northern BC Business and Technology Award with Husky Energy Best paper awards from International Academy of Science and Environmental Geotechnology Society Research Leadership: Dr. Li has secured over $800,000 in 2023 and $1.9 million in 2020 for oil spill response research through NSERC, DFO, and NRCan. His current portfolio includes groundwater protection for Indigenous communities, next-generation decanting technologies, and water security for remote regions. He actively mentors PhD, MSc, and MASc students while serving on NSERC evaluation committees and co-directing the UNBC/UBC environmental engineering program (2013-2017). Collaborative Networks: Dr. Li leads multi-institutional partnerships with UBC, government agencies, industry (including Husky Energy), and Indigenous communities like Lheidli T'enneh First Nation. His work through the Multi-Partner Research Initiative addresses practical challenges in rural British Columbia while advancing fundamental knowledge in environmental systems engineering.
Nuno Pereira Lopes is an Associate Professor at Instituto Superior Técnico , part of Universidade de Lisboa , and a researcher at INESC-ID . He also serves as an advisor at FuriosaAI , focusing on tensor contraction processors for AI workloads. Research Interests : Compilers, formal verification of LLVM optimizations, machine learning frameworks, undefined behavior exploitation, probabilistic model checking, blockchain security, and many-core code generation. Teaching : Compilers and Computer/Informatics Engineering projects. Funding : Supported by Google, Matter Labs, NLnet, Oracle, PRACE, RNCA, and Woven by Toyota. Recent Publications focus on LLVM backend validation , PyTorch pipeline parallelism , C++ dynamic cast optimization , undefined behavior in C/C++ , and AI tensor processors . His work bridges compiler design, formal methods, and AI hardware. Academic Service includes representing Portugal in ISO/IEC JTC 1/SC 22 (C++), organizing FLoC'26 , and serving on program committees for PLDI, EuroLLVM, and CGO.
Professor Haiyan Zhou serves as Professor of Genetic Medicine at University College London (UCL), affiliated with the Institute of Child Health and Department of Genetics and Genomic Medicine. She directs the UK Platform of Nucleic Acid Therapy (UPNAT Node) for rare diseases, co-leads the Therapeutic Innovation and Trials Community Domain in Genomics England, and acts as Deputy Theme Lead for Novel Therapies at the NIHR Great Ormond Street Hospital Biomedical Research Centre. Prof. Zhou earned her MD-PhD in clinical medicine and skin pharmacology from Peking Union Medical College. Her research pioneers nucleic acid therapeutics (NAT) for rare genetic disorders, focusing on RNA-based approaches including antisense oligonucleotides, siRNA, and RNA editing for neuromuscular diseases. The Zhou Lab collaborates extensively across UCL with experts in muscular dystrophies, respiratory disorders, neurological conditions, and metabolic diseases to translate experimental therapies into clinical applications for pediatric patients. Recent publications (2023-2025) reveal a dominant focus on optimizing RNA therapeutics for spinal muscular atrophy and collagen VI-related dystrophies, with key advances in allele-specific silencing, biomarker discovery, and preclinical-to-clinical translation. Her work consistently bridges molecular mechanisms with therapeutic development, emphasizing tissue-specific delivery and treatment response monitoring. Scientific recognition includes: Harrington UK Rare Disease Scholar (2021) Lea Rose Spinal Muscular Atrophy Award (2017, 2015) Young scientist award from The SMA trust (2011) President Prize for the Young Myologist of the Year (World Muscle Society, 2006) As principal investigator, Prof. Zhou secures funding from MRC, NIHR, and the Harrington Discovery Institute for RNA therapeutic development. She mentors early-career researchers through e-COST Action, Marie Skłodowska-Curie ITN, and UCL programs while supervising MSc/PhD students. Her leadership extends to directing UCL's MSc Personalized Medicine and Novel Therapies Programme and serving on multiple education committees. The Zhou Lab operates as a multidisciplinary hub within UCL's Institute of Child Health, collaborating closely with the Dubowitz Neuromuscular Centre and international consortia like the Oligonucleotide Therapeutic Society. Current initiatives focus on individualized RNA therapy for pediatric rare diseases, with active pipelines for hereditary sensory neuropathy and COL6-related dystrophies.
