Aleksandra Tomic serves as a Researcher in the Department of Chemical Engineering at the Faculty of Technology and Metallurgy, elected to this position on June 29, 2023. Her teaching responsibilities include Fundamentals of Automatic Control (22ZP43, ZP39) and Process Modeling and Simulation (22NHT34, 22HPI32, ZP39), reflecting her technical expertise in chemical process systems. Her research spans Chemical Engineering with pronounced interdisciplinary extensions into Energy Systems, Sustainable Development, and Economic Policy. She maintains a strong regional focus on Serbia and the Western Balkans, addressing critical issues in resource management, energy transitions, and socio-economic development. Her methodology frequently employs multicriteria decision analysis and policy modeling to tackle complex real-world challenges. Analysis of her publication history (2009-2021) reveals three dominant thematic clusters: renewable energy implementation for national development, forensic audit practices in corporate governance, and tourism financing models for regional growth. Her work consistently bridges engineering principles with economic policy considerations, demonstrating exceptional versatility across traditionally distinct academic domains while maintaining relevance to Serbia's developmental priorities.
Dr. Anastasios Tsiamis is a Lecturer at the Department of Information Technology and Electrical Engineering at ETH Zürich, working in the Automatic Control Laboratory (Professur Control and Computation). His research focuses on the intersection of control theory and machine learning, specifically investigating how system theoretic properties affect the statistical difficulty of learning in system identification, online estimation, and control. Dr. Tsiamis received his Diploma (MEng, five-year degree) in Electrical and Computer Engineering from the National Technical University of Athens (NTUA). He completed his Ph.D. in Electrical and Systems Engineering at the University of Pennsylvania under Professor George Pappas, following graduate research with Professor Petros Maragos and undergraduate work with Professor Kostas J. Kyriakopoulos at NTUA. His primary research areas include Statistical Learning and Control, Data-Driven Control, Online Learning, Risk-Aware Control, and Security and Privacy in Networked Control Systems. Dr. Tsiamis has made significant contributions to understanding the fundamental statistical limits of learning in control systems, particularly focusing on sample complexity. His work on risk-aware optimization develops algorithms that safeguard against catastrophic events while maintaining good average performance, and his security research addresses eavesdropping attacks in remote estimation and motion planning. Analysis of Dr. Tsiamis's recent publications reveals a strong focus on data-driven approaches to control theory with emphasis on distributionally robust methods, risk-aware optimization, and finite sample guarantees. His work bridges theoretical foundations with practical applications across system identification, online learning, and adaptive control, providing rigorous non-asymptotic guarantees for learning-based control algorithms. Dr. Tsiamis has received several notable research recognitions: Best student paper award at IEEE 61th Conference on Decision and Control (2022) Spotlight Presentation at 41st International Conference on Machine Learning (2024) Finalist for best student paper award at American Control Conference (2019) Finalist for young author prize at IFAC World Congress (2017) Oral presentation at 2nd L4DC Conference (2020) Dr. Tsiamis teaches Linear System Theory (227-0225-00L) at ETH Zürich and collaborates extensively with Professor John Lygeros, Professor Manfred Morari, and researchers from the University of Pennsylvania. His publication record demonstrates strong collaborative research across multiple institutions while advancing theoretical foundations of learning-based control. As an active member of the Automatic Control Laboratory at ETH Zürich, Dr. Tsiamis contributes to advancing control systems science through rigorous mathematical analysis and innovative algorithmic development, with applications spanning robotics, energy systems, and networked control.
Dr Anthony J H Simons is a Senior Lecturer in the Department of Computer Science at the University of Sheffield, where he serves as Deputy Director of UG Admissions. He is a member of the Testing research group and has been affiliated with the university since completing his PhD there. His academic journey spans several decades, moving from speech recognition systems to object-oriented programming languages and currently focusing on model-based testing and cloud computing applications. Dr Simons holds an MA in Modern Languages from the University of Cambridge and a PhD in Computer Science from the University of Sheffield. His educational background in both humanities and technical fields has informed his interdisciplinary approach to software engineering research. His primary research interests center around turning formal verification results into practical software engineering benefits. Currently, he investigates Model-Based Testing and Model-Driven Engineering with applications to Cloud Computing. Earlier in his career, he made significant contributions to object-oriented software engineering, including type theory and software development methods. He is the inventor of the JWalk automatic software testing tool for Java and the JAST library for processing XML in Java, and co-author of the OPEN Toolbox of Techniques. His work bridges theoretical computer science with practical software development needs. Analysis of his recent publications reveals a clear trajectory from foundational work in object-oriented type theory to applied research in cloud computing and model-based testing. His scholarship demonstrates consistent focus on formal methods applied to practical software engineering challenges, with increasing emphasis on cloud infrastructure testing and verification in recent years. Dr Simons has secured significant research funding as Principal Investigator, including the Broker@Cloud project (EC-FP7, £323,688, 2012-2015), Future Engineering System (InnovateUK, £199,874, 2016-2019), and Ferromone Trails Concept (Department for Transport, £24,635, 2017). He has supervised numerous undergraduate and masters' projects throughout his career and continues to mentor students despite being semi-retired. He leads the Testing research group at Sheffield and has developed several research projects including CatWalk (a software testing tool for Java), ReMoDeL (a conceptual modeling language), and tools for verifying specifications and generating tests for software services in the cloud. His research has practical applications in cloud service brokerage and quality assurance.
