Jeremy Blackburn is an Associate Professor in the Department of Computer Science at Binghamton University. He co-founded the International Data-driven Research for Advanced Modeling and Analysis Lab ( iDRAMA Lab ) and leads its Binghamton satellite. His research focuses on large-scale measurement and analysis of social media, particularly the behavior of malicious actors and disinformation campaigns.
Gianfranco Chicco is a Full Professor at the Politecnico di Torino , Italy, within the Department of Energy (DENERG). He serves as Scientific Director of the Electrical Power Systems research group and the Turin unit of the ENSIEL Consortium. A Fellow of IEEE (since 2018), he has held editorial leadership roles as Editor-in-Chief of Sustainable Energy, Grids and Networks and Subject Editor of Energy , while chairing major conferences like IEEE ISGT Europe 2017 and UPEC 2020. Education : Laurea (cum laude) in Electrical Engineering (1987), Ph.D. in Electrical Engineering (1992), Doctor Honoris Causa (2017, Polytechnic University of Bucharest; 2018, Technical University 'Gheorghe Asachi' of Iasi). Research Interests : Focus on power transmission and distribution systems , distributed energy resources , and multi-energy smart grids , with applications in artificial intelligence , load management , and power quality . His work addresses technical, economic, and environmental aspects of distributed generation and smart grid sustainability . Publications Trends : Recent articles emphasize photovoltaic power optimization , dynamic grid modeling , and multi-energy system coordination , reflecting expertise in renewable integration , clustering algorithms , and adaptive control . Key subfields include voltage stability , load forecasting , and blockchain for energy trading . Awards : IEEE Fellow (2018-) Best Paper Awards at SEST (2018, 2020) Doctor Honoris Causa (2017, 2018) 'Giancarlo Vallauri' Degree Prize (1988) Advising and Grants : Supervises PhD students in power converters , renewable integration , and high-voltage measurement methodologies . Leads European projects like H2020 MIGRATE and OSMOSE, focusing on grid resilience , clustering-based network planning , and multi-energy sustainability .
Professor Marios C. Angelides is a full-time faculty member at Brunel University London , serving as Professor of Computing and Divisional Lead within the College of Engineering, Design and Physical Sciences . He leads the Creative Computing Research Group under the Institute of Digital Futures and contributes to the Digital Media department at Brunel Design School. BSc (First Class Honours) and PhD in Computing from the London School of Economics (LSE) Chartered Engineer (CEng) and Chartered Fellow of the British Computer Society (FBCS CITP) His research focuses on Creative Computing , specifically applying Machine Learning , Serious Gaming , and Cognitive Modeling to develop Smart IoT Applications . His work spans autonomous drone fleets for environmental monitoring, cybersecurity middleware for Android systems, wearable technology for lifestyle recommendations, and historical analysis of Alan Turing’s legacy in modern AI. Recent publications highlight trends in deploying Machine Learning for: IoT systems optimization Autonomous aerial/underwater vehicle coordination Deepfake detection using Turing’s Imitation Game Energy allocation in CubeSats via gaming mechanics Scientific recognition includes being Deputy Editor of The Computer Journal and runner-up for the 2016 Oxford University Press Wilkes Award . He has supervised PhD students in topics like Smart Android Middleware for Cybersecurity and Wearable Recommendation Systems , with active involvement in editorial boards and international conferences.
Dr. Gabriel Wainer is a Professor in the Department of Systems and Computer Engineering at Carleton University's Faculty of Engineering and Design. He leads the Advanced Real-Time Simulation Lab and specializes in modeling and simulation methodologies, particularly focusing on discrete event systems, real-time modeling, cellular automata, and DEVS formalism. Research Interests: Discrete event systems, DEVS formalism, cellular automata, real-time simulation, IoT applications, and parallel/distributed simulation Affiliation: Carleton University Recent publications highlight his work in advanced simulation frameworks, energy-efficient 5G systems using deep reinforcement learning, and pandemic modeling with cellular automata. His lab develops tools like PROMETHEUS and Devsmap for standardized DEVS model representation, while also exploring applications in wireless communication, building energy systems, and behavioral epidemiology.
