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Kangwon SeoView profile

Associate Professor

• Reliability Engineering
• Quality Engineering
• System Health Monitoring
• +7 more

Kangwon Seo is an Associate Teaching Professor in the Department of Industrial and Systems Engineering at the University of Missouri, within the College of Engineering. He joined Mizzou in 2017 after completing his PhD and MS at Arizona State University and undergraduate studies at Hongik University. He teaches core courses such as probability and applied statistics for engineers and design of experiments. Education: PhD, Arizona State University MS, Arizona State University BS, Hongik University His research centers on reliability and quality engineering, with a focus on optimal experimental design , functional data analysis , and system health monitoring . He investigates failure prediction in complex systems, particularly in nuclear reactor coolant pumps and lithium-ion batteries. His work integrates advanced statistical methods to model real-world variability and improve predictive accuracy. The recent research articles reflect a strong trend in applying functional data analysis and wavelet-based signal processing to engineering reliability problems. These studies bridge theoretical statistics with practical industrial applications, particularly in energy systems and safety-critical infrastructure. Scientific Awards: No awards explicitly mentioned. Dr. Seo actively advises graduate students and leads applied research projects, including those funded through Mizzou Engineering initiatives. His team has published in peer-reviewed journals and presented at major conferences such as the IEEE Reliability and Maintainability Symposium. He emphasizes real-world impact, particularly in sustainability, energy systems, and public safety. He is part of the Industrial and Systems Engineering research group at Mizzou, collaborating on interdisciplinary projects related to manufacturing systems, health monitoring, and data-driven decision making. The team works on developing scalable methods for early fault detection and lifecycle prediction in engineering systems.

Gary B LamontView profile

Professor

• Evolutionary Algorithms
• Multi-Objective Optimization
• Computational Intelligence
• +7 more

Dr. Gary B. Lamont is a Professor in the Department of Electrical and Computer Engineering at the Air Force Institute of Technology (AFIT), part of Air University. His work bridges computational intelligence, evolutionary algorithms, and defense systems engineering, with extensive applications in aerospace, cybersecurity, and autonomous systems. Ph.D., University of Minnesota Institute of Technology, 1970 Master of Science in Electrical Engineering, University of Minnesota Institute of Technology, 1967 Bachelor of Physics, University of Minnesota Institute of Technology, 1961 Dr. Lamont’s research centers on multi-objective evolutionary algorithms (MOEAs) , with applications in UAV swarm mission planning, network intrusion detection, image processing, and protein structure prediction. He has pioneered the use of evolutionary computation in military and defense contexts, including radar waveform design, satellite constellation planning, and autonomous agent behavior generation. His work often integrates swarm intelligence, artificial immune systems, and distributed optimization techniques. The recent publications highlight a strong trend toward military and defense applications of computational intelligence, particularly in electronic warfare, space surveillance, and cyber defense. His work frequently employs multi-objective optimization to balance competing constraints in real-world systems such as radar, UAV swarms, and network security architectures. Image processing and signal transformation using evolved algorithms also remain active areas, especially for defense imaging and compression. IEEE Fritz Russ Bio-Engineering Award, 2008 IEEE Senior Life Member, 2004 Eta Kappa Nu AFIT Teacher of the Year, 2002 WPAFB Professional Employee of the Year, 1981 Best Presentation Award, Institute of Navigation, 2008 BEST PAPER AWARD, Gameon North America '09 Best Paper Award Nominee, IEEE SSCI 2007 Dr. Lamont has advised numerous graduate students, including Jeremy Stringer, Mark Kleeman, and Dustin Nowak, many of whom have co-authored significant publications with him. His research has been supported by the U.S. Air Force and other defense agencies, enabling high-impact work in autonomous systems, network security, and optimization under uncertainty. He has led projects involving multi-agent systems, self-organized swarms, and parallel evolutionary algorithms, often in collaboration with institutions like Wright-Patterson Air Force Base. His research group at AFIT operates at the intersection of computational intelligence and defense engineering, focusing on self-organized UAV swarms , evolutionary intrusion detection systems , and adaptive signal processing . The team utilizes high-performance computing environments and simulation platforms like Swarmfare to test swarm behavior and mission planning algorithms. The lab emphasizes software engineering discipline in AI systems, as seen in tools like jREMISA, and integrates biological metaphors such as immune systems and genetic algorithms into robust cyber defense frameworks.