Jianfeng Gu is a Ph.D. Candidate and researcher at the Technical University of Munich (TUM), affiliated with the Department of Computer Science and specifically the Chair of Computer Architecture and Parallel Systems led by Prof. Martin Schulz. He maintains an active research profile with numerous publications and contributes to the academic community through teaching seminars on Cloud Computing. His academic path began with a Bachelor of Software Engineering from Sun Yat-sen University in China (2014-2018), followed by a Master of Engineering from the same institution (2018-2020). Since April 2021, he has been pursuing his Ph.D. at TUM, advancing research in computing systems and architectures. Gu's research focuses on Heterogeneous Serverless Computing for Deep Learning applications, specializing in GPU, FPGA, and NPU technologies within serverless environments. His work addresses critical challenges in resource allocation, auto-scaling, and performance optimization for serverless inference systems. Additionally, he investigates Real-time Autonomous Driving Systems , developing advanced perception techniques through sensor fusion (particularly stereo-LiDAR fusion) for high-precision depth sensing and object detection in autonomous vehicles. His interdisciplinary approach bridges hardware acceleration, cloud infrastructure, and AI applications. His publication trajectory shows a progression from foundational computer vision and autonomous driving research (2018-2020) toward increasingly sophisticated work on serverless computing and federated learning (2021-2025). Recent publications focus on efficient resource sharing in heterogeneous serverless environments, with particular attention to GPU and FPGA allocation strategies that maintain service level objectives while optimizing costs. His work demonstrates strong technical depth across multiple computing domains. Best Paper Award at IEEE/ACM DATE 2021 15+ publications with 185+ citations Research featured in top venues for computer architecture and cloud computing As a Ph.D. researcher, Gu teaches seminars on Cloud Computing (IN2107) and contributes to multiple research projects at TUM's Chair of Computer Architecture and Parallel Systems. His work is supported by the department's research infrastructure and collaborations with faculty including Prof. Martin Schulz and Prof. Michael Gerndt. Gu works within TUM's advanced computing research environment, contributing to projects related to high-performance computing, serverless architectures, and autonomous systems. His research group maintains specialized hardware and software infrastructure for evaluating modern HPC architectures and accelerators, including FPGA clusters and GPU resources for deep learning research.
Amirhosein Taherkordi is a Professor in the Networks and Distributed Systems group at the Department of Informatics, University of Oslo, Norway. His research focuses on resource-efficiency, scalability, adaptability, dependability, mobility and data-intensiveness of distributed systems for emerging computing technologies including Internet of Things (IoT), Fog/Edge/Cloud Computing, and Cyber-Physical Systems (CPS). Dr. Taherkordi received his Ph.D. from the Informatics Department at the University of Oslo under the supervision of Prof. Frank Eliassen, with his thesis titled "Programming Wireless Sensor Networks: From Static to Adaptive Models." He holds an M.Sc. in Information Technology Engineering (Software Engineering) from University of Science and Technology and a B.Sc. in Computer Engineering from Sharif University of Technology. His research spans multiple domains of distributed systems with emphasis on practical applications. He investigates energy efficiency in wireless sensor networks, communication optimization in IoT systems, and adaptive resource allocation in edge computing environments. His work addresses critical challenges in network traffic classification, federated learning for vehicular networks, and data processing across heterogeneous platforms. Analysis of his recent publications reveals a strong trajectory toward communication-efficient federated learning techniques for vehicular networks, energy-aware protocols for IoT data collection, and advanced machine learning approaches for network traffic analysis. His research consistently focuses on optimizing resource usage while maintaining system performance and privacy in distributed architectures. Dr. Taherkordi actively contributes to several research initiatives including the CPS Lab at UiO for Cyber Physical Systems, DILUTE: Fluid Service Abstraction for Large-Scale Cloud IoT Systems, and the Gemini Centre on IoT at UiO. His work bridges theoretical advances with practical implementations in transportation systems, environmental monitoring, and industrial automation.