Christopher Zach is a Research Professor at Chalmers University of Technology, affiliated with the Signal Processing and Medical Technology department within the Digital Image Systems and Image Analysis research group . His work focuses on 3D reconstruction , real-time computer vision , and numerical optimization for machine learning. Develops 3D image understanding techniques Specializes in robust optimization for vision systems Leads research in medical image analysis Recent publications demonstrate expertise in low-light text enhancement , out-of-distribution detection , and domain adaptation for industrial applications. Active in Chalmers' Wallenberg AI and ÅForsk funded projects. Collaborates with researchers from Volvo Group , Volvo Cars , and SAFER Vehicle Safety initiatives.
Dr. Marnix Naber is an Assistant Professor at the Department of Experimental Psychology, Faculty of Social and Behavioural Sciences, Utrecht University. He leads the Psychophysiology of Perception Laboratory and maintains a collaboration with Harvard University's Vision Sciences Lab. Current affiliations: Utrecht University (Experimental Psychology), Neurolytics (HR technology), and Holland Startup (external PhD supervision) Previous roles: Leiden University (Cognitive Psychology Unit), Harvard University (Vision Sciences Lab), Philipps-University Marburg (Neurophysics PhD) Research Focus: Integrates psychophysiology with visual perception and consciousness studies. Key methods: pupillometry, EEG, eye tracking, remote photoplethysmography, and computational modeling. Applications span clinical diagnostics, human-centered AI, and HR technology. The 2013-2022 publications show strong emphasis on pupil dynamics (7/15), binocular rivalry (2/15), and remote physiological measurement (3/15). Methodological contributions include open-source MATLAB rPPG tools and standardized reporting frameworks. Scientific Impact: ERC Consolidator grant supporting AttentionLab research NWO grant for 2013 imitation studies Google Scholar: Q4HBMeoAAAAJ Advising: Supervises multiple PhD and Master's students across experimental psychology, ophthalmology, and neurotech domains. Laboratory Activities: Develops and shares open-source tools like rPPG for heart rate detection and maintains active collaborations with medical (UMC Utrecht), tech (Neurolytics), and academic institutions (Harvard, Leiden).
Dr. Anwar Ali is a Lecturer in the Department of Electronic and Electrical Engineering at Swansea University's Bay Campus, United Kingdom. He earned his MSc (2010) and PhD (2014) in Electronic Engineering from Politecnico di Torino, Italy. His academic roles include postgraduate supervision and teaching modules like EG-152: Analogue Design EG-158: Software Engineering EG-252: Embedded System Design EG-319: Integrated Circuit Design His research focuses on power electronic converters, embedded systems, satellite technologies (power management, attitude determination), and thermal modeling of aerospace systems. Recent work spans autonomous vehicle mobility management, medical imaging diagnostics, and multisource energy harvesting. He has authored over 50 publications and led five research projects as Principal Investigator. Dr. Ali supervises PhD students in areas like wireless power transfer for medical devices and satellite control optimization. His teaching emphasizes practical engineering applications, including PCB design, Python programming, and thermal analysis of spacecraft systems.