Riccardo Raheli is a Full Professor at the University of Parma , Department of Engineering and Architecture, with a career spanning over three decades in Information and Communication Technologies (ICT). He has served as Chair of the Councils for Telecommunications and Communication Engineering programs, and as representative of the University of Parma in CNIT and its Members' Assembly. Education: Laurea in Electronic Engineering (University of Pisa, 1983), M.Sc. in Electrical and Computer Engineering (University of Massachusetts, 1986), Postgraduate Diploma (Scuola Superiore Sant'Anna, 1987) Key Roles: President of Degree Councils (2002-2018), CNIT Committee Member (2000-2005), Editorial Board member for IEEE Transactions, Springer and MDPI journals His research bridges telecommunications , digital signal processing , and healthcare applications , producing extensive international publications and industrial patents. He has co-authored monographs including Detection Algorithms for Wireless Communications (Wiley, 2004) and LDPC Coded Modulations (Springer, 2009). Recent article trends show interdisciplinary work in automotive stress monitoring (IoT/Matlab-based systems), video processing for healthcare (neonatal seizures, respiratory monitoring), and acoustic field control (microphone virtualization, personal sound zones). His work spans machine learning applications in automotive systems, stochastic acoustic modeling , and power-line communications . Scientific Leadership : Co-Chair for IEEE conferences (ICC 2010, GLOBECOM 2011, ISPLC 2020) Editorial roles in 7+ international journals Grants & Collaborations : Led industrial patents in communications systems Coordinated CNIT Technical Reports series (2025) He teaches Wireless Communications and Digital Signals Laboratory , emphasizing Matlab/Simulink proficiency. His laboratory sessions focus on practical implementation of signal processing algorithms, requiring full software installation on personal devices.
Prof. Dr. Wolfgang Nejdl is a Professor at the Institute for Data Science within the Faculty of Electrical Engineering and Computer Science at Leibniz University Hannover. He serves as Executive Director of the L3S Research Centre and Leibniz Forschungszentrum Inclusive Citizenship. Web Science Information Retrieval Artificial Intelligence Deep Learning His recent research focuses on AI applications in medicine , multimodal data fusion , and ethical AI systems . Projects include CAIMed (AI in Causal Medicine) and DAISEC (AI & Cybersecurity). His publications span conferences like AAMAS, WWW, and SIGIR. Notable awards include membership in the National Academy of Science and Engineering (acatech) . Former students hold positions at institutions like Stanford, TU Dresden, and ETH Zürich. Current projects involve climate resilience AI , federated learning for healthcare , and quantum-inspired data science .
Christopher G. Brinton is the Elmore Associate Professor of Electrical and Computer Engineering at Purdue University, where he leads the ION research lab. He is affiliated with the Department of Electrical and Computer Engineering in the College of Engineering at Purdue University's West Lafayette campus. Dr. Brinton received his PhD from Princeton University, where he was previously the Associate Director of the EDGE Lab and a Lecturer of Electrical Engineering. His research focuses on the intersection of networking, communications, and machine learning, with particular emphasis on Fog computing systems, the Internet of Things (IoT), NextG Wireless, and social learning networks. His research integrates foundational techniques including convex and non-convex optimization, machine learning, and signal processing to address challenges in networked intelligent systems. The ION lab under his leadership develops both theoretical frameworks and practical implementations for next-generation networking solutions, with strong industry collaborations including Qualcomm, Nokia, Intel, Cisco, Dell, and Ericsson. Recent publications reveal a strong trend toward federated learning, decentralized algorithms, and edge intelligence, with significant contributions to model partitioning, communication-efficient learning, and robust network architectures. His work increasingly bridges traditional communication theory with modern machine learning techniques to solve emerging challenges in distributed networked systems. NSF CAREER Award ONR Young Investigator Program (YIP) Award DARPA Young Faculty Award (YFA) AFOSR Young Investigator Program (YIP) Award Intel Rising Star Faculty Award (RSA) Dr. Brinton teaches several courses including ECE 647: Performance Modeling of Computer Communication Networks, ECE 301: Signals and Systems, and ECE 547: Introduction to Computer Communication Networks. He has co-authored the book 'The Power of Networks: Six Principles That Connect Our Lives' and taught three Massive Open Online Courses (MOOCs) with over 400,000 cumulative students. While not currently actively recruiting students, he remains open to connecting with highly motivated individuals. Dr. Brinton leads the ION (Intelligent Optimization and Networking) research lab, which focuses on creating theoretical foundations and practical implementations for next-generation networked systems. The lab has recently published significant work on 6G taxonomy in collaboration with major industry partners and continues to push boundaries in distributed learning and network optimization.