Steven FentonView profile

Senior Lecturer

• Low Power Systems
• Health Innovation
• Remote Health/Wound Monitoring
• +6 more

Steven Fenton is a Senior Lecturer and Subject Area Leader in Engineering at the Department of Engineering & Technology, School of Computing and Engineering, University of Huddersfield. He holds a 1st Class Honours degree in Electronic & Information Engineering from the University of Huddersfield and has extensive industry experience in audio engineering, DSP, and embedded systems design. Current research focuses on low power systems, remote health monitoring, audio signal processing, and immersive audio technology. Active member of the Audio Engineering Society and Centre for Audio and Psychoacoustic Engineering. His work spans audio quality measurement , dynamic range optimization , and assistive technologies for the visually impaired. Recent publications highlight innovations in immersive audio mixing and ultra-low energy distributed monitoring systems. Scientific contributions include a Fellow of the Higher Education Academy and an h-index of 67. Available for PhD supervision in engineering and audio technology domains.

Müjdat ÇetinView profile

Professor

• Signal Processing
• Image Processing
• Data Science
• +12 more

Müjdat Çetin is a Professor of Electrical and Computer Engineering and serves as the Robin and Tim Wentworth Director of the Goergen Institute for Data Science and Director of the New York State Center of Excellence in Data Science at the University of Rochester. He previously held faculty positions at Sabancı University and was a Research Scientist at MIT, with visiting roles at Boston University, Northeastern University, and MIT. Education: PhD in Electrical Engineering, Boston University, 2001 MS in Electrical Engineering, University of Salford, 1995 BS in Electrical Engineering, Boğaziçi University, 1993 His research lies at the intersection of signal processing, machine learning, and data science, with applications in biomedical imaging, radar, and brain-computer interfaces. He develops probabilistic and deep learning models for robust information extraction from noisy and complex data. His work emphasizes computational imaging, sparse representations, and multimodal data fusion. The recent publications reflect a strong trend toward integrating Bayesian methods and deep learning in imaging sciences, particularly in medical image reconstruction, neuroimaging analysis, and radar systems. His group actively explores transformer architectures, federated learning, and model-based deep learning for solving inverse problems in imaging. Scientific Awards and Honors: IEEE Fellow IEEE Signal Processing Society Best Paper Award IET Radar, Sonar and Navigation Premium Award Elsevier Signal Processing Best Paper Award Turkish Academy of Sciences Distinguished Young Scientist Award (GEBİP) ODTÜ Mustafa Parlar Foundation Research Incentive Award TÜBİTAK Career Award Boston University Best Engineering Research Award Professor Cetin has advised numerous PhD and Master’s students and led significant research grants in data science and imaging. He has served as a Senior Area Editor for IEEE Transactions on Image Processing and IEEE Transactions on Computational Imaging, and held editorial roles in several top journals. He has chaired major conferences including ICASSP, ICIP, and IVMSP workshops. He leads a multidisciplinary research group focused on data science and imaging, collaborating with neuroscientists and medical researchers. The team develops novel algorithms for brain-computer interfaces, medical image analysis, and remote sensing systems, often integrating machine learning with physical models of data acquisition.

• Numerical Analysis
• Iterative Methods
• Nonlinear Equations
• +7 more

Vicente Fco Candela Pomares is an Associate Professor in the Department of Mathematics at the Faculty of Mathematics, University of Valencia, Spain. His academic career has been centered on numerical analysis and computational mathematics, with a focus on iterative methods for nonlinear equations and multiresolution techniques. His research interests lie primarily in Numerical Analysis , especially iterative root-finding methods such as Halley, Chebyshev, and Steffensen-type algorithms. He has contributed significantly to the convergence analysis of these methods, particularly in Banach spaces and for ill-conditioned problems. His work extends to multiresolution analysis , wavelets , and image restoration , where he applies fractional regularization and nonlinear approximation frameworks. The trends in his recent publications show a sustained focus on derivative-free iterative methods , convergence theory , and applications in image processing . His work often bridges theoretical numerical analysis with practical computational challenges. He earned his PhD from the University of Valencia in 1988 under the supervision of Dr. Antonio Marquina Vila, with a thesis on a priori error estimators for iterative methods. He has collaborated extensively with researchers including Sergio Amat, Sonia Busquier, and Rosa Peris. Notable co-authors include Pantaleón D. Romero and Francesc Aràndiga. His publications appear in high-quality journals such as Journal of Computational and Applied Mathematics , Applied Mathematics and Computation , and SIAM journals. He is actively affiliated with the University of Valencia, as evidenced by his institutional email and ongoing publications. There is no indication of part-time status, retirement, or awards in the available data.