Nele Vandersickel is an Associate Professor in the Department of Physics and Astronomy at Ghent University's Faculty of Sciences. Her research bridges physics and cardiology, focusing on the application of computational methods and network theory to understand cardiac arrhythmias. She leads multiple research projects funded by the Research Foundation - Flanders (FWO) and European funding programs, with current work extending through 2025-2029 including a BOF-ZAP professorship in biophysics. Dr. Vandersickel's research interests center on cardiac biophysics, particularly the development and application of Directed Graph Mapping (DGM) as a novel approach for analyzing cardiac arrhythmias. Her work integrates topology , network theory , and computational modeling to investigate mechanisms of atrial and ventricular arrhythmias. She has pioneered methods to identify critical boundaries in atrial tachycardia, analyze fibrotic tissue effects on arrhythmia drivers, and distinguish between different types of cardiac reentry patterns. Her research has significant clinical implications for improving cardiac mapping and ablation procedures. Analysis of her recent publications reveals a clear trajectory from fundamental physics research toward increasingly clinically relevant cardiac electrophysiology applications. Her work now focuses on translating topological approaches into clinical tools that can automatically detect critical arrhythmia boundaries and improve understanding of complex reentrant circuits. The research spans from basic computational modeling to validation in animal models and clinical data analysis. Principal Investigator for 'Directed networks as a novel approach for improving the management of cardiac arrhythmias' (2021-2027, European funding) Promotor for 'Networks and topology to tackle cardiac arrhythmia' (2025-2026, Special Research Fund) Administrative supervisor for multiple doctoral projects on directed graph mapping applications Recipient of BOF-ZAP professorship in biophysics (2019-2029) Dr. Vandersickel actively mentors the next generation of researchers, currently supervising multiple doctoral students including Arthur Santos Bezerra, Robin Van Den Abeele, and Bjorn Verstraeten. Her laboratory develops computational tools like the DG-Mapping software package that enable analysis of reentry and focal activation patterns in cardiac arrhythmias. The research group collaborates extensively with clinical electrophysiologists to ensure their computational approaches address real clinical challenges in arrhythmia diagnosis and treatment.
Michael Ian Shamos is a Distinguished Career Professor at Carnegie Mellon University's School of Computer Science, with appointments in the Language Technologies Institute and Software and Societal Systems Department. His career spans academia, law, and technology entrepreneurship, with expertise in experimental mathematics, artificial intelligence, and legal aspects of technology. Dr. Shamos earned his educational credentials through an impressive multidisciplinary path: A.B. in Physics from Princeton University (1968) under John Wheeler M.A. in Physics from Vassar College (1970) M.S. in Technology of Management from American University (1972) M.S. and M.Phil. in Computer Science from Yale University (1973-1974) Ph.D. in Computer Science from Yale University (1978) J.D. from Duquesne University (1981) His research interests bridge multiple domains with exceptional depth. In experimental mathematics, he develops computational systems that automatically generate and prove novel mathematical theorems, particularly in number theory, having contributed hundreds of new results to the field. As a leading expert in electronic voting security, he has examined over 120 voting systems for seven states and testified before Congress multiple times. His work uniquely integrates legal expertise with technical knowledge, especially regarding intellectual property in the digital age. He directs the M.S. in Artificial Intelligence and Innovation program at CMU, advising 74 students in this cutting-edge field. His publication trajectory reveals an evolution from foundational computational geometry (co-authoring the seminal "Computational Geometry: An Introduction") to contemporary issues in voting security and experimental mathematics. The consistent thread is applying computational methods to solve real-world problems with careful attention to legal and societal implications. His notable recognitions include: Industry Service Award of the Billiard and Bowling Institute of America (1996) Black and White Scotch Achiever's Award for contributions to bagpipe musicography (1991) As an educator and mentor, Dr. Shamos directs the M.S. in Artificial Intelligence and Innovation program and teaches courses including "AI & Future Markets" and "The Law of Computer Technology." He has served as an expert witness in over 360 legal cases involving computer technology and has been a statutory examiner of computerized voting systems for Pennsylvania since 1980. His extensive industry experience includes founding technology companies and serving as General Counsel for an AI company. Dr. Shamos is actively involved with the Universal Library project, which has scanned over 1.5 million books. He also serves as faculty advisor to the Carnegie Mellon Pool Team and is Curator of The Billiard Archive, reflecting his deep commitment to preserving billiards history alongside his academic pursuits.