Mitchell L. Stevens is a Professor at Stanford University’s Graduate School of Education and holds a courtesy appointment in the Department of Sociology. He co-directs the Stanford Center on Longevity and leads the Pathways Network and Futures Project on Education and Learning for Longer Lives . His research bridges organizational sociology and educational innovation, focusing on equity in academic pathways, data-driven institutional practices, and the sociology of higher education. Education: PhD in Sociology (Northwestern University, 1996); BA in Sociology (Macalester College, 1988). Stevens’ scholarly work examines alternative schooling , educational policy , gendered academic decision-making , and lifelong learning . His recent publications analyze the intersection of machine learning and enrollment trends , merit rituals in admissions , and the marketization of higher education . He employs mixed methods, including large-scale data analysis and comparative-historical frameworks. Stevens mentors doctoral students and postdoctoral researchers, with advisees including Daniela Ganelin, Philip Hernandez, Hansol Lee, Léon Marbach, Melanie Shimano, Joao M. Souto-Maior, Bernardo Mackenna, and Katie Spoon. His lab, the Pathways Network , develops analytics tools to enhance educational equity and institutional practices. Current teaching includes courses on Higher Education , Stanford’s Historical Context , and Organizational Analysis .
Prof. Dr.-Ing. Ralf Beck serves as Professor for Control and Regulation Technology and Automation Technology at Hochschule Düsseldorf University of Applied Sciences within the Faculty of Electrical Engineering & Information Technology. His academic responsibilities span multiple degree programs including BEng Electrical Engineering, BEng Industrial Engineering, and MSc Electrical Engineering and Information Technology. His educational background includes Mechanical Engineering studies at TU Braunschweig (1998-2004), followed by doctoral research at RWTH Aachen's Institute of Control Engineering where he earned his Dr.-Ing. in 2010 with a dissertation on predictive energy management for hybrid vehicles. Prior to his current professorship, he held progressive roles at FEV Europe GmbH from 2009-2018, culminating as Senior Project Manager for Vehicle and Powertrain Electronics. Beck's research focuses on control engineering systems with particular emphasis on automation technology, regulation systems, and model-based development approaches. His work bridges theoretical control methodologies with practical automotive applications, especially in hybrid vehicle energy management, multi-robot systems, and intelligent air path control. The Modellfabrik Fab21 serves as his primary experimental platform for model-based development applications. His publication record since 2005 demonstrates consistent contributions to control engineering, particularly in hybrid vehicle systems, emission control optimization, and calibration methodologies. Recent work shows increasing focus on distributed robotics and intelligent transportation systems, reflecting evolving research directions while maintaining core expertise in control theory applications. As an educator, Beck teaches foundational and advanced courses including Electrical Engineering III, Control and Regulation Technology, Model-Based Development, Technical Mechanics, and Advanced Control Engineering at the Master's level. His teaching integrates theoretical concepts with practical laboratory applications through the university's Moodle platform, emphasizing hands-on implementation of control algorithms and system modeling techniques.