• Acoustics
• Signal Processing
• Room Impulse Response
• +7 more

Dejan G. Ciric is a Full Professor at the Faculty of Electronics in Niš, University of Niš, Department of Telecommunications. He has been a central figure in acoustics and signal processing research, with a strong international presence through collaborations at Aalborg University (Denmark) and IRCAM (France). His work bridges theoretical acoustics and practical applications in industrial and automotive sound analysis. PhD, Master’s, and BSc in Telecommunications from Faculty of Electronics in Niš Specialization in Acoustics, Aalborg University, Denmark (2002–2003, 2003–2007) His research focuses on acoustics, room impulse response, sound measurement, and signal processing , particularly using image similarity measures, wavelets, and machine learning for sound analysis. He investigates nonlinear effects in measurements, truncation correction, and air absorption in scale models. His recent work emphasizes industrial product sound, vehicle noise, and DC motor diagnostics through spectrogram analysis and automated systems. The trend in his publications (2023–2002) shows a consistent focus on improving the accuracy and automation of acoustic measurements, especially in complex environments. He applies mathematical models, signal processing techniques, and cross-domain methods (e.g., treating sound as images) to solve real-world problems in audio engineering and diagnostics. He has received notable recognition: Research in Paris 2013 award (IRCAM, France) Young Investigator Award, International Commission for Acoustics (2007) Dejan Ciric has participated in 5 national and 5 international projects in the past, and is currently involved in 1 national and 1 international project . He has advised students and contributed to academic training in acoustics and telecommunications. His work has resulted in 18 publications in journals with impact factors . He has been affiliated with research teams at Aalborg University’s Department of Acoustics and the IRCAM Institute in Paris , contributing to projects on audiometric calibration, machine learning for sound directivity control, and advanced acoustic measurement systems.

• Computer Engineering
• Digital Logic Design
• Signal Processing
• +3 more

Dragan S. Janković is a Full Professor at the Faculty of Electronic Engineering, University of Niš, specializing in Computer Science. His academic career spans over three decades with continuous research contributions since his doctorate in 2001. His educational background includes: Diploma in Electrical Engineering and Computing (1991) Master's in Electrical Engineering and Computing (1995) PhD in Electrical Engineering and Computing (2001) All obtained at the Faculty of Electronic Engineering, University of Niš. Professor Janković's research focuses on advanced computational methods in digital systems, with particular expertise in multi-valued logic, spectral transforms, and decision diagram techniques. His work bridges theoretical computer science with practical circuit design applications, emphasizing optimization algorithms for logic synthesis and signal processing. Current investigations involve recursive algorithm development for polarity matrices and wavelet-based circuit minimization. His publication record shows consistent contributions to high-impact journals, with research trends indicating sustained focus on computational logic structures and their engineering applications over the past 25 years. Key methodological contributions include novel tabular techniques for multi-valued logic and efficient implementations of decision diagram packages. Professor Janković actively participates in research projects with 5 national and 3 international collaborations currently underway, demonstrating ongoing engagement in the academic community.

In Young MinView profile

Lecturer

• International Relations
• Security Studies
• East Asian Politics
• +3 more

In Young Min is a Lecturer in Korean studies at the Centre for East Asian Studies, Heidelberg University. He holds a B.A. and M.A. in Political Science from Yonsei University (South Korea), and a Ph.D. in Political Science and International Relations from the University of Southern California. His research focuses on international relations and security in East Asia, particularly the dynamics of power asymmetry and smaller states' agency in shaping these dynamics, with a regional focus on Korea. Recent work examines historical and contemporary issues surrounding the Korean Peninsula, including nuclear policy and unification treaties. His interdisciplinary contributions span political theory and historical analysis. Education History: B.A. and M.A. in Political Science, Yonsei University, South Korea Ph.D. in Political Science and International Relations, University of Southern California Research Interests: Power asymmetry dynamics in international relations Ontological security and identity in hierarchical systems Korean Peninsula security and unification South Korea's nuclear policy and non-proliferation challenges Publications Trends: His work bridges historical and contemporary analyses, with contributions to journals like the International Relations of the Asia-Pacific and Journal of Asian Security and International Affairs . Earlier technical articles in mathematics and computational methods reflect interdisciplinary engagement, though recent focus is on political science and international relations.