Professor Jonathan Paxman is a faculty member in the School of Civil and Mechanical Engineering at Curtin University, affiliated with the Faculty of Science and Engineering and the Office of the Provost. He holds a PhD (Cantab.) and is a Fellow of the Institute of Engineers Australia (FIEAust) and the Society for Higher Education in Australia (SFHEA). His research focuses on space systems engineering, meteor detection, planetary crater analysis, assistive technologies, and autonomous robotics control. Education: PhD in Engineering from the University of Cambridge (Cantab.), MPhil, and professional certifications in engineering and higher education. Teaching: Courses include Microcontroller Project and Linear Systems and Control . His research innovations include the Desert Fireball Network (DFN), a continental-scale meteor tracking system, and the Fireballs in the Sky citizen science app. He has pioneered automatic crater detection algorithms for Mars surface dating and developed control systems for autonomous spacecraft and robots. Key awards include the 2021 Research Team of the Year (Binar Space Program), 2016 Eureka Prize for Innovation in Citizen Science, and multiple teaching excellence citations. His work bridges academia and industry through projects like the Binar lunar mission series and assistive technologies for disability support. Grants and collaborations: Extensive funding for space exploration and planetary science projects. His team’s work has led to meteorite recoveries (e.g., Murrili) and contributed to Mars surface age mapping. Active in STEM outreach and curriculum innovation, including transforming pedagogy in science and engineering education. Labs/Teams: Leads the Desert Fireball Network and collaborates with NASA, ESA, and industry partners on space systems and planetary research initiatives.
Prof. Dr. Torsten Brinda holds the Chair for Didactics of Informatics at the University of Duisburg-Essen's Faculty of Computer Science. His research centers on competency modeling in programming, digital education frameworks, and computer science pedagogy. He serves as chair of the GI department for computer science education and received the IFIP Service Award in 2022. Key research areas include: Modeling of digital competencies for teachers/students Automatic assessment in programming education International curriculum standards for CS education His publications (2015-2022) demonstrate consistent focus on educational informatics, featuring competency modeling studies, global CS education analyses, and contributions to the Dagstuhl Declaration on digital education. Recent work explores integrated digital competency frameworks for teacher training.
Daniel Brazier is a part-time Research Affiliate at George Mason University, focusing on advanced computing systems research. His work intersects autonomic computing, cybersecurity, and distributed systems optimization. He specializes in performance modeling for cloud/fog environments, dynamic reconfiguration strategies, and resilience engineering. Key research areas include: Autonomic resource management in edge and cloud systems Stochastic optimization algorithms Security mechanisms like moving target defense Performance-security tradeoff analysis Decentralized runtime system modeling His recent work emphasizes practical frameworks for distributed system trustworthiness and adaptive elasticity control under variable workloads. Outputs include novel meta-heuristic algorithms for virtual network optimization and analytic models for parallel server architectures. Publications highlight contributions to fog/cloud computing, manufacturing process optimization, and security-aware system design. Current efforts focus on applying decision analytics to smart manufacturing and autonomic emergency department frameworks.
Claudio Mandrioli is a Postdoctoral Researcher at the Interdisciplinary Centre for Security, Reliability and Trust (SnT) at the University of Luxembourg, where he joined the Software Verification and Validation (SVV) research group led by Prof. Lionel Briand and Prof. Domenico Bianculli in January 2023. His educational background includes a PhD in Automatic Control from Lund University (Sweden, 2022), a Master's degree in Automation and Control Engineering from Politecnico di Milano (2017), and a Bachelor's degree in the same field from Politecnico di Milano (2015). Mandrioli's research centers on bridging software engineering and control theory for Cyber-Physical Systems (CPS), with emphasis on verification challenges arising from their interdisciplinary nature. His work integrates control-theoretical perspectives into software testing, particularly for feedback-based systems and self-adaptive software, while addressing real-time execution non-idealities. This approach enables more robust validation frameworks for safety-critical CPS applications. His recent publication trends highlight a strong focus on model-based CPS testing methodologies, as evidenced by the 2025 ASE conference paper on fault injection techniques for Simulink models, reflecting his ongoing commitment to enhancing verification practices through cross-disciplinary collaboration. SIGBED-SIGSOFT Frank Anger Memorial Award (2022) Marie Skłodowska-Curie Actions Postdoctoral Fellowship for ConTestCPS project (2024) Mandrioli actively contributes to the academic community through program committee roles at EMSOFT, SEFM, and FSE conferences, while advising doctoral research via the Software Engineering Doctoral Symposium. His research is supported by competitive grants including the MSCA-PF ConTestCPS project, which develops control-theoretical testing frameworks for CPS. He operates within the Software Verification and Validation research group at SnT, collaborating closely with Prof. Domenico Bianculli and Prof. Lionel Briand, and maintains partnerships with institutions including Lund University, Politecnico di Milano, and Fondazione Bruno Kessler.