Frank Fitzek serves as Full Professor holding the Deutsche Telekom Chair of Communication Networks at Dresden University of Technology, where he directs the Centre for Tactile Internet (CeTI) Cluster of Excellence and maintains association with the Faculty of Computer Sciences. His work is institutionally anchored within the School of Engineering Sciences and actively engages with 5G Lab Germany and 6G-life Hub initiatives, positioning him at the forefront of next-generation communication research. Fitzek's research spans communication networks, tactile internet systems, 5G/6G mobile technologies, network coding, quantum networking, virtual twinning, and haptic feedback systems. His recent publications demonstrate emphasis on resilient network architectures through quantum security protocols, cloud-native 5G implementations, theoretical communications frameworks, and human-computer interaction in mixed reality environments. This work consistently bridges theoretical innovation with practical testbed validations across multiple emerging technology domains. As Director of CeTI, Fitzek leads a major interdisciplinary research cluster focused on ultra-low latency networks enabling remote physical interaction. His affiliations with 5G Lab Germany and 6G-life Hub facilitate industry-academic collaboration on standardization and deployment of future communication infrastructures, with particular emphasis on network coding techniques and tactile internet applications that transform industrial automation and teleoperation scenarios.
Dr. Janis Nötzel is a senior researcher at the Chair of Theoretical Information Technology (Technische Universität München) and leads his independent Emmy Noether research group. Previously, he held a postdoctoral position at Universitat Autónoma de Barcelona and contributed to 5G practical implementations at TU Dresden's 5G Lab. His research spans quantum information theory, physical layer security, and machine learning applications. Key focuses include Quantum channel capacities under adversarial conditions Entanglement-assisted communication Quantum software frameworks (QuNetSim, QuReed) Interplay between classical and quantum communication Security analysis for 6G networks Resource optimization in quantum systems Recent publications (2023-2025) showcase innovations in Quantum satellite communication architectures Hybrid quantum-classical clustering algorithms Photonic processor instability modeling Covert capacity of compound channels Quantum key distribution resilience Free-space Bessel beam communication He actively collaborates with 6G-life research hub and contributes to quantum network simulation tools. Grants include funding from DFG (Leibniz Program), BMBF (6G-life, Q.Link.X), and StMWi (6G Zukunftslabor Bayern).
Muhannad S. Bakir is the Dan Fielder Professor in the School of Electrical and Computer Engineering at Georgia Institute of Technology, and Director of the 3D Systems Packaging Research Center . His research focuses on heterogeneous integration , electrical/photonic interconnects , thermal modeling , and electronics for healthcare , with over 180 publications and 12 U.S. patents. Research areas include: Advanced cooling and power delivery for emerging systems Biosensor-CMOS integration 2.5D/3D IC packaging Polylithic integration technology Nanofabrication for microsystems Scientific accolades include: 2018 IEEE EPS Exceptional Technical Achievement Award 2013 Intel Early Career Faculty Honor Award 2012 DARPA Young Faculty Award 2011 IEEE CPMT Outstanding Young Engineer Award Best paper awards at IEEE ECTC, IITC, and CICC 2020 Georgia Tech Doctoral Thesis Advisor Award His lab explores integrated 3D systems with emphasis on co-design of thermal, power, and electrical networks for machine learning and healthcare applications.
Leonardus Cornelis Nicolaas de Vreede is a Professor at Delft University of Technology in the Faculty of Electrical Engineering, Mathematics and Computer Science. With over 237 research publications and extensive conference activities, he is a leading researcher in RF and microwave engineering with specialization in power amplifiers, digital transmitters, and mm-wave circuits for wireless communications applications. Dr. de Vreede's research focuses on the intersection of circuit design and signal processing for next-generation wireless systems: Advanced Power Amplifier Architectures including Doherty and Out-phasing techniques Energy-Efficient Digital Transmitters with high linearity and power efficiency mm-Wave Circuit Design for 5G/6G applications Machine Learning Applications for Digital Predistortion CMOS RF Integrated Circuit Implementation Wideband Signal Processing Techniques His recent publications demonstrate a clear research trajectory toward integrating machine learning with traditional RF circuit design to solve the efficiency-linearity tradeoff in wireless transmitters. This work is particularly relevant for current and future wireless infrastructure requiring high spectral efficiency across wide bandwidths while maintaining energy efficiency. Dr. de Vreede has received significant recognition for his contributions to the field: EuMC Microwave Prize (2024) for groundbreaking work on wideband Doherty amplifiers Recognition for innovative characterization techniques for high-power RF transistors (2015) As an active researcher and educator, Dr. de Vreede has supervised 16 students and regularly participates in major international conferences including serving on program committees for the IEEE MTT-S International Microwave Symposium. His work bridges theoretical advances with practical implementations for wireless infrastructure applications, with numerous patents and industry collaborations evident from his research portfolio.