• Computer Engineering
• Embedded Systems
• Image Processing
• +3 more

Kranitis Nektarios is a Lecturer at the Department of Informatics and Telecommunications, National and Kapodistrian University of Athens. His research focuses on FPGA-based hardware architectures, space-grade computing, and image compression standards like CCSDS, with applications in satellite systems and reliable data processing. Primary affiliation: National and Kapodistrian University of Athens Department: Informatics and Telecommunications Research interests center on space-grade SRAM FPGAs , LDPC encoding , hyperspectral image compression , and software-based self-test methodologies for embedded systems. His work addresses high-speed data processing and fault tolerance in satellite communications. Key trends in his publications include CCSDS standard implementations , hardware accelerators for image compression, resilience to SEUs , and energy-efficient testing techniques for microprocessors. Topics span space systems , parallel computing , and digital circuit design .

Robert MillerView profile

Professor

• Psychological Methodology
• Psychobiology
• Stress Research
• +4 more

Robert Miller holds the Professorship for Psychological Methodology at the Department of Psychology, Humboldt University of Berlin. His academic work centers on advancing methodological rigor in psychological science through interdisciplinary approaches bridging statistics, neuroscience, and digital technology. Miller's research program integrates core domains including stress physiology (using cortisol biomarkers), digital health application development, and psychometric instrument validation. He pioneers methods for high-dimensional data analysis in "large-p, small-n" scenarios, Bayesian evidence generation frameworks, and meta-psychological standardization of research protocols. His work consistently emphasizes ecological validity through comparisons of laboratory versus real-world settings. Publication trends reveal Miller's strategic focus on methodological innovation across stress measurement and digital health. His recent work demonstrates increasing integration of signal processing techniques (e.g., wavelet transforms) with psychological assessment, alongside cross-national validation studies of stress biomarkers. A distinctive pattern involves translating complex statistical models into practical tools for clinical outcome assessment while maintaining rigorous psychometric properties.

Sarah Eberle-BlickView profile

Senior Lecturer

• Numerical Analysis
• Inverse Problems
• Partial Differential Equations
• +7 more

Sarah Eberle-Blick is a Senior Lecturer at the Institute of Mathematics , Goethe University Frankfurt, Department of Computer Science and Mathematics. Her work bridges numerical methods, inverse problems, and wave propagation in elasticity. Research Focus : Numerical analysis of PDEs, monotonicity methods for inclusion detection, FEM-BEM coupling, multiscale seismic data processing. Key Contributions : DFG-funded projects on elastic wave reconstruction; development of stable integral formulations for acoustic and thermoelastic wave equations; implementation of 3D wave simulations. Article Trends : Recent papers emphasize inverse problems in linear elasticity, time-harmonic wave equations, and multiscale analysis using wavelets. Collaborative work spans geophysics, computational mechanics, and mathematical modeling. Projects : Includes monotonicity-based regularization, Lipschitz stability estimation, and FEM-BEM coupling with convolution quadrature. Contact: eberle@math.uni-frankfurt.de | Room 103, Institute of Mathematics, Frankfurt am Main, Germany.

Sri KrishnanView profile

Professor

• Biomedical Signal Analysis
• Wearables/Textile Computing
• Assistive Technology
• +5 more

Dr. Sri Krishnan is a Professor and Dean at the Department of Electrical, Computer, and Biomedical Engineering at Toronto Metropolitan University. With a focus on interdisciplinary research, he bridges electrical engineering, computer science, and biomedical applications. His work emphasizes mathematical signal analysis for healthcare solutions. PhD, University of Calgary (1999) MSc, University of Calgary (1996) BE, College of Engineering, Guindy, Anna University (1993) Research Interests: Dr. Krishnan specializes in biomedical signal analysis, affective computing, and compressive sensing. He develops wearable technologies and machine learning algorithms for applications in mental health, cardiovascular diagnostics, and neurological disorders. Scientific Contributions: His recent publications highlight advancements in fetal ECG separation, seizure detection via EMD dictionaries, acoustic scene classification using local binary patterns, compressive sensing in gait signals, and wavelet-based gait diagnostics. Fellow, Canadian Academy of Engineering Outstanding Canadian Biomedical Engineer Award Canada Research Chair in Biomedical Signal Analysis Sarwan Sahota Distinguished Scholar Award Laboratory: He leads the Signal Analysis Research Group, fostering innovation in time-frequency theory and non-stationary signal processing.

