جستجوی استاد راهنمای دانشگاهی

Nazar Aliمشاهده پروفایل

دانشیار

• Antennas
• RF Circuits and Systems
• Power Amplifiers
• +۲ مورد دیگر

Dr. Nazar Ali serves as an Associate Professor in the Department of Electrical Engineering at Khalifa University, Abu Dhabi, UAE. With over three decades of academic experience since his 1990 PhD, he maintains active roles in research, teaching, and professional leadership within the electrical engineering domain. His educational foundation includes: PhD in Electrical Engineering, University of Bradford, UK (1990) BSc in Electrical Engineering, University of Mosul, Iraq (1984) Research spans cutting-edge RF engineering with emphasis on antenna design, high-efficiency power amplifiers, and indoor localization systems. His pioneering integration of Artificial Intelligence into traditional RF frameworks addresses modern wireless communication challenges, focusing on system optimization and next-generation wireless solutions. This interdisciplinary approach bridges hardware engineering with machine learning methodologies to enhance signal processing and device performance. Professional distinctions include: Senior Member of the Institute of Electrical and Electronics Engineers (IEEE) Internationally recognized Chartered Engineer certification Dr. Ali has mentored multiple MSc and PhD candidates through thesis supervision while teaching core electrical engineering curriculum including Applied Electromagnetics (ECCE320), Electric Circuits II (ECCE222), Electronic Circuits & Devices (ECCE312), and Microwave Circuits and Devices (ECCE316). His pedagogical approach combines theoretical rigor with practical laboratory implementation to develop industry-ready engineering competencies.

Baker Mohammadمشاهده پروفایل

استاد

• Very-Large-Scale Integration (VLSI)
• Hardware Accelerators for Artificial Intelligence
• Hardware Security
• +۷ مورد دیگر

Prof. Baker Mohammad serves as Professor and Director of the System on Chip Lab in the Department of Computer and Information Engineering at Khalifa University. With over 15 years of industrial experience at Intel and Qualcomm designing microprocessors and DSP chips, he bridges academic research with real-world engineering challenges in high-performance computing and low-power systems. His educational background includes: Ph.D. in Electrical and Computer Engineering, University of Texas at Austin (2008) M.S. in Electrical and Computer Engineering, Arizona State University B.S. in Electrical Engineering, University of New Mexico Dr. Mohammad's research spans cutting-edge domains where VLSI design converges with AI acceleration and emerging memory technologies . His work pioneers Memristor applications in environmental sensing (radiation, vacuum, glucose) and neuromorphic computing, while advancing energy harvesting systems for wearable electronics. The integration of in-memory computing with security primitives represents a paradigm shift in hardware design, moving beyond traditional CMOS limitations. His publication trajectory reveals accelerating focus on self-powered neuromorphic systems and RRAM-based architectures, with recent work (2021-2023) emphasizing hardware-software co-design for edge AI. Over 75% of his recent publications involve cross-disciplinary collaborations spanning materials science, chemistry, and biomedical engineering. Notable scientific recognition includes: IEEE TVLSI Best Paper Award 2016 IEEE MWSCAS Myrill B. Reed Best Paper Award Qualcomm Qstar Award for Performance Leadership KUSTAR IP Excellence Award Multiple SRC Techon Best Session Papers As a dedicated mentor, he has supervised over 15 graduate students while securing competitive funding from Khalifa University, ADEK, Qualcomm, Tii, and UAE space agencies. His grant portfolio demonstrates exceptional translational impact, converting fundamental research in memristive devices into drone flight computers and medical sensors. Current projects integrate academic rigor with industrial deployment timelines. The System on Chip Lab operates as a multidisciplinary hub where semiconductor physicists collaborate with AI researchers to develop RISC-V-based secure processors and piezoelectric nanogenerator systems. Recent expansions include partnerships with Tii for aerospace applications and medical device startups for glucose monitoring technology.