John McGready, PhD, ScM, is a Teaching Professor in the Department of Biostatistics at the Johns Hopkins Bloomberg School of Public Health. He is affiliated with multiple centers including the McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins Biostatistics Center (JHBC), The Johns Hopkins Institute for Clinical and Translational Research, and the R³ Center for Innovation in Science Education (R3ISE). Dr. McGready earned his PhD from the Johns Hopkins Bloomberg School of Public Health in 2008 and his ScM from Harvard School of Public Health in 1996. Prior to joining Johns Hopkins, he worked as a quantitative policy analyst focusing on criminal justice policy, taught high school math in Washington, D.C., and worked as a healthcare data analyst for Healthcare Investment Analysts. His research interests span biostatistics, statistical education, statistical consulting, statistical methods, and statistical literacy. Dr. McGready is particularly known for his work in statistical education and has developed numerous teaching materials including OpenCourseWare. His research collaborations extend across multiple departments at the Bloomberg School including Health Policy and Management, Epidemiology, International Health, and Population and Family Reproductive Health, as well as with the Johns Hopkins University School of Medicine and Johns Hopkins Healthcare. His publication record shows a diverse range of research interests from clinical applications of biostatistics to educational methods. Recent work spans pulmonary function analysis, diabetes prevention using AI, food security measurement, and growth patterns in genetic conditions like achondroplasia. His work combines rigorous statistical methodology with practical applications in public health and clinical medicine. Dr. McGready has received numerous teaching awards throughout his career: Multiple Golden Apple Teaching Awards (2001, 2004, 2008, 2012, 2016, 2020, 2024) Ernest Lyman Stebbins Medal (2021) ASPH/Pfizer Early Career Award for Teaching Excellence (2010) Outstanding Teacher Award from the American Statistical Association (2010) Excellence in Online Education Awards (2001, 2005) As the primary instructor for 'Statistical Reasoning in Public Health I and II' (taught both on campus and online) and 'Statistical Methods in Public Health III,' Dr. McGready has significantly impacted statistical education. He is also the co-creator and instructor of intensive data analysis workshops offered in the School's Summer Institute of Epidemiology and Biostatistics. His research collaborations span numerous public health domains, with particular emphasis on clinical applications of biostatistical methods.
Professor Jon Wardle serves as Foundation Director of the National Centre for Naturopathic Medicine and holds the Maurice Blackmore Chair of Naturopathic Medicine at Southern Cross University. He maintains significant international influence through visiting positions at Boston University, University of Washington, and University of Oxford, while serving on the World Health Organization and National Health and Medical Research Council committees. His leadership spans public health policy, integrative medicine systems, and traditional knowledge protection. His educational foundation includes a Bachelor of Health Science (ACNM), Postgraduate Certificate in Health Economics, Master of Health and Medical Law (University of Melbourne), Master of Public Health (University of Queensland), and PhD (University of Queensland). These qualifications underpin his interdisciplinary approach to health systems research. Wardle's research centers on integrating traditional medicine into contemporary healthcare frameworks, with emphasis on regulatory systems, cultural safety, and health equity. His work critically examines therapeutic pluralism in global contexts, particularly regarding Indigenous knowledge protection, migrant health disparities, and pandemic response equity. He develops evidence-based frameworks like the Contemporary Implementation of Traditional knowledge and Evidence (CITE) to bridge traditional practices with modern health systems. Analysis of his 15 most recent publications reveals dominant themes: traditional medicine governance (35% of works), pandemic impacts on vulnerable populations (20%), complementary medicine regulation (15%), and women's health integration (10%). His methodological approach combines qualitative analysis with systematic reviews, focusing on policy implementation gaps across Australian, African, and global contexts. A notable trend is the increasing emphasis on decolonizing health research and stakeholder-driven policy development. As Editor-in-Chief of Advances in Integrative Medicine and editorial board member for seven other journals, Wardle shapes scholarly discourse in the field. His leadership extends to convening the Public Health Association of Australia's complementary medicine special interest group and chairing World Federation of Public Health Associations initiatives. Wardle actively supervises higher degree research students through Southern Cross University's Graduate School, focusing on integrative medicine policy and traditional knowledge systems. His NHMRC Natural Therapies Working Committee role directly influences Australian health funding priorities, while WHO collaborations drive global standard-setting for traditional medicine integration. The National Centre for Naturopathic Medicine operates as his primary research hub, facilitating collaborations with 14-country networks studying naturopathic practice patterns. Current projects include Sub-Saharan Africa traditional medicine governance frameworks and Australian military complementary medicine utilization studies, positioning the Centre at the forefront of evidence-based integrative health policy development.
