جست‌وجوی استاد و پژوهشگر

Pradip Sharmaمشاهده پروفایل

دانشیار

• Cybersecurity
• Artificial Intelligence
• Blockchain
• +۵ مورد دیگر

Dr. Pradip Sharma is an Associate Professor of Cybersecurity & AI at the University of Aberdeen, UK, within the School of Natural and Computing Sciences, Department of Computing Science. He is a globally recognized academic and researcher with expertise in Cybersecurity, Artificial Intelligence, Blockchain, and Edge Computing. His research interests span multiple domains including Cybersecurity, Blockchain, Edge Computing, Software-defined Networking, and IoT Security. Dr. Sharma's work focuses on developing innovative solutions for security challenges in emerging technologies, with particular emphasis on privacy-aware AI systems, secure data sharing frameworks, and intelligent network security mechanisms. His interdisciplinary approach bridges theoretical foundations with practical implementations across healthcare, smart mobility, and consumer electronics domains. Senior Fellowship Advance HE (SFHEA) IEEE Senior Member (SMIEEE) Dr. Sharma actively supervises doctoral researchers and is accepting new PhD students in Computing Science. His funded research portfolio exceeds £1M from sources including EPSRC, Innovate UK, and international agencies. Current projects include 'Secure, Privacy-aware, and Trusted Data Share in Smart Mobility' (EPSRC, £200K), 'ZECURE Data Exchange Platform' (Innovate UK, £236K), and 'Quantum-resistant Cybersecurity' (Royal Embassy of Saudi Arabia, £73K). He also serves as an editor for leading journals and is a regular keynote speaker at international conferences.

Md Noor-A-Rahimمشاهده پروفایل

استادیار

• Intelligent Transportation Systems
• Machine Learning
• Internet of Things
• +۴ مورد دیگر

Dr. Md Noor-A-Rahim is an Assistant Professor (Lecturer-Above the Bar) at the School of Computer Science and Information Technology, University College Cork (Ireland). He previously served as a Senior Researcher and Marie Curie Fellow at the same institution. His academic journey includes a