Maher Maaloufمشاهده پروفایل

دانشیار

• Machine Learning
• Data Mining
• Multivariate Statistics
• +۳ مورد دیگر

Dr. Maher Maalouf serves as an Associate Professor in the Department of Industrial and Systems Engineering at Khalifa University, where he has been a faculty member since 2011. He holds a PhD in Industrial Engineering from the University of Oklahoma and teaches core courses including Six Sigma Methodology and Applications (ISYE 445), Business Analytics (ESMA 610), and Advanced Business Analytics (ESMA 711). His academic credentials include: PhD in Industrial Engineering, University of Oklahoma (USA) MSc in Industrial Engineering, University of Oklahoma (USA) BBA in Management Information Systems, University of Oklahoma (USA) Dr. Maalouf's research integrates advanced analytical methodologies with industrial applications, focusing on classification and regression algorithms in machine learning, statistical process optimization through Lean Six Sigma frameworks, and operational excellence implementations. His work bridges theoretical data science with practical business process improvement across manufacturing and service sectors. He maintains active research supervision through the Socio-Technical Systems Lab, currently mentoring PhD students Toheeb Olajide Salahudeen and Kehinde Ganiyu Ismaila alongside Research Associate Assia Chadly. No scientific awards were documented in the source material.

Shihab Jimaaمشاهده پروفایل

دانشیار

• AI-based performance enhancement of LP-WAN technologies for IoT
• 6G wireless communications
• Atrial Fibrillation Data Analysis and Validation
• +۳ مورد دیگر

Dr. Shihab Jimaa is an Associate Professor at the Department of Computer and Information Engineering , Khalifa University, and currently serves as the Associate Dean of UG Studies at the College of Computing and Mathematical Sciences. He has held academic positions including Research Fellow, Senior Lecturer, and Assistant Professor at institutions such as Loughborough University, Warwick University, and Queen Mary University of London. PhD : Digital Communications, Loughborough University (1990) MSc : Digital Communication Systems, Loughborough University (1986) PGCE : Post Graduate Certificate in Higher Education, University of Hertfordshire (1998) Dr. Jimaa’s research focuses on energy-efficient wireless communication systems , AI-driven 6G technologies , and machine learning applications for early detection of Atrial Fibrillation . His work spans adaptive filtering, channel estimation, and signal processing in both telecommunications and biomedical engineering domains. Current projects include optimizing LP-WAN technologies for IoT scalability and developing deep learning-based scheduling techniques. His research also investigates terahertz communications , optical wireless networks , and ultra-massive MIMO for next-generation systems. He has contributed to 3 book chapters and over 100 conference/journal papers. IEEE Senior Member HEA Fellow Recipient of 1 patent Dr. Jimaa has supervised 30 MSc, 3 MPhil, and 4 PhD students . He actively participates in academic leadership as TPC Chair for IEEE conferences and previously served as Guest Editor for the International Journal of Communication Systems . Affiliated centers include the 6G Research Center and Center for Cyber-Physical Systems .

Mihai Sanduleanuمشاهده پروفایل

دانشیار

• RF Integrated Circuit Design
• Analog Mixed-Signal Integrated Circuit Design
• Wireless Communication Circuits
• +۷ مورد دیگر

