Stefan Wolf is a Full Professor in the Department of Informatics at the Università della Svizzera italiana (USI), Lugano. He has held academic roles since 2005, including Associate Professor at USI (2011–present), SNF Professor for Quantum Information at ETH Zürich (2005–2011), and Assistant Professor positions at the University of Waterloo and Université de Montréal. His research focuses on cryptography, information theory, and quantum information processing, emphasizing provably secure cryptographic systems using weak classical or quantum-physical primitives. Education: Dipl. Math. ETH (Mathematics) PhD in Computer Science from ETH Zurich, supervised by Prof. Ueli Maurer Research Interests: Dr. Wolf’s work bridges theoretical foundations and applied aspects of information security. Key areas include cryptographic protocol design, quantum communication theory, and the integration of quantum mechanics into computational systems. His group, the Cryptography and Quantum Information group , explores cutting-edge topics such as post-quantum cryptography and quantum-resistant algorithms. Labs/Teams: Leads the Cryptography and Quantum Information research group at USI, fostering interdisciplinary projects in secure information processing.
Dr. Sally A Kuykendall is a Professor in the Department of Health Sciences at Saint Joseph’s University, where she has served since 2004 (holding roles including Department Chair from 2011–2015). A former critical care nurse with multidisciplinary academic training (PhD in Health Studies from Temple University, MS in Health Education from Saint Joseph’s University, and BSc in Chemistry/Biology from the University of Plymouth), her work spans bullying prevention, scientific misconduct analysis, and trauma-informed care. She led a nine-year bullying prevention study and authored seminal works like Skewed Studies (2020), exposing flaws in health/psychology research. Her research also examines family violence, adverse childhood experiences, and firearm-related youth behavior. Professional experience includes clinical roles at SmithKline Beecham Pharmaceuticals and Abington Hospital, alongside adjunct/visiting professorships at Temple University and Saint Joseph’s University. She has secured over $3 million in grants for initiatives like the Olweus Bullying Prevention Program implementation and Healthy Lessons for Urban Youth. Awards include the Teaching Excellence Award (2003) and Crystal Community Impact Award (1996). Her recent focus includes creative problem-solving research and book projects addressing institutional responses to whistleblowing. Key contributions include evidence-based bullying prevention frameworks, trauma-informed care protocols, and critiques of unethical research practices across health and psychology disciplines.
Andreas J. Kassler is a Full Professor of Computer Science at Karlstad University, Sweden, where he has been since 2005. He co-chairs the Distributed Systems and Communication (DISCO) group and focuses on networking, cloud computing, and wireless networks. His research includes software-defined networking, future internet architectures, and network optimization. He has authored/co-authored over 130 peer-reviewed publications, holds 6 patents, and serves on editorial boards of journals like Journal of Internet Engineering . Education : Ph.D. in Computer Science, Universität Ulm (2002) Docent (Habilitation), Karlstad University (2007) M.Sc. in Mathematics/Computer Science, Universität Augsburg (1995) Research Interests : Software Defined Networking (SDN) Programmable Dataplanes Wireless Mesh Networks Time-Sensitive Networking (TSN) Edge Computing Machine Learning for Network Optimization Recent Directions : His work spans TSN scheduling, hybrid P4 solutions for 5G, and explainable AI in energy communities. He explores network resilience, latency optimization, and multi-objective control in microgrids. Service Contributions : Track co-chair for VTC 2015 General chair for Wired/Wireless Internet Communications (WWIC) 2013 Editor-in-Chief of IARIA Journal on Advances in Internet Technology Labs/Teams : Leads DISCO group at Karlstad University. Collaborates with global teams on projects like mmWave backhaul networks and SDN-enabled industrial control systems.
