جست‌وجوی استاد و پژوهشگر

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.

Andreas Benderمشاهده پروفایل

استاد

• Drug Discovery
• Artificial Intelligence
• Cheminformatics
• +۷ مورد دیگر

Prof. Andreas Bender is a Professor for Machine Learning in Medicine at the Department of Medicine, Khalifa University, Abu Dhabi. He focuses on integrating heterogeneous chemical, biological, and medical data for clinically relevant decision-making. PhD, University of Cambridge Diplom-Chemiker, University of Frankfurt His research interests include Drug Discovery , Artificial Intelligence , Cheminformatics , and Computational Biology , particularly in the context of life science data analysis and AI/ML applications. He has been involved in founding biotech companies such as Healx Ltd., PharmEnable Ltd., and Pangea Bio. His work bridges academic research and translational drug discovery, with a focus on in silico methods and solubilizing difficult-to-drug targets.

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 .

Omar Alhusseinمشاهده پروفایل

استادیار

• Network Automation and Intelligence
• Network Resource Management and Optimization
• AI and Networking
• +۲ مورد دیگر

Dr. Omar Alhussein serves as an Assistant Professor in the Department of Computer Science at Khalifa University. Previously, he worked as a Senior Research Engineer at Huawei Technologies Canada (2020-2023), where he developed machine-learning solutions for networks and filed six patent applications. His educational qualifications include: Ph.D. in Electrical and Computer Engineering, University of Waterloo (2020) M.A.Sc. in Engineering Science, Simon Fraser University (2015) B.Sc. in Electrical and Computer Engineering, Khalifa University (2013) Research focuses on the convergence of networks and artificial intelligence: Network Automation and Intelligence Network Resource Management and Optimization AI and Networking NFV/SDN Wireless Networks He employs interdisciplinary methods to advance network intelligence through fundamental research principles. Scientific recognition includes: Outstanding Individual Award (Huawei Technologies) Quality Research Award (Huawei Technologies) Dr. Alhussein mentors PhD candidates and holds six patent applications for probabilistic/distributed AI in next-generation networks and AI trustworthiness. He actively recruits PhD students for ongoing research. He maintains active affiliations with Khalifa University's 6G Research Center and Center for Cyber-Physical Systems.

Muhammad Muzammal Naseerمشاهده پروفایل

استادیار

• Artificial Intelligence
• Machine Learning
• Computer Vision
• +۵ مورد دیگر

Dr. Muhammad Muzammal Naseer serves as an Assistant Professor in the Computer Science department at Khalifa University's College of Computing and Mathematical Sciences. Previously, he held research positions at Data61 (CSIRO), Inception Institute of Artificial Intelligence, and Mohamed Bin Zayed University of Artificial Intelligence (MBZUAI) from 2018 to 2024. His academic background includes: Ph.D. in Engineering & Computer Science, Australian National University (ANU), 2022 M.Sc. in Electrical Engineering, King Fahd University of Petroleum & Minerals (KFUPM) B.Sc. in Electrical Engineering, University of the Punjab (PU) His research specializes in robust intelligent systems through adversarial machine learning for AI behavior explanation, self-learning methodologies (self-supervision, self-distillation), and multimodal large language models. Key application domains include healthcare security and image/video understanding, with publications in top venues like CVPR, NeurIPS, and TPAMI. Dr. Naseer teaches Artificial Intelligence (COSC604), Introduction to Machine Learning (COSC434), and Machine Vision and Image Understanding (COSC606). He is affiliated with the Center for Cyber-Physical Systems Research and actively recruits Ph.D. students for his research group focusing on AI robustness and security.

Maria Lourdes Vega Fernandezمشاهده پروفایل

استاد

• Molecular Thermodynamics
• Clean Energy
• Decarbonization (CCUS)
• +۷ مورد دیگر

Prof. Maria Lourdes Vega Fernandez is a globally recognized Professor of Chemical Engineering at Khalifa University of Science and Technology, where she serves as the Joint Chair Professor of the Gas Research Center. She founded and directs the Research and Innovation Center on CO2 and Hydrogen (RICH Center) in Abu Dhabi, UAE. PhD in Physics (University of Seville, 1992) Postdoctoral Associate at Cornell University (1992-1995) Her research bridges fundamental science and industrial applications in clean energy, focusing on CO2 capture/utilization , hydrogen technologies , and sustainable cooling systems . She leverages computational modeling and AI for designing 2D/3D materials for energy applications. Prof. Vega has received multiple prestigious awards for her contributions to chemical engineering and environmental science, including the Mohammed Bin Rashid Medal and AIChE Fellowship. She leads advisory boards in the UAE and UK, and contributes to strategic energy initiatives globally.