Dr. Mihai Sanduleanu is an Associate Professor of Electrical Engineering at Khalifa University of Science and Technology. He has extensive industry experience from Philips Semiconductors, Philips Research Eindhoven, IMEC, and IBM T.J. Watson Research Center, combined with academic appointments including Adjunct Professor at Eindhoven University of Technology. His educational background includes: MSc from Gh. Asachi Technical University of Iasi, Romania MEE from Technical University Eindhoven, The Netherlands PhD from University of Twente, The Netherlands Dr. Sanduleanu's research focuses on cutting-edge integrated circuit design across the frequency spectrum from RF to THz. His work spans wireless transceiver design, analog/mixed-signal circuits, high-speed communication systems, and innovative applications in healthcare monitoring. He has pioneered developments in mm-wave imaging for skin cancer detection, ultra-low power radios, and high-performance analog-to-digital converters. His scholarly contributions include: 53 granted US patents Over 104 papers published in IEEE Journals and Conferences 9 books or book chapters Citation h-index of 22 and i10-index of 46 Dr. Sanduleanu has received significant recognition including multiple Philips and IBM Research Awards. He serves on the Editorial Board of the Analog Integrated Circuits and Signal Processing Journal and has previously been Associate Editor for IEEE Transactions on Circuits and Systems. He has successfully mentored 21 MSc students and 7 PhD students to graduation. Currently, he advises PhD student Ahmed Mahdy and MSc student Aaron Zerai Tekleab. His research is supported through affiliations with the Center for Cyber-Physical Systems, with current projects focused on vital signs monitoring using 160GHz radar and non-invasive glucose detection using 120GHz sub-mm wave technology.

Sherif Moussaمشاهده پروفایل

استاد

• Wireless Communication
• Computer Networks
• Machine Learning
• +۱ مورد دیگر

Dr. Sherif Moussa is a Professor and Dean at the Faculty of Engineering, Applied Science and Technology, Canadian University Dubai. He holds a PhD in Electrical and Computer Engineering from the University of Quebec and an MSc from the University of Waterloo, both in Canada. Before joining CUD in 2007, he served as a lecturer at Centennial College in Toronto. His research focuses on: Wireless Communication Computer Networks Machine Learning Digital Circuit Design His recent publications explore machine learning applications in cybersecurity, MIMO-OFDM systems, FPGA implementations, and routing protocols, reflecting a consistent emphasis on optimizing wireless and network technologies. Trends show increasing work in AI-driven solutions and intrusion detection since 2018. He received the 2015 CUD Research Excellence Award and founded the university's first robotics club. He actively contributes as a reviewer and technical committee member for international conferences.

Khalid Al Aliمشاهده پروفایل

دانشیار

• Hydrogen Production
• Solar Fuel Production
• Thermochemical Energy Storage
• +۶ مورد دیگر

Dr. Khalid Al Ali is an Associate Professor in the Department of Chemical Engineering at Khalifa University, focusing on solar fuel production and thermochemical energy storage. His research spans hydrogen generation, CO2 utilization, and solar reactor design. Education: PhD in Chemical Engineering (Tokyo Institute of Technology, 2014) MSc in Chemical Engineering (Tokyo Institute of Technology, 2011) BSc in Mechanical Engineering (United Arab Emirates University, 2006) Research Interests: High-temperature solar chemistry for hydrogen production Development of solar-driven thermochemical/photochemical processes Micro-kinetics modeling and catalysis Conversion of industrial waste into sustainable materials Key Projects: His work includes solar H2S decomposition for hydrogen production, blue hydrogen generation using sand-derived catalysts, and CO2 conversion systems. Scientific Roles: UAE Coordinator for Solar Chemistry at SolarPACES (2018–present) Director of Operations at Seramic Materials Ltd. (startup from Khalifa University) Teaching: Courses include Reaction Engineering, Kinetics of Materials, and Numerical Methods.

