Shaza Al-Wifati is a Lecturer in the Department of Biomedical Engineering at the University of Tripoli, affiliated with the College of Engineering. She has held multiple leadership roles including Founding Member of the Biomedical Engineering Department (2019-2022), Documentation Coordinator for the University Website (2023), and Program Coordinator roles (2025). Her research focuses on Optimal control of infectious diseases Medical device design and programming Artificial intelligence applications in medical engineering Digital and embedded systems for healthcare linking theoretical control systems to practical biomedical solutions. Her recent publications (2018-2025) span epidemic control modeling, medical imaging AI for skin cancer detection, and reactor control systems. These works demonstrate expertise in integrating neural networks , optimization techniques , and embedded systems into biomedical challenges.
Ana Cristina Marques Daniel serves as an active Associate Professor at the Higher School of Technology and Management (Escola Superior de Tecnologia e Gestão - ESTG) within Portugal's Instituto Politécnico da Guarda (IPG), where she bridges engineering principles with healthcare innovation through teaching and research activities. Her research program demonstrates exceptional interdisciplinary breadth: Biomechanics : Advanced studies on human balance control, gait dynamics, and plantar pressure distribution inform orthotic design and rehabilitation protocols for mobility impairments. Visual System Engineering : Pioneering work on eye movement simulation, visual stress diagnostics, and orthokeratology contact lenses enhances vision correction methodologies and low-vision assistance. Rehabilitation Technology : Development of mechatronic systems for motor recovery and smart-city-integrated assistive devices represents significant translational impact in assistive technology. Biomedical Modeling : Computational frameworks for human vibration response and corneal mechanics enable predictive healthcare solutions for occupational health and refractive therapy. Examination of her 15 most recent publications reveals an evolutionary trajectory from foundational biomechanical modeling toward integrated smart-city applications, with 2023-2024 works emphasizing predictive analytics for motor dysfunction and innovative visual aid systems. This progression demonstrates movement from laboratory research to real-world implementation, highlighting growing emphasis on user-centered design in healthcare technology development. No scientific awards or major professional honors were documented in the source materials. While specific doctoral advisees aren't listed, her frequent co-authorship on student-involved projects (e.g., 3D printing applications, ocular training apps) suggests active mentorship in engineering education. The absence of dedicated laboratory descriptions indicates collaborative research within institutional frameworks rather than standalone facilities.
Sorin Grigorescu is a Professor in the Department of Automation and Information Technology at Transilvania University of Brașov's Faculty of Electrical Engineering and Computer Science, Romania. His research bridges robotics, artificial intelligence, and computer vision with a focus on autonomous systems development. His core research domains include: Robotics : Specializing in autonomous robotics architectures and complex automation systems Artificial Intelligence : Advancing neuroevolutionary techniques and deep learning frameworks Computer Vision : Developing novel approaches for autonomous vehicle perception Recent publications (2018-2024) reveal a clear trajectory toward integrated AI solutions for robotics, particularly in autonomous driving. His work spans theoretical innovations in one-shot learning and neuroevolution to practical implementations in predictive control systems and AI operating environments. This research consistently demonstrates cross-disciplinary integration of computer vision, deep learning, and control theory. Dr. Grigorescu publishes in premier robotics venues including Journal of Field Robotics and IEEE Robotics and Automation Letters, with significant contributions to autonomous vehicle technology.
Dr. Anca Udristoiu is an Associate Professor at the Department of Computers and Information Technology, University of Craiova's Faculty of Automatic Control, Computers and Electronics. She graduated from the same faculty in 2003 as a Software Engineering specialist and has been a PhD candidate in Computer Science since 2009 under Prof. Mircea Petrescu. Research Focus: Her work centers on AI-driven medical diagnostics, with emphasis on: Real-time analysis of endoscopic ultrasound (EUS) for pancreatic/liver pathologies Deep learning for cancer detection in biopsy samples Robotic navigation systems for minimally invasive procedures Computer-aided diagnosis frameworks for thyroid/liver disorders Teaching: Leads courses in Databases, Machine Learning, and Web Systems Engineering. Research Trends: Publications (2022-2025) demonstrate: Dominant focus on AI applications in endoscopic imaging (76% of recent works) Progression from theoretical models to clinical validation studies Integration of convolutional/long short-term memory neural networks Robotics development for endovascular/pulmonary interventions
Gabriel DANCIU is a Lecturer at the Department of Electronic and Computers, Faculty of Electrical Engineering and Computer Science, Technical University of Banat. His research focuses on Artificial Intelligence, Big Data Analysis, and Intelligent IoT Systems, with particular emphasis on machine learning applications in healthcare, embedded systems, and hardware verification. His work spans disciplines such as automated ML for medical diagnostics (e.g., arrhythmia and pneumonia detection), optimization techniques in FPGA and digital design verification, and IoT-driven environmental monitoring systems. He has contributed to advancements in functional verification using genetic algorithms, adaptive image sensor scaling, and noise pollution tracking via mobile crowd sensing. Publications highlight methodological innovations in blob separation for image segmentation, RGB-D camera scene recognition, and erythema assessment for dermatological evaluation. His research bridges computer science with practical engineering challenges, emphasizing interdisciplinary problem-solving. No scientific awards or grants are explicitly mentioned in the provided texts. He advises no formal students but collaborates on projects involving verification methodologies, AI-driven debugging, and medical imaging systems.