Antoni Jaume-i-CapóView profile

Professor

• Artificial Intelligence
• Explainable Artificial Intelligence
• Computer Vision
• +3 more

Dr. Antoni Jaume-i-Capó is a Full Professor in the Department of Mathematics and Computer Science at the University of the Balearic Islands (UIB) , affiliated with the Computer Graphics and Vision and Artificial Intelligence Group (UGiVIA) and serving as Director of the Artificial Intelligence Applications Laboratory (LAIA@UIB) . His work bridges Artificial Intelligence , Computer Vision , and Medical Imaging with applications in Motor Rehabilitation and Explainable AI (XAI) . Research Interests : Artificial Intelligence, Explainable AI, Computer Vision, Human-based Computation, Intelligent Systems for Motor Rehabilitation, Medical Imaging Processing. Teaching : Courses include Algorithmics and Data Structures , Final Degree Projects , and Practical Placements for Informatics Engineering degrees across multiple campuses. Scientific Contributions span 15 recent publications focusing on XAI fidelity metrics , medical image analysis , and crowdsourced diagnostics . These works integrate machine learning for Sickle Cell Disease classification and kinect-based rehabilitation systems . Scientific Awards : Premio al mejor trabajo JENUI 2010 Students : Supervised over 11 PhD/Master’s students, including Gabriel Moyà-Alcover and Pedro Marrero-Fernández. Projects : Leads EU-funded initiatives like EXPLAINME and EUGAIN , alongside regional efforts such as People4Sicklemia .

Fahrettin HorasanView profile

Associate Professor

• Machine Learning
• Data Security
• Recommender Systems
• +3 more

Dr. Fahrettin Horasan is an Associate Professor in the Department of Computer Engineering at the Faculty of Engineering and Natural Sciences . His research focuses on applied computational methods in data security, machine learning, and information retrieval systems. Specialized in medical image watermarking and encryption using matrix decomposition techniques (SVD, ULV) Developed novel collaborative filtering recommender systems with hybrid approaches and matrix approximation Contributions in sentiment analysis for healthcare and e-commerce domains His recent publications highlight interdisciplinary work combining cryptology, biomedical imaging, and large-scale data processing. Notable methods include chaotic system-based encryption, latent semantic indexing, and gradient boosting for darknet traffic analysis. While specific awards, educational background, and student advisement details are not publicly detailed in the provided texts, his technical output reflects active engagement in computational science advancements.

• Computational imaging
• Computational physiology
• Signal processing
• +4 more

Dr. Hamid Abbasi is a Senior Research Fellow affiliated with the Auckland Bioengineering Institute , Center for Brain Research , and Department of Physiology at the University of Auckland. His work bridges computer science , bioengineering , and clinical medicine , focusing on AI-driven solutions for neurosurgical navigation, drug discovery, and neonatal brain injury detection. PhD in Engineering Science (University of Auckland, 2018) Senior IEEE member with contributions to medical AI and signal processing Research Interests: Computational imaging and physiology Transformer architectures for EEG analysis Automated biomarker detection in hypoxic-ischemic injury Deep learning for infant movement tracking Recent publications demonstrate transformer models outperforming CNNs in seizure detection, scalogram-based classifiers for EEG biomarkers, and 3D data fusion techniques for clinical outcome prediction. His projects involve collaborations with Auckland Hospital, the Liggins Institute, and the Department of Exercise Sciences. Scientific Awards: 2024 Future AI-Startup Award (Neurofanos) 2023 ABI Excellence in Research Translation Award 2022 Royal Society Te Apārangi Cooper Award 2022 Velocity $100k Challenge winner (Neurofanos team lead) He leads PhD supervision opportunities in AI applications for neurosurgery, drug discovery, and neonatal diagnostics via the University of Auckland.