Srinivasakannan Chandrasekarمشاهده پروفایل

استاد

• Gas Processing
• Adsorption
• Catalysis
• +۹ مورد دیگر

Srinivasakannan Chandrasekar is a Professor in the Department of Chemical & Petroleum Engineering at Khalifa University's College of Engineering, with over 30 years of experience spanning academia, research, and the petrochemical industry. He has held faculty positions at University Science Malaysia, Curtin University, Monash University, and joined Khalifa University (formerly Petroleum Institute) in 2009, advancing to full professor by 2014. Education: PhD in Chemical Engineering, Indian Institute of Technology, Chennai B.E. in Chemical Engineering, Annamalai University Research Interests: Gas processing, catalysis, adsorption technologies, mineral processing, gasification, pyrolysis, combustion systems, microwave applications in chemical processes, and environmental solutions for solid waste, wastewater, and air pollution. His work emphasizes process modeling and simulation for industrial and energy applications. Scientific Recognition: Recognized among the top 0.05% globally in ScholarGPS's 'Highly Ranked Scholars - Lifetime' category. Teaching: Courses include Chemical Engineering Design Projects, Process Safety, Combustion, Heat Transfer, Mass Transfer, and Petroleum Refining. He supervises graduate students, including PhD candidates Adeel Iftikhar Ahmad and Asma Al Blooshi. Collaborations: Holds an honorary professor position at Kunming University of Science and Technology, China, and contributes to the Center for Catalysis and Separation Research.

Aamna AlShehhiمشاهده پروفایل

استادیار

• Artificial Intelligence
• Machine Learning
• Big Data Analytics
• +۷ مورد دیگر

Dr. Aamna AlShehhi serves as an Assistant Professor in the Department of Biomedical Engineering and Biotechnology at Khalifa University, where she has pioneered AI-driven healthcare solutions since joining in 2020. Her interdisciplinary expertise bridges electrical engineering, computer science, and clinical medicine through innovative research collaborations with MIT, Imperial College London, and Novartis. Her educational foundation includes: Bachelor's in Software Engineering, United Arab Emirates University (2009) Master's in Computing and Information Science, Masdar Institute (MIT collaboration) (2013) PhD in Interdisciplinary Engineering, Masdar Institute (MIT collaboration) (2017) Dr. AlShehhi's research centers on artificial intelligence for healthcare transformation , with emphasis on neurodegenerative disease prediction, rare disease diagnostics, and wearable-based gait analysis. She develops constrained deep learning models for Alzheimer's biomarker discovery, self-supervised frameworks for emotion recognition using smartphone data, and physics-informed neural networks for biomechanical analysis. Her work integrates multimodal data including fMRI, genomic sequences, and real-world behavioral metrics to address critical gaps in dementia screening, cancer detection, and mental health monitoring. Analysis of her 2023-2025 publications reveals three dominant trends: (1) Explainable AI architectures for clinical decision support, particularly constrained graph neural networks analyzing comorbidity networks in Alzheimer's; (2) Multimodal sensor fusion systems combining wearables, keystroke dynamics, and fMRI for neurological assessment; (3) Self-supervised learning approaches enabling robust performance with limited medical data. Her work consistently targets real-world clinical deployment through portable systems like smart gait analyzers and remote depression screening tools. Dr. AlShehhi actively mentors the next generation of biomedical engineers: Ferial J. Abuhantash (Ph.D. candidate) Khalid Ahmed Abdulla (Master's student) Her research is supported through strategic partnerships with Novartis Institute for Biomedical Research and collaborative grants enabling AI-driven drug repurposing for dementia and genomic cancer detection. She leads projects analyzing skin lesions for melanoma screening and developing deep learning models for early-stage cancer detection using genomic data. As a core member of Khalifa University's Healthcare Engineering Innovation Group , she directs a multidisciplinary team including Postdoctoral Fellow Dr. Sherlyn Jemimah and Research Assistant Chahd Maher Musthafa Chabib. Current initiatives focus on creating deployable AI systems for clinical settings, with ongoing work on portable gait assessment tools for rehabilitation centers and real-time emotion recognition platforms for mental health monitoring.