Mohammad Alsharidمشاهده پروفایل

استادیار

• Biomedical Image Analysis
• Computer Vision
• Natural Language Processing
• +۶ مورد دیگر

Dr. Mohammad Alsharid is an Assistant Professor in Computer Science at Khalifa University, specializing in biomedical image analysis, computer vision, and machine learning. He holds a DPhil in Engineering Science from the University of Oxford (2022) and a BSc in Computer Engineering with highest honors from Khalifa University. Education DPhil (Oxon) in Engineering Science, University of Oxford, UK BSc in Computer Engineering, Khalifa University, UAE Research Interests Biomedical Image Analysis Natural Language Processing Computer Vision Machine Learning Healthcare AI Ultrasound Analysis Scientific Awards Best Presentation Award at ASMUS workshop of MICCAI

Rashid Abu Al Rubمشاهده پروفایل

استاد

• Mechanical Engineering
• Materials Science
• Computational Mechanics
• +۵ مورد دیگر

Professor Rashid Abu Al Rub is a distinguished academic and researcher currently serving as the Director of the Advanced Digital & Additive Manufacturing (ADAM) Center and Professor of Mechanical & Nuclear Engineering at Khalifa University of Science and Technology. He has held leadership roles, including Acting Chair of Aerospace Engineering and Associate Department Chair of Mechanical Engineering at Khalifa University, and Department Head of Mechanical and Materials Engineering at Masdar Institute of Science and Technology. With prior appointments at Texas A&M University, Louisiana State University, and Catholic University of America, he brings extensive experience in multi-scale computational mechanics and material modeling. PhD in Mechanical Engineering from Louisiana State University (2004) MSc in Mechanical Engineering from Jordan University of Science and Technology (2001) BSc in Mechanical Engineering from Jordan University of Science and Technology (1999) His research focuses on developing constitutive models and computational tools for advanced materials, particularly leveraging additive manufacturing and 3D printing in aerospace, defense, and automotive industries. He is a pioneer in damage and fracture mechanics, multifunctional materials, and nano/micro-structured composites. Professor Abu Al Rub has received numerous accolades, including the Student-Led Teaching Excellence Award (2009, 2011), Truman R. Jones Graduate Teaching Award (2010), and the Ferdinand P. Beer Outstanding Educator Award (2011). He has secured over $27 million in research funding and holds 6 patents, including a book on Non-Local Damage and Plasticity. Member of American Institute of Aeronautics and Astronautics (AIAA) Member of American Society of Mechanical Engineers (ASME) Member of American Society for Engineering Education (ASEE)

Tamer Mohamed Abdellatif Mohamedمشاهده پروفایل

استادیار

• Applied Artificial Intelligence (AI)
• Machine Learning
• Information Retrieval (IR)
• +۲ مورد دیگر

Dr. Tamer Mohamed Abdellatif Mohamed is an Assistant Professor and Program Coordinator at the Canadian University Dubai , affiliated with the School of Engineering, Applied Science and Technology and the Department of Computer and Networking Engineering Technology . He holds a PhD in Electrical and Computer Engineering from the University of Western Ontario, Canada, and a professional certificate in STEM teaching at the university level from the same institution. Education : PhD in Electrical and Computer Engineering (University of Western Ontario, Canada); STEM Teaching Certificate (University of Western Ontario). His research expertise spans applied artificial intelligence (AI) , machine learning , information retrieval (IR) , software analytics , and mining software repositories . With over 20 years of industry experience at multinational corporations like Hewlett-Packard Enterprise, he contributes practical insights as an experienced Project Manager and Software Practitioner. Dr. Mohamed has published extensively in top-tier journals and conferences. Prior leadership roles include Vice President of Professional Development at PMI, London Chapter and Treasurer at IEEE Young Professional, London Chapter . He is based at the university's Hub G,10 location, with contact via tamer.mohamed@cud.ac.ae or +971(04)7096822.

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.

Randa Asadمشاهده پروفایل

دانشیار

• Astrophysics
• Galaxy Evolution
• Chemical Enrichment
• +۳ مورد دیگر

Dr. Randa Asad serves as Associate Professor in the Department of Physics at the College of Arts and Sciences, American University of Sharjah (AUS) since 2021, specializing in astrophysical research on galaxy evolution through star cluster analysis. Her work integrates observational astronomy with advanced computational techniques to decode chemical enrichment histories across cosmic time. Education background: PhD in Physics, University of Cincinnati, United States (2012) MS in Physics, University of Cincinnati, United States (2008) BS in Physics, Jordan University of Science and Technology, Jordan (2005) Her research program centers on spectroscopic analysis of star clusters to reconstruct galactic chemical evolution, employing full-spectrum fitting methodologies and machine learning algorithms. She has developed the ASAD (Analyzer of Spectra for Age Determination) framework and secured observing time at premier facilities including VLT, Gemini, and SOAR telescopes. International collaborations include visiting researcher appointments at Harvard-Smithsonian Center for Astrophysics, Space Telescope Science Institute, and ESO headquarters. Publication trends reveal sustained focus on stellar population analysis since 2014, with recent works (2022-2024) emphasizing machine learning applications for abundance measurements in clusters like NGC 1856. Earlier research established foundational methodologies for age determination through integrated light spectroscopy, consistently targeting the Large Magellanic Cloud as a key laboratory for galaxy evolution studies. Scientific recognition: CAS Excellence in Research Award, AUS (April 2022) Dr. Asad has secured significant observational resources at major telescopes worldwide while maintaining active membership in the International Astronomical Union (since 2016). Her research group conducts observational campaigns to unravel stellar population complexities through spectral analysis, contributing to international efforts in galactic archaeology. The Star Clusters Research Group she leads bridges theoretical modeling with empirical data to decode star formation histories across diverse galactic environments.