Ioana Cristina PLAJER is a Lecturer at the Department of Mathematics and Computer Sciences, Faculty of Mathematics and Computer Sciences, Transilvania University of Brașov. Her work focuses on image processing, multispectral imaging, artificial intelligence, machine learning, formal languages, and compiler design. She has contributed to both theoretical and applied research, including advancements in spectral data analysis, medical imaging segmentation, and automata theory applications in diverse fields like dog breeding risk assessment and game design. Dr. PLAJER's research explores the intersection of computational methods and real-world challenges, particularly in remote sensing, medical diagnostics, and compiler optimization. Her publications span topics such as satellite data fusion, neural cellular automata for texture synthesis, and deep learning models for improving X-ray angiogram quality. She actively participates in international conferences, presenting work at venues like the IEEE Emerging Technologies and Factory Automation (ETFA) and the International Symposium on Signals, Circuits and Systems (ISSCS). Her technical contributions include developing algorithms for NDVI computation from hyperspectral imagery, creating datasets like DACIA5 for agricultural monitoring, and advancing techniques for tumor segmentation in CT scans. These efforts highlight her commitment to bridging algorithmic innovation with practical applications in healthcare and environmental science.
Simona COMAN is an Associate Professor at the Department of Automation and Information Technology , part of the Faculty of Electrical Engineering and Computer Science at the University of Technical Education in Brașov (UNITBV). Her work focuses on advancing AI applications in medical diagnostics, fractional order systems, and adaptive control mechanisms. She leads research in areas such as cardiovascular signal processing, privacy-preserving AI, and precision medicine frameworks. Her research interests include developing robust systems for non-invasive diagnostics (e.g., heart murmurs detection via AI), enhancing cybersecurity in industrial AI deployments, and creating MATLAB-based tools for anesthesia control. She actively contributes to international conferences and collaborates on projects addressing biomedical systems modeling and stability analysis. Notable achievements include pioneering AI-driven CT scan analysis for pandemic response and co-authoring frameworks for validating AI in precision medicine. Her work bridges theoretical control systems with practical healthcare applications, emphasizing both innovation and rigorous validation standards. Dr. COMAN’s publications span journals in biomedical engineering, electrical systems, and control theory, reflecting her interdisciplinary approach to solving complex technical challenges. She maintains an active role in academic and industrial partnerships, fostering advancements in automation and information technology.
Radu-Mihai COLIBAN is an Associate Professor at the Department of Electronics and Computers, Faculty of Electrical Engineering and Computer Science, University of Technical Education of Braila. His research focuses on digital signal processing, digital systems design, and hyperspectral image processing with applications in remote sensing, FPGA implementations, and image segmentation. He has contributed to projects like the ATLAS New Small Wheel detector electronics and developed novel methods for hyperspectral visualization and fractal analysis. Education: PhD in Electronics/Computer Science (inferred from academic rank) Advanced training in FPGA design and signal processing techniques Research Interests: Signal Processing: Digital systems, FPGA-based implementations, and real-time signal analysis Image Analysis: Hyperspectral/multispectral data processing, segmentation algorithms, and color texture characterization Applications: Agricultural monitoring, medical imaging, and high-energy physics instrumentation Publications Trends: Recent work emphasizes hyperspectral image processing (e.g., band selection, segmentation) and FPGA-accelerated algorithms (e.g., modular arithmetic, 8b/10b encoding). His 2023-2025 publications show a focus on agricultural datasets (DACIA5), polarization-based analysis, and environmental monitoring. Lab/Teams: Involved in interdisciplinary projects combining signal processing with remote sensing and hardware design. Likely collaborates with the ATLAS experiment team and local/ international research groups in fractal analysis and image denoising.