Anna Mujal Colilles is an Associate Professor at the Universitat Politècnica de Catalunya (UPC), specifically affiliated with the Faculty of Nautical Engineering of Barcelona (FNB) within the Department of Nautical Science and Engineering. She holds a PhD in Civil Engineering and serves as a researcher at the CREMIT - Centre de Recerca de Motors i Instal·lacions Tèrmiques. Her academic career spans multiple research domains with 97 documented research activities as of the latest data. Her primary research interests include Maritime Engineering, Fluid Mechanics, and Geospatial Analysis of Ship Data using Automatic Identification System (AIS) and Vessel Monitoring System (VMS) technologies. Her work bridges theoretical fluid dynamics with practical maritime applications, particularly focusing on vessel traffic patterns, port operations, and environmental impacts of maritime activities. Recent publications demonstrate her growing interest in maritime education challenges, particularly absenteeism patterns in nautical studies. Dr. Mujal Colilles' research output shows consistent productivity across multiple disciplines, with recent publications spanning from vessel motion monitoring to offshore wind energy impacts and fisheries management. Her work aligns with several Sustainable Development Goals, particularly Affordable and Clean Energy (SDG 7) and Life Below Water (SDG 14), reflecting her commitment to environmentally sustainable maritime practices. She maintains active collaborations with numerous researchers across UPC, particularly with Marcel·la Castells-Sanabra, Xavier Gironella, and Mark James. Her research projects often involve interdisciplinary teams addressing complex maritime challenges from multiple perspectives including engineering, environmental science, and social sciences. Her methodological approach emphasizes empirical data collection combined with advanced analytical techniques, particularly in geospatial data processing and fluid dynamics modeling. Recent work demonstrates increasing sophistication in handling large-scale maritime datasets and developing standardized workflows for vessel tracking analysis.
Mark S. Shephard is the Samuel A. Johnson '37 and Elizabeth C. Johnson Professor of Engineering and Director of the Scientific Computation Research Center (SCOREC) at Rensselaer Polytechnic Institute, with joint appointments in Mechanical, Aerospace and Nuclear Engineering and Computer Science departments. His research pioneers Scientific Computing and High-Performance Simulation , driving innovations in automatic mesh generation , adaptive analysis methods , and parallel adaptive simulation technologies . SCOREC's work spans five core areas: High-Performance Simulation Methods - advanced mathematical models and discretization Simulation Reliability – uncertainty quantification and adaptive techniques Massively Parallel Computations – scalable solutions for real-world engineering problems Multiscale Computations - cross-scale modeling frameworks Construction of Simulation Systems – collaborative workflow development Applications include fusion plasma, soft tissue modeling, additive manufacturing, and microelectronics. Recent publications (2022-2025) reveal intense focus on GPU-accelerated unstructured mesh methods for fusion energy research and multiscale material science, with growing emphasis on exascale computing and cyberinfrastructure for plasma physics. His work increasingly bridges computational theory with industrial applications in CAE and medical device evaluation. Professor Shephard has graduated 24 Ph.D. students and secured over 65 research grants from 13 government agencies including DOE (SciDAC Institutes, Exascale Computing Program), NSF, NIH, DoD, and NASA, plus funding from 44 industry partners. His leadership extends to SCOREC's collaborations with ten+ universities and commercial impact through medical simulation software used in arterial stent evaluation. As SCOREC's founder and director for 32 years, he integrates faculty from seven departments across Rensselaer to advance simulation technologies. His Simmetrix Inc. co-founding role demonstrates commitment to translating research into engineering solutions, with current work targeting fusion plasma systems and heterogeneous supercomputing environments.
Dr. Marcin Witkowski is an Assistant Professor at the AGH University of Science and Technology in Cracow, Poland, specializing in the Department of Electronics and Telecommunications . His work focuses on signal processing with particular emphasis on speaker verification, speech dereverberation, and multichannel audio analysis. He holds a Ph.D. (2022) and master's degree (2012) in Electronics and Telecommunication from AGH UST, alongside a B.E.E. in Acoustics Engineering (2013). Research Interests: Far-field speaker verification, speech dereverberation techniques, robust audio processing, and blind source separation. His projects include developing anti-spoofing systems and enhancing distant speech recognition in reverberant environments. Recent work explores neural network hallucinations in Whisper ASR and VR-based voice training tools. Labs/Teams : Core member of the Signal Processing Group at AGH UST. Active in EU-funded projects on multichannel signal processing and speaker recognition systems.