Ibrahim M. Elfadelمشاهده پروفایل

استاد

• Cyber Physical Systems
• Secure Cloud and Edge Computing
• Embedded Intelligence
• +۷ مورد دیگر

Prof. Ibrahim M. Elfadel is a Professor in the Department of Computer and Information Engineering at Khalifa University, Abu Dhabi, UAE, where he has held academic positions since 2011 (previously at Masdar Institute, now integrated into Khalifa University). He concurrently serves as founder and CEO of Laboos Technologies, a UAE medical wearables startup, and has held significant leadership roles including founding co-director of the Abu Dhabi SRC Center of Excellence on Energy-Efficient Electronic Systems (2013-2018) and Program Manager of Mubadala's TwinLab MEMS (2014-2019). His educational background includes: Ph.D. from Massachusetts Institute of Technology (USA), 1993 M.Sc. from Massachusetts Institute of Technology (USA), 1986 Dr. Elfadel's research spans Cyber Physical Systems, Secure Cloud and Edge Computing, Embedded Intelligence, and Computer-Aided Design applications in VLSI, MEMS, and Photonics. His work integrates biomedical sensing, embedded signal processing, and secure reconfigurable computing, with active projects in Secure Low-Power IoT Communication, Machine Learning Methods in VLSI CAD, 3D Integrated Circuits, and MEMS-based energy harvesting systems. His research demonstrates strong industry-academia collaboration through Mubadala partnerships. His scientific recognition includes: Six IBM Invention Achievement Awards IBM Outstanding Technical Achievement Award IBM Research Division Award D. O. Pederson Best Paper Award (IEEE, 2014) Semiconductor Research Corporation Board Award (2018) IFIP Service Award (2022) Dr. Elfadel mentors six graduate students comprising PhD candidates Ismail Shittu, Toheeb Salahudeen (co-advised), and Waleed Rather (co-advised), along with MSc students Omar Alketbi, Abdulla Alsuwaidi, and Esrat Khan. His sponsored research portfolio, secured through entities like Mubadala and SRC, covers the full spectrum of cyber physical systems development from concept to working prototypes. He directs the Advanced Digital Systems Laboratory and maintains strong affiliations with the Center for Cyber-Physical Systems Research, having previously founded multiple research centers including ACE4S, TwinLab 3DSC, and iMicro (Masdar Institute Center for Microsystems).

Mohammad Abu Haijaمشاهده پروفایل

دانشیار

• Catalysis
• Nanomaterials
• Water Treatment
• +۵ مورد دیگر

Dr. Mohammad Abu Haija serves as Associate Professor in the Department of Chemistry at Khalifa University, United Arab Emirates, and holds the position of Deputy Director at the Advanced Materials Chemistry Center (AMCC). Previously, he was Assistant Professor at King Khalid University (Saudi Arabia) and a postdoctoral fellow at Argonne National Laboratory (USA). His academic credentials include: PhD in Chemistry, Technical University of Berlin (Germany), 2006 MSc in Chemistry, Yarmouk University (Jordan), 1997 BSc in Chemistry, Yarmouk University (Jordan), 1995 Dr. Abu Haija's research centers on functional nanomaterials for environmental and energy applications, with emphasis on catalysis , surface engineering , and material-property relationships . His work bridges fundamental surface science with practical solutions for water treatment and sustainable energy systems. Nanomaterial design for catalytic advanced oxidation processes (AOPs) CO2 adsorption/conversion using functionalized nanosilica and MOFs Electrochemical valorization of biomass derivatives Photocatalytic degradation of persistent pollutants His recent publications (2020-2023) reveal a consistent focus on developing nanocomposite solutions for critical environmental challenges. Key themes include visible-light photocatalysis for pharmaceutical removal, engineered adsorbents for carbon capture, and integrated electrocatalytic systems for simultaneous CO2 reduction and biomass upgrading—demonstrating a strategic shift toward circular economy applications. Recognition for his contributions includes: Commendation for Research (2018) Faculty Research Excellence Award (2019) Faculty Research Excellence Award (2022) As an academic leader, he mentors 5 PhD candidates and 15 MSc students while directing research projects spanning water treatment nanotechnology, CO2 management, and biomass conversion. His team operates within Khalifa University's Center for Catalysis and Separation Research and the Advanced Materials Chemistry Center. Current initiatives focus on scaling laboratory innovations for industrial water treatment systems and developing dual-functional electrocatalytic platforms that simultaneously address carbon emissions and renewable fuel production.