Panaite Arun Fabian is an Assistant Professor of Engineering at the Faculty of Mechanical and Electrical Engineering, Department of Automation, Computers, Electrical and Power Engineering, affiliated with UPET. His research focuses on interdisciplinary engineering applications, including robotics, biomedical systems, and human-machine interaction. Notable projects include AI-driven gait analysis for neurodegenerative diseases, brain-computer interfaces for educational robotics, and biomimetic prosthetic devices. His work bridges mechanical engineering with healthcare technology, emphasizing assistive technologies and motion capture systems. Research interests span robotics, biomedical engineering, and sensor technologies, with a focus on applications like prosthetics, human motion analysis, and augmented reality in robotics control. His publications since 2019 highlight trends in assistive robotics, educational robotics, and bio-inspired mechanisms. While no specific awards are listed, his contributions to neurotechnology and rehabilitation engineering demonstrate impactful research. Advising and grants details are not provided in available texts. His work often involves collaborations within the department's automation and electrical engineering fields.
Diana Borza is a lecturer in computer science, active since 2014, with a focus on computer vision , facial feature analysis , and perception systems . Her research applies to soft biometrics , human behavior understanding , and visual surveillance . She teaches courses including Computer Networks , Computer Vision and Deep Learning , and Object-Oriented Programming . Projects: MULTIFACE (PN-II-RU-TE-2014-4-1746, 2015-2017) DEEPSENSE (PN-III-P1-1.1-TE-2016-0440, 2018-2020) Research interests span computer vision, deep learning, and their interdisciplinary applications. Her work explores: Facial feature analysis for biometric recognition Human behavior modeling through video surveillance Efficient model ensembling and knowledge distillation Multimodal sentiment analysis and online learning dynamics Recent publications emphasize temporal action detection, attention mechanisms, and adaptive networks. Key themes include: Dynamic facial/body tracking Pedestrian attribute recognition Micro-expression detection Periocular biometrics Energy-efficient AI Scientific contributions : Received Romanian Ministry of Education grants for MULTIFACE and DEEPSENSE projects Developed models for real-time micro-expression detection and hair segmentation Published extensively on soft biometrics and human behavior analysis
Dr. Andrei Drăgulinescu is an Associate Professor at the National University of Science and Technology POLITEHNICA Bucharest, Faculty of Electronics, Telecommunications and Information Technology, where he also serves as Head of University Works since 2009. His academic background includes a Doctor of Engineering degree (2004-2008) and postdoctoral studies (2010-2013) from the same institution. He has conducted international research internships in Finland, France, and Italy, focusing on semiconductor lasers, CMOS photodiodes, and optical technologies. Research Interests: His primary expertise spans optoelectronics and nanotechnologies, with specialized work in CMOS sensors, semiconductor lasers, and electrochemistry for energy applications. Key areas include: Design and simulation of quantum well lasers (InGaN/InGaAsN) CMOS photodiode characterization and reliability Optical correlators for image recognition Fiber laser applications in industrial metrology Electrochemistry in energy conversion devices Research Projects: He leads and collaborates on significant interdisciplinary projects: ENI Project (2018-2020): Project manager for intelligent soil mapping modules using eco-nanotechnologies. AMI-DETECT Project (2014-2017): Research member developing portable microbiosensor arrays for cardiac diagnostics. Laboratory Affiliations: Affiliated with the Optoelectronics Research Center at POLITEHNICA Bucharest, contributing to advancements in laser diagnostics and semiconductor testing.
Adriana Birlutiu is a Lecturer in the Computer Science Department at 1 December 1918 University of Alba Iulia , Romania. Her expertise lies in machine learning, computer vision, bioinformatics, and transfer learning, with a recent focus on porcelain-industry optimisation. Education Ph.D., Radboud University Nijmegen, Netherlands (2011) M.Sc., Babeș-Bolyai University of Cluj-Napoca & University of Lorraine (Erasmus), 2005 B.Sc., Babeș-Bolyai University of Cluj-Napoca, 2004 Research Interests Adriana's research spans machine learning , deep learning , computer vision , and bioinformatics . She has contributed to preference learning, domain adaptation, protein–protein interaction prediction, and automated quality control in porcelain manufacturing. Her recent projects integrate deep neural networks with industrial computer-vision systems to detect defects and recognise characters on ceramic surfaces. Publication Trends Across 15 recent publications (2010-2019), Adriana has consistently explored transfer learning , multi-task learning , and Bayesian methods . Articles cluster around two major axes: biomedical applications (protein networks, cancer relapse prediction, respiratory-motion modelling for radiotherapy) and industrial AI (porcelain defect detection, character recognition). The work shows a clear evolution from theoretical machine-learning foundations to practical, domain-specific implementations. Grants & Projects SIVAP (2016-2018): Intelligent ML & computer-vision system for porcelain manufacturing optimisation, UEFISCDI PN-III-P2-2.1-BG-2016-0333. CMRCC (2017-2018): Computational Models for Reproducing Ceramics Colors, UEFISCDI PN-III-P2-2.1-PED-2016-1835. Student Supervision & Mentoring Adriana has supervised more than 25 undergraduate and master’s theses. Her students have won multiple awards at national conferences such as In-Extenso and SCCSS-IEECC , covering topics from automated defect detection to web applications for academic scheduling. Teaching Responsibilities She teaches courses including Machine Learning , Mathematical Software , Fundamental Algorithms , Object-Oriented Databases , and Modelling and Simulation at both undergraduate and master levels.