Hokeun Kim is an Assistant Professor in the School of Computing and Augmented Intelligence (SCAI) at Arizona State University (ASU), part of the Ira A. Fulton Schools of Engineering. He previously held positions at Hanyang University (2021-2023) and worked in industry roles at Google, LinkedIn, and HP Labs. His research focuses on cyber-physical systems, IoT security, and computer architecture, with a particular emphasis on safety and security aspects of time-sensitive systems. Education: Ph.D. in EECS, University of California, Berkeley (2017) M.S. in EECS, Seoul National University (2012) B.S. in Computer Science and Engineering, Seoul National University (2010) Research Interests: Kim’s work spans secure IoT frameworks, real-time embedded systems, and edge computing. He develops tools like the Secure Swarm Toolkit (SST) and Lingua Franca, addressing challenges in distributed system security, interoperability, and performance. Key Contributions: Authored over 30 peer-reviewed publications in top venues like IEEE Transactions, ACM Conferences, and DATE. Received the ACM/IEEE Best Paper Award (IoTDI 2017) and IEEE Micro Top Picks Honorable Mention (2017). Active in organizing conferences (e.g., DATE, FDL) and serves on technical committees for top journals/conferences. Teaching: Courses include Computer Architecture I/II, Real-Time Embedded Systems, and IoT design at both undergraduate and graduate levels.
Dr. Hien Quoc Ngo is a Reader at Queen's University Belfast and a UKRI Future Leaders Fellow. He specializes in wireless communications, particularly in massive MIMO, cell-free massive MIMO, and cooperative systems. His research focuses on improving spectral efficiency, security, and energy efficiency in next-generation networks. Education: B.S., Electrical Engineering, Ho Chi Minh City University of Technology (2007) M.S., Electronics and Radio Engineering, Kyung Hee University (2010) Ph.D., Communication Systems, Linköping University (2015) Research Interests: Dr. Ngo's work spans massive MIMO systems, cell-free architectures, physical layer security, and millimeter-wave technologies. He has pioneered studies on channel estimation, power allocation, and interference management in distributed networks. Awards & Recognition: IEEE ComSoc Stephen O. Rice Prize (2015) IEEE ComSoc Leonard G. Abraham Prize (2017) Best PhD Award from EURASIP (2018) UKRI Future Leaders Fellowship (2019) Multiple AMiner Most Influential Scholar Awards (2022-2024) Grants & Projects: Lead on the Future Communications Hub in All-Spectrum Connectivity (UKRI-funded) Principal Investigator for Cell-Free Massive MIMO for ISAC Labs & Teams: He leads the Wireless Communications Research Group at Queen's University, focusing on 5G/6G technologies and intelligent systems.
Paulo Alves is an Associate Professor at Católica Porto Business School, Universidade Católica Portuguesa, where he serves as Vice-Dean for Management Control, Accreditations, and Master's Programmes. He holds a Ph.D. and Post-Doctorate in Accounting and Finance from Lancaster University (UK) and maintains an active collaboration as a Visiting Research Associate and guest lecturer there. His research focuses on the impact of information on capital markets, particularly financial narratives in public-private partnerships, with publications in reputable journals. He is affiliated with the Research Center in Management and Economics (CEGE) and contributes to the Corporate Financial Information Environment project at Lancaster University. Education: Ph.D. in Accounting and Finance, Lancaster University (UK) Post-Doctorate in Accounting and Finance, Lancaster University (UK) Paulo Alves' research spans two distinct domains. In Finance and Accounting, he examines financial narratives, capital market impacts, and public-private partnership accountability. In Healthcare, his work includes pressure ulcer prevention, wound care, and health-related quality of life metrics. His publications reflect interdisciplinary engagement, combining rigorous financial analysis with clinical healthcare innovation. Recent publications highlight trends in Financial Reporting (public-private partnerships, earnings disclosures) and Healthcare Technology (prophylactic dressings, medical device safety). He has developed tools like the Ghent Global IAD Categorization Tool and contributed to consensus frameworks like SECURE prevention for pressure ulcers. Scientific Awards: International ranking distinction for researcher at Católica Porto Business School As a certified auditor and accountant, Paulo consults on governance and financial systems while leading projects analyzing financial information retrieval and healthcare quality metrics. His affiliations include CEGE and the Corporate Financial Information Environment initiative.