Christopher G. Healey is the Goodnight Distinguished Professor of Analytics in the Institute for Advanced Analytics and a Professor in the Department of Computer Science at North Carolina State University. His research spans visualization, data analytics, text analytics, sentiment analysis, machine learning, cognitive psychology, computer graphics, and social media analytics. He has graduated 15 Ph.D. and 26 master's students and secured over $6 million in research funding from agencies including the National Science Foundation, Department of Defense, National Security Agency, Army Research Office, and various industry partners. He has published over 100 peer-reviewed articles and is a senior member of both IEEE and ACM, as well as a member of the NC State Academy of Outstanding Teachers. His research focuses on developing visualization techniques that leverage visual perception to support rapid, accurate, and effective analysis of large, complex datasets. More recently, he has been investigating machine learning for natural language processing and text analytics. His work includes projects on visualizing election results, sentiment estimation for social media, and wildfire narratives using large-scale social media data. His publications demonstrate a strong trend toward integrating machine learning with visualization, particularly for text analytics and social media analysis. He has made significant contributions to visualizing deep neural networks, cyber situation awareness, and pandemic response analytics, showing how visualization can enhance understanding of complex systems and large datasets across multiple domains. IBM Faculty Award (2007, 2008, 2010, 2011, 2012) Senior member, Association of Computing Machinery (ACM) (2007) Senior member, Institute of Electrical and Electronics Engineers (IEEE) (2007) NC State Academy of Outstanding Teachers inductee (2003) National Science Foundation Faculty Early CAREER Award (2001) He has successfully mentored numerous graduate students and secured significant research funding across multiple projects. His work with the Laboratory for Analytic Sciences, National Science Foundation, and Department of Defense demonstrates strong industry and government partnerships. His recent projects focus on visualizing social media narratives, deep neural networks for text understanding, and predictive analytics for large document collections. He leads research groups focused on visualization and analytics, working with teams to develop innovative approaches for data exploration and analysis. His current work continues to push the boundaries of how visualization can be used to enhance understanding of complex data across domains including public health, cybersecurity, and social media analysis.
Eliese-Sophia Lincke is a Junior Professor at the Department of History and Cultural Studies, Freie Universität Berlin, since May 2022. Her work bridges computational methods with Egyptology, focusing on digital tools for studying ancient texts. Bachelor's and Master's in Egyptology, Humboldt-Universität zu Berlin (2007) PhD in "The Conception of Spaces in Language" (TOPOI Cluster, 2012) Research interests include: Digital Humanities : Developing machine learning models for Hieroglyphic, Demotic, and Coptic text processing Linguistic Typology : Analyzing classifier systems in Ancient Egyptian and Sign Languages Spatial Linguistics : Investigating prepositions and spatial adverbs in Egyptian-Coptic Recent publications focus on Neural Lemmatization , OCR for Coptic , and Classifier Semantics , demonstrating her commitment to computational Egyptology. Scientific awards include the Humboldt-Preis 2008 for best Master's thesis and the Prize for Good Teaching 2014 . She has co-organized workshops like "Wege zum Ägyptischen" and served as Co-Editor for Lingua Aegyptia . Her teaching contributes to the Digital Studies of Ancient Texts Master's program.