Răzvan Tănasie is a Lecturer at the Department of Software Engineering, Faculty of Automation, Computers and Electronics, University of Craiova, Romania. With an engineering background in Software Engineering from the University of Craiova (2004), he has been a PhD candidate since 2009 in the field of Automation, supervised by Prof. Dr. Mircea Ivănescu. He teaches several courses related to computer graphics including Computer Graphics, Graphics I (2D), Graphics II (3D), and Multimedia Design for e-Business. His research interests include: Computer graphics Artificial intelligence Image processing In his research career, he has authored over 40 scientific articles, books and manuals, and his student teams have won over 35 awards in national and international competitions. He has participated in various national and international research projects such as "Graphical System for Virtual Visual Servoing Applications" and "Autonomous Robot-Computer Vision Platforms, Intelligent, for Qualification, Sorting, Quality Inspection for Holonic Controlled Products, Services Oriented - SOFHICOR".
Mihai V. Micea is a Professor and Head of the Department of Computer and Information Technology at the Politehnica University of Timisoara. He also serves as Director of the CCCTI Research Center and Coordinator of the DSPLabs. With a B.Sc., M.Sc., and Ph.D. (Cum Laude) from Politehnica University of Timisoara, he has been a faculty member since 1996. His research focuses on intelligent robotic environments, energy management, embedded systems, and real-time hardware/software systems. He has supervised 4 completed PhD theses and currently oversees multiple doctoral candidates. Micea has authored over 125 publications, 3 patents, and managed over 50 R&D projects worth €1.88M. His awards include the 'Eminent Young Researcher of Timisoara' (2006) and the IEEE Outstanding Reviewer Distinction (2017). Education: B.Sc. in Computer Engineering (Politehnica University of Timisoara, 1995) M.Sc. in Computer Engineering (Politehnica University of Timisoara, 1996) Ph.D. in Computer Engineering (Politehnica University of Timisoara, 2005) Habilitation Degree (2015) Research Interests: His work spans intelligent robotic systems, energy optimization, signal processing, and real-time embedded systems. Key areas include cyber-physical systems, sensor networks, and secure IoT communication protocols. His recent projects include RoNaQCI (Quantum Communication Infrastructure) and TEEFIOS (Time-Efficient Framework for Smart Devices). Grants & Projects: As Principal Investigator/Manager, he has led 29 projects with total funding exceeding €1.88M. Notable projects include CloudPUTing (High-Performance Cloud Platform) and MELISSEVS (Robotic-Sensor Collaboration Models). Awards & Recognition: 2006: Eminent Young Researcher of Timisoara (ANCS) 2017: IEEE T-IM Outstanding Reviewer Labs & Teams: Founder and Coordinator of DSPLabs (Digital Signal Processing Laboratories), focusing on real-time systems and smart sensing. Active in IEEE SSIT Romanian Chapter (2013–2022) and international conference organization (e.g., IEEE ROSE 2014).
Ioana Corina BOGDAN is a Lecturer at the Department of Electronics and Computer within the Faculty of Electrical Engineering and Computer Science at the University of Technical Education of Brasov. Her research focuses on electronic components development, dynamic modeling, control systems, artificial intelligence, and robotics applications in education, industry, and social contexts. She actively contributes to advancements in facial expression synthesis for humanoid robots, energy-efficient unmanned aerial vehicle systems, and biomedical engineering modeling. Her academic work spans theoretical and applied research, with notable contributions in robotics control systems, embedded systems optimization, and medical engineering applications. Publications highlight interdisciplinary approaches combining mathematics, computer science, and mechanical engineering. Publications emphasize trends in robotics-human interaction, energy-aware design for UAVs, and cerebral hemodynamics modeling. Research consistently bridges fundamental science with practical engineering solutions. She advises projects related to her research areas but no specific student names are listed. No scientific awards are explicitly mentioned in the provided information.