Andrew J Whelton is a Professor of Civil and Construction Engineering at Purdue University's College of Engineering, with concurrent appointments in Sustainability Engineering and Environmental Engineering. He serves as Director of the Healthy Plumbing Consortium and Lead for the Center for Plumbing Safety, focusing on water quality, chemical contamination, and public health in building plumbing systems. Professor, Civil and Construction Engineering Professor, Sustainability Engineering Professor, Environmental Engineering Director, Healthy Plumbing Consortium Lead, Center for Plumbing Safety His research spans environmental engineering and public health, with key themes including chemical contamination from plastic pipe degradation, post-disaster water system recovery, wildfire-related water quality impacts, and microbial risks in premise plumbing. Recent work addresses crises like the East Palestine chemical spill and Maui wildfires, while also developing predictive models for water quality and evaluating sustainable infrastructure materials. Scientific awards and recognitions include: Rapid Response Research (RAPID) Grants from NSF for disaster-related studies Environmental Protection Agency (EPA) support for building water quality programs Leadership in interdisciplinary consortia focused on plumbing safety Development of novel tools for water quality monitoring and remediation His publications reveal trends in: Chemical leaching from plastic piping materials Environmental justice in water contamination crises Integration of machine learning for water quality prediction Microbial ecology in stagnant plumbing systems Policy recommendations for disaster response Sustainable material innovation for infrastructure
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.
Dr Raja Akrom is a Senior Lecturer in the Department of Computer Science , School of Natural and Computing Sciences , University of Aberdeen since July 2020. Previously, he held research positions at Royal Holloway, University of London (Post Doctoral Research Assistant), University of Waikato (Research Fellow), and Edinburgh Napier University (Senior Research Fellow). PhD in Information Security from Royal Holloway, University of London MSc in Information Security and Computer Science from Royal Holloway and University of Agriculture, Faisalabad BSc in Mathematics and Physics from University of the Punjab His research focuses on user-centric applied security and privacy architectures , data ownership in heterogeneous computing , security for machine learning , and security in emerging technologies such as blockchain, UAVs/drones, and autonomous vehicles. Key technical interests include smart card security, cryptographic protocols, IoT security, and Trusted Execution Environments. The article list reveals expertise in: edge computing security (DECML 2025), medical AI applications (2024), embedded device ownership (CO-TSM 2024), NFC transaction security (2024), and malware detection with ML (2024). Earlier work explored UAV security , blockchain governance , and smart card protocols . Currently teaching courses in Operating Systems , Secure Software Design , and Enterprise Security Architecture . Supervises postgraduate MSc Cybersecurity program.
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.
Elena Grigorescu is an Adjunct Associate Professor in the Department of Computer Science at Purdue University, where she has been a faculty member since Fall 2012. Her research program spans theoretical computer science with a focus on foundational algorithmic challenges in large-scale data processing and computational limits, maintaining strong connections to cryptography, communications, and optimization applications. Her educational background includes a PhD from the Massachusetts Institute of Technology (MIT), establishing her expertise in rigorous theoretical frameworks. Professor Grigorescu's research emphasizes designing algorithms that operate in sublinear time or space for massive datasets, analyzing complexity of error-correcting codes and lattices, and exploring information-theoretical computation limits. Current investigations integrate differential privacy with learning-augmented techniques to solve online optimization problems, network design challenges, and data stream processing bottlenecks. Her work bridges abstract theory with practical implementations in cryptographic systems and quantum computing paradigms, demonstrating consistent innovation in algorithmic foundations. Analysis of her recent publications (2022-2025) reveals a dominant focus on sublinear-time algorithms, particularly at the intersection with differential privacy and machine learning augmentation. Key contributions include novel spanner constructions for network design, privacy-preserving clustering frameworks, and breakthroughs in trace reconstruction and coding theory. A pronounced trend shows increasing integration of learning-based predictions to enhance classical online algorithms for packing/covering problems while maintaining theoretical guarantees, alongside sustained contributions to error-correcting code analysis and graph-theoretic foundations. No specific scientific awards or major fellowships were documented in the provided materials, though her publication record in premier venues like STOC, FOCS, and APPROX/RANDOM indicates significant peer recognition. Professor Grigorescu actively mentors graduate students in theoretical computer science research, guiding investigations in sublinear algorithms, complexity theory, and coding theory. Her collaborative projects involve interdisciplinary teams across institutions, focusing on cryptographic applications and quantum information theory, though specific grant details were not included in the source texts. Ongoing work suggests expansion into quantum algorithm design and privacy-preserving machine learning frameworks. While dedicated laboratory facilities were not specified, her research operates within Purdue's theoretical computer science group, leveraging university-wide computational resources and fostering collaborations through conference participation and workshop organization.