Mohammad Namiمشاهده پروفایل

دانشیار

• Cognitive Neuroscience
• Clinical Neuropsychology
• Sleep Neuroscience
• +۳ مورد دیگر

Dr. Mohammad Nami serves as Associate Professor of Cognitive Neuroscience and Clinical Neuropsychology at the School of Health Sciences and Psychology, Canadian University Dubai. He concurrently directs the Brain, Cognition, and Behavior Unit at BrainHub UAE and maintains associate membership in the Harvard Medical School Alumni network. Previously, he held leadership roles as Head of Neuroscience Department and Vice Chancellor for Research at Shiraz University of Medical Sciences. His academic credentials include: PhD in Cognitive Neuroscience from Institute for Cognitive Science Studies Dr. Nami's research centers on the interdependence of mental health and sleep health, with primary expertise in cognitive neuroscience, clinical neuropsychology, and sleep disorder interventions. He advocates that cognitive and affective potential can only be fully realized through integrated sleep-mental health approaches, emphasizing neuro-cognitive fitness and neurological aspects of sleep pathologies. His work bridges clinical practice with neuroscience to develop practical interventions for cognitive optimization. Analysis of his 2023-2025 publications reveals three dominant research trajectories: (1) Sleep-neuroscience interfaces using quantitative EEG for insomnia and sleep disorder diagnostics, (2) Cognitive performance assessment in safety-critical occupations like aviation and industrial control rooms, and (3) Neurocognitive rehabilitation techniques for stroke, cerebral palsy, and neurodegenerative conditions. His methodology frequently combines clinical trials with advanced neuroimaging and computational modeling. As an associate member of Harvard Medical School Alumni and Harvard Alumni Entrepreneurs, Dr. Nami contributes to academic-industry knowledge translation. The provided text does not reference specific scientific awards. With 173 peer-reviewed publications (H-index 27, i10-index 77 as of August 2025), his research program demonstrates significant scholarly impact. While student mentorship details are absent, his leadership of the Brain, Cognition, and Behavior Unit suggests active supervision of research personnel. His publication record indicates consistent grant funding, particularly for sleep-neuroscience and occupational safety projects. The Brain, Cognition, and Behavior Unit at BrainHub UAE functions as his primary research hub, conducting studies on sleep-cognition interactions, neurocognitive fitness metrics, and real-world applications of neuroscience findings. Current initiatives appear focused on digital health tools for stress management and neurophysiological monitoring in occupational settings.

Ameena Alsumaitiمشاهده پروفایل

دانشیار

• Renewable Energy
• Energy Policy and Economics
• Energy and Demand Side Management
• +۱۲ مورد دیگر

Dr. Ameena Alsumaiti is an Associate Professor in Electrical Engineering at Khalifa University, specializing in renewable energy, smart cities, and risk-reliability analysis. She earned her Ph.D. and M.A.Sc. in Electrical and Computer Engineering (Power and Energy) from the University of Waterloo (Canada) in 2015 and 2010, respectively, and a B.Sc. in Electrical Engineering (Communication Track) from United Arab Emirates University in 2008. Education: Ph.D., Electrical and Computer Engineering, Power and Energy, University of Waterloo (2015) M.A.Sc., Electrical and Computer Engineering, Power and Energy, University of Waterloo (2010) B.Sc., Electrical Engineering, Communication Track, United Arab Emirates University (2008) Her research focuses on Renewable Energy, Energy Policy, Demand Side Management, Smart Cities, Autonomous Driving, and Cyber-Physical Systems, addressing the Water-Electricity-Gas-Transport Nexus. She leads the Smart OR Lab and is affiliated with the Advanced Power and Energy Center. Dr. Alsumaiti teaches Engineering Mathematics (MATH232) and Risk, Reliability, and Uncertainty in Engineering Systems (ECCE622). Scientific Awards and Honors: University of Waterloo Graduate Scholarship Award UW Faculty of Engineering Graduate Scholarship Award Provost Doctoral Entrance Award for Women UW/NSERC Graduate Scholarship Award Masdar Scholarship Award Her Highness Sheikha Fatima Bint Mubarak Award United Arab Emirates University Award UAEU Honor Student Program Award Creativity Club Award Al-Maktoum Institute Award Abu Dhabi Education Council Award Photography Competition Award She has supervised multiple Ph.D. and Master’s students, including Mohamed Elsir, Abdulrahman Hamdy, Ahmed Alzubaidi, and Alya Alhaj Alhindi, and collaborated with post-doctoral fellows and researchers like Motiur Rezza, Nguyen The Hoach, and Mrityunjay Kumar Mishra.