Dr. Andrea L. Wirtz is an Associate Professor in the Department of Epidemiology at Johns Hopkins Bloomberg School of Public Health, with primary division in Infectious Disease Epidemiology and joint division in Social and Behavioral Interventions. She is affiliated with the Center for Global Health, Center for Humanitarian Health, and Center for Public Health and Human Rights. Her educational background includes: PhD, Johns Hopkins Bloomberg School of Public Health (2015) MHS, Johns Hopkins Bloomberg School of Public Health (2007) Dr. Wirtz advances epidemiologic methods to measure associations between human rights and health outcomes, with particular focus on evidence-based interventions and translation to policy. Her research centers on community-partnered international and domestic epidemiologic research addressing intersections between human rights and HIV and other health outcomes, with specific attention to populations traditionally excluded from research or underserved in health services. Internationally, she serves as joint Principal Investigator for estimating HIV prevalence among Venezuelan migrants and refugees in Colombia. In the U.S., she leads a nationwide cohort study focused on health and HIV risks in transgender women. Her work integrates epidemiologic expertise into complex humanitarian interventions and human rights investigations across diverse settings. Analysis of her recent publications reveals a strong focus on transgender health, HIV prevention and treatment, migrant and refugee health, and the application of epidemiologic methods to human rights investigations. Her research increasingly addresses long-term health conditions in marginalized populations, including studies on Long COVID, cardiovascular disease in transgender women with HIV, and pandemic impacts on healthcare access for vulnerable groups. Her scientific recognition includes: Robert Carr Memorial Research Award (2022) for community-academic partnerships advancing human rights-based policies Global Leadership in HIV Prevention Research award from US Department of State (2021) Multiple teaching awards from Johns Hopkins Bloomberg School of Public Health (2014-2022) Advising, Mentoring, & Teaching Recognition Award (2015-16) At Johns Hopkins, Dr. Wirtz instructs graduate-level courses on health survey research methods and using epidemiologic methods to investigate human rights violations. She has secured significant grant funding for studies on HIV prevention, transgender health, and migrant health interventions. Her research portfolio includes community-academic-policy collaborations that address complex health challenges through rigorous epidemiologic approaches. Dr. Wirtz leads several major research initiatives including the American Cohort to Study HIV Acquisition among Transgender Women (LITE study), development of screening tools for gender-based violence in humanitarian settings, and effectiveness studies of HIV preventive interventions for vulnerable populations globally.
Kristian Gjøsteen is a Professor at the Department of Mathematical Sciences within the Norwegian University of Science and Technology (NTNU) . He actively contributes to the Algebra Group and specializes in cryptographic systems with a focus on electronic voting , security proofs , and privacy-enhancing technologies . Educational Background: MSc and PhD from NTNU Research Interests: His work spans cryptography , key exchange protocols , cloud security , and formal verification of security mechanisms. Particular emphasis is placed on coercion-resistant voting systems , lattice-based encryption , and blockchain privacy models . Article Trends: Recent publications demonstrate expertise in post-quantum cryptography , machine-checked security , and privacy-preserving voting architectures . Collaborative efforts explore hybrid cryptographic schemes , verifiable decryption , and mix-net implementations for secure elections.
Simone Ferlin is an Adjunct Senior Lecturer at Karlstad University working with 5G and Internet evolution. She completed her PhD in computer science in 2017 at the Simula Research Lab and Universitetet i Oslo under the supervision of Dr. Ozgu Alay and Prof. Michael Welzl. Her PhD dissertation focused on increasing robustness in multipath transport with MPTCP. Dr. Ferlin's educational background includes a PhD in Computer Science from the Simula Research Lab and Universitetet i Oslo (2017). Her doctoral research centered on enhancing robustness in multipath transport protocols, specifically focusing on MPTCP (Multipath TCP). She also completed undergraduate work that contributed to a book project with Prof. Friedrich Oehme on electronics and circuit technology. Dr. Ferlin's research spans multiple domains at the intersection of networking, systems, and performance engineering. Her primary interests include network and system measurements, performance analysis, security, and congestion control. She investigates how networks like the Internet evolve, examining technology development, adoption patterns, and their impacts on various entities. Additionally, she explores ways to harmonize security and privacy while making them more usable and assessable. Her work particularly focuses on transport layer and multipath transport protocols, examining their performance and security aspects. She also investigates application and transport layer performance, automation, and monitoring. Her research extends to network programming in both Linux kernel and