Yousof Alhammadiمشاهده پروفایل

دانشیار

• Information Security
• Intrusion Detection
• Botnet Detection
• +۶ مورد دیگر

Dr. Yousof Alhammadi is an Associate Professor at Khalifa University of Science and Technology, affiliated with the Department of Electrical and Computer Engineering. His research focuses on Information and Network Security, with expertise in intrusion detection, botnet/virus detection, RFID security, blockchain, and mobile security. He also teaches courses in Linear Algebra, C++ Programming, and Network/Computer Security. Education: Ph.D. in Computer Science (University of Nottingham, UK, 2009) M.Sc. in Telecommunications Engineering (University of Melbourne, Australia, 2003) B.Eng. in Computer Engineering (Etisalat College of Engineering, UAE, 2000) His research team includes Post-Doctoral Fellows Dr. Khouloud Eledlebi (Cyber Physical Systems) and Dr. Lamees Mahmoud AlQassem (Electrical and Computer Engineering), along with graduate student Al Anoud Almemari.

Nejib Ben Hadj-Alouaneمشاهده پروفایل

استاد

• Software Engineering
• Cybersecurity
• Web Services
• +۶ مورد دیگر

Dr. Nejib Ben Hadj-Alouane is a Professor of Computer Engineering and Program Director for the Master of Science in Artificial Intelligence at AUD's School of Engineering. He previously held professorial roles at Tunisia's National Engineering School of Tunis (ENIT) and National School of Computer Sciences (ENSI), where he contributed to program modernization and PhD/Master’s program development. His industry experience includes R&D roles at Dow Chemical Corporation and software development for traffic simulation systems. He is an entrepreneur, co-founding a software startup focused on human resource management for mining operations. Education: Ph.D. in Computer Engineering, University of Michigan, Ann Arbor, USA MSE in Computer Engineering, University of Michigan, Ann Arbor, USA BSE in Computer Engineering, Syracuse University, USA Research Focus: Dr. Alouane's work spans cybersecurity concepts like non-interference and opacity, optimization of software and cloud/fog infrastructure (e.g., genetic algorithms for game server placement), and machine learning applications in smart agriculture. He emphasizes water conservation through adaptive irrigation systems and has authored over 90 peer-reviewed publications. Advising & Entrepreneurship: Mentor to over 20 PhD/Master’s graduates and founding member of a Canadian mining HR software startup. His entrepreneurial efforts include architectural leadership for industrial ERP integration in Tunisia.

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.

Arafat Aldweikمشاهده پروفایل

استاد

• Wireless Communications
• Intelligent Transportation Systems
• Internet of Things
• +۵ مورد دیگر

Dr. Arafat Aldweik is a Professor in the Department of Computer and Information Engineering at Khalifa University in the United Arab Emirates. He also holds the title of Research Professor at Western University and the University of Guelph in Canada, and is a Visiting Research Fellow at Newcastle University in the UK since 2006. M.S. in Electrical Engineering from Cleveland State University (Summa Cum Laude, 1998) Ph.D. in Electrical Engineering from Cleveland State University (Magna Cum Laude, 2001) Dr. Aldweik’s research focuses on Wireless Communications , Digital Communications , Internet of Things (IoT) , Error Correction Coding , UAV Communications , and Physical Layer Security , with a strong emphasis on 6G networks and physical unclonable functions (PUFs). He has raised over $3.6M in research funding and published more than 170 articles, with notable projects including Hybrid High-Density WSNs , Cloud-Based Micro-Stations for Green ITS , and PHY Layer Security for UAV Networks . Scientific Awards & Honors Leader-Founder Award, UAE (2019) Best Academic Research Award, Dubai Sustainable Transportation (2017) Fulbright Scholarship (1996) Hijjawi Award for Applied Sciences, Jordan (2004) Best Paper Awards at major conferences Senior Member, IEEE Dr. Aldweik’s editorial roles include Editor for IEEE Transactions on Vehicular Technology and IET Communications. He is also a Registered Professional Engineer in Ontario, Canada, and co-founder of two startups with eight US patents.