David Francis Daltonمشاهده پروفایل

مدرس ارشد

• English for Academic Purposes
• Applied Linguistics
• Intercultural Communication
• +۵ مورد دیگر

David Francis Dalton is a Senior Lecturer in the General Education Unit at Khalifa University of Science and Technology, Abu Dhabi, UAE, where he has taught English for Academic Purposes and Intercultural Communication since 2018 following the merger of the Petroleum Institute with KU. With over two decades of international teaching experience across Scotland, England, Spain, Mexico, and the UAE, he specializes in curriculum design for multilingual engineering contexts and academic communication development. His educational background includes: MA in Applied Linguistics, University of Sheffield Postgraduate Diploma in Education, University of Sheffield Licentiate Diploma in TESOL, Trinity College London Diploma in Youth and Community Work, Manchester University B.Soc.Sc. Joint Honors, Birmingham University Certificate in TESOL, Sheffield Hallam University Dalton's research centers on English for Academic Purposes within engineering education, with emphasis on critical reading strategies, academic integrity, and intercultural communication. His work explores how Arab engineering students develop academic literacy in English-medium environments and investigates plagiarism perceptions through cultural lenses. Current research focuses on Flipped Learning methodologies and compliance frameworks in higher education. His publication portfolio reveals consistent contributions to engineering education communication, particularly in cross-cultural academic writing, critical reading pedagogy, and team-based learning approaches. Key trends include adapting communication curricula for multilingual engineering students, developing plagiarism prevention strategies sensitive to cultural contexts, and creating engagement frameworks for technical communication courses. Dalton has played pivotal roles in establishing institutional resources including the Petroleum Institute Writing Centre and Project-X for student engagement. His teaching methodology emphasizes learner-centered classrooms with extensive use of problem-based learning in Freshman Communications and Engineering Design courses. He has delivered teacher training across multiple institutions including Sheffield University, University of Valencia, and British University in Dubai.

Jorge Diasمشاهده پروفایل

استاد

• Robotics
• Artificial Intelligence
• Artificial Perception
• +۴ مورد دیگر

Jorge Dias is a Full Professor at Khalifa University (Abu Dhabi, UAE) specializing in Robotics and Artificial Intelligence, with a focus on Artificial Perception. He coordinates the Khalifa University Center of Autonomous Robotic Systems (KUCARS) and has contributed to robotics advancements since 1984. Habilitation/Doctor of Science (2011) & PhD (1994) in Electrical Engineering from University of Coimbra, Portugal His research spans Robotics for Sustainability , Computer Vision , and Social Robots , with over 300 publications. Recent work emphasizes autonomous navigation, underwater robotics, and neuromorphic computing. He has led international projects like the ECOBOTICS.sea RISE Marie Curie initiative and coordinated European consortia for elderly-inclusive robotics ("Social Robot", "GrowMeUP"). Current teaching includes courses in Algorithmic Robotics , Autonomous Systems , and Robotic Perception .