user space, mobile broadband networks from 2G to 5G, and their intersection with the Internet. She is deeply engaged in observability, distributed and system performance monitoring, and automation. Analysis of Dr. Ferlin's recent publications reveals a strong focus on next-generation networking technologies. Her work spans multiple domains including 5G/6G networks, transport protocols (particularly QUIC and MPTCP), network virtualization, container orchestration, and the application of machine learning to networking problems. She has increasingly incorporated large language models into network configuration and automation research. Her publications demonstrate a consistent emphasis on performance measurement, optimization, and security across diverse networking environments from the edge to the cloud. Dr. Ferlin has received notable recognition for her research contributions: Best paper award at IEEE ICIN'21 for 'Learning-based Incast Performance Inference in Software-Defined Data Centers' Applied Networking Research Prize (ANRP)'25 winner for 'NetConfEval: Can LLMs Facilitate Network Configuration?' Dr. Ferlin is actively involved in mentoring the next generation of networking researchers. She has co-supervised numerous Master's and PhD students across multiple institutions including Karlstad University, KTH, TU Berlin, University of Oslo, and universities in Brazil. Her students have worked on diverse topics including NAT64 performance comparison, system tracing visualization, network observability, ML applications to multipath transport, FEC integration with QUIC, high-performance networking for 5G, congestion control, shared bottleneck detection, multipath IoT applications, and container runtime performance. She is also involved in several significant research projects including Vinnova's SEMLA (Securing Enterprises via Machine-Learning-based Automation), Horizon Europe's CODECO (Cognitive Decentralised Edge Cloud Orchestration), and the Knowledge Foundation of Sweden's DRIVE (Data-driven Latency-Sensitive Mobile Services for a Digitized Society). Dr. Ferlin serves as Workshop Chair for ACM SIGCOMM '25, is a member of the ACM/IRTF Applied Networking Research Workshop (ANRW) steering committee, and co-chairs the Internet Congestion Control Research Group (ICCRG) at the IRTF. She previously served as Associate Technical Editor for IEEE Communications Magazine and has been active on numerous program committees for major networking conferences including SIGCOMM, CoNEXT, IMC, and PAM.
Nele Mentens is a full professor at both KU Leuven and Leiden University, where she leads cutting-edge research in applied cryptography, hardware security, and secure embedded systems. At KU Leuven, she is affiliated with the Faculty of Engineering Technology and the Electrical Engineering Department (ESAT), leading the Emerging Technologies, Systems & Security (ES&S) research group at the Diepenbeek campus. Simultaneously, she holds a full professorship at Leiden University’s Leiden Institute of Advanced Computer Science (LIACS), focusing on applied cryptography and security. She has been instrumental in numerous national and international research initiatives, including Horizon Europe and NWO-funded projects. Full Professor, KU Leuven (since 2023) Full Professor, Leiden University (since 2020) Associate Professor, KU Leuven (2014–2023) Post-doctoral Researcher & Lecturer, KHLim / KU Leuven (2007–2014) Ph.D. in Engineering Science, KU Leuven (2007) M.Sc. in Electrical Engineering, KU Leuven (2003) Her research focuses on secure and efficient hardware design, particularly for cryptographic applications on FPGAs, reconfigurable architectures, IoT security, and neuromorphic computing. She explores physical attack resistance, side-channel analysis protection, and trusted computing architectures, with applications in healthcare, industrial monitoring, and endpoint AI. Her work bridges theoretical cryptography with practical hardware implementations, emphasizing energy efficiency and real-time performance. The 15 most recent publications reflect a strong trend toward secure, energy-efficient, and intelligent embedded systems. Topics include neuromorphic AI accelerators, trusted IoT architectures, dynamic reconfiguration for side-channel protection, and secure medical data processing. These works span disciplines such as computer architecture, cybersecurity, digital design, and embedded systems, with a focus on hardware-software co-design and real-world deployment. Nele Mentens has received recognition for her contributions, including: Best Paper Award, DATE'16 Best Paper Nomination, AsianHOST'17 Best Paper Award, CHES'19 She has supervised over 15 Ph.D. students and post-docs, both current and former, and has served as principal investigator in approximately 25 funded research projects. Her work has attracted significant grants from Horizon Europe, NWO, FWO, and national innovation programs. She actively contributes to the academic community through editorial roles in top journals and leadership in major conferences. Nele Mentens leads the ES&S research group at KU Leuven and collaborates closely with LIACS at Leiden University. Her team includes Ph.D. students, post-docs, and research experts working on projects like NimbleAI, NeuroSoC, and TrustedIoT. She has also established secure electronics labs through infrastructure grants and maintains strong international ties with institutions such as EPFL, Ruhr University Bochum, and ETH Zurich.
Jorg Liebeherr is a Professor in the Department of Electrical and Computer Engineering at the University of Toronto, holding the Nortel Chair of Network Architecture and Services. His research focuses on computer networks , particularly network calculus , self-organizing networks , protocol design , and traffic scheduling . Education: Diplom-Informatiker (with distinction), University of Erlangen (Germany), 1988 PhD, Computer Science, Georgia Institute of Technology, 1991 His recent work includes low-cost LoRa mesh networks for environmental sensing and mathematical frameworks for traffic control in 5G and IoT systems. Publications span journals like IEEE Internet of Things Journal and conferences such as IEEE Infocom and ACM Sigmetrics . Scientific Awards: IEEE Fellow (2008) Outstanding Service Award, IEEE ComSoc TC on Computer Communications (2006) ACM Sigmetrics Best Student Paper Award (2005) NSF CAREER Award (1996) Advising and Grants: Supervised 15+ theses (MASc/PhD) and secured grants from NSF, Virginia Engineering Foundation, and industry partners. Labs: Leads the Network Research Lab and HyperCast projects, an open-source platform for application-layer internetworking.
Karl Palmskog is a Lecturer at KTH Royal Institute of Technology in the Division of Theoretical Computer Science and the STEP research group. His work focuses on program verification and proof engineering, with particular emphasis on developing techniques and tools based on proof assistants for constructing functionally correct and secure software systems. Palmskog received his Ph.D. in Computer Science in 2014 from KTH, advised by Mads Dam, and his M.Sc. in Computer Science and Engineering from KTH in 2007. Prior to his current position, he was a postdoc at The University of Texas at Austin and University of Illinois at Urbana-Champaign. His research interests span programming languages, software engineering, and formal verification, with a particular focus on developing techniques and tools based on proof assistants. He is an avid user of the Coq proof assistant for both proving and programming, often complemented by OCaml, and also utilizes HOL4 and other ML family dialects. His work bridges theoretical foundations with practical applications, particularly in the domains of blockchain systems, distributed systems, and automotive software verification. Analysis of his recent publications reveals a strong focus on Coq-based verification, with significant contributions to proof engineering tools and methodologies. His work includes developing tools for regression proving, change impact analysis, mutation testing for Coq projects, and lemma name suggestion using deep learning. There's also a growing trend toward applying formal methods to real-world systems like blockchain protocols and automotive software. Palmskog has been involved in several research projects, including Coq-community Proof Engineering and Distributed Components. His past projects include Trustfull (SSF), Model-based Event Driven Scalable Programming for the Mobile Cloud (NSF), Highly Adaptable and Trustworthy Software (EU FP7), and 4WARD Future Internet (EU FP7). As an educator, Palmskog has served as examiner, course responsible, teacher, and assistant for various courses including Algorithms, Data Structures and Complexity; Degree Projects; Game Theory; Parallel and Distributed Computing; and Programming Paradigms. His work on Chip, a Coq formalization of change impact analysis, demonstrates his commitment to creating practical, certified tools that bridge formal methods with software engineering practice.
Ryan Scrivens is an Associate Professor at the School of Criminal Justice, Michigan State University, and holds cross-appointments as Associate Director at Simon Fraser University's International CyberCrime Research Centre and Research Fellow at VOX-Pol Network of Excellence (Ireland). His problem-oriented research combines computational methods with qualitative insights to study right-wing extremism, hate crime, and cyber-terrorist activities. PhD in Criminology (2017), Simon Fraser University MA in Criminology (2011), Ontario Tech University BA in Criminology (2009), Ontario Tech University His research integrates advanced quantitative methods and machine learning with in-depth interviews to analyze: online radicalization pathways , right-wing extremist forum dynamics , and CVE program evaluation . Recent work examines incel subcultures on Reddit, hate speech during global crises, and desistance modeling for extremists. His publications span journals like Terrorism and Political Violence and Social Media + Society , with forthcoming volumes on Former Extremists (Oxford) and Right-Wing Extremism (Palgrave). Funded by Public Safety Canada and the Canadian Network for Research on Terrorism, Security and Society, he advises law enforcement agencies and tech companies internationally. Early Career Impact Award (2022), American Society of Criminology As editorial board member for Terrorism and Political Violence and Perspectives on Terrorism , Scrivens bridges academic rigor with practitioner needs through 60+ publications and policy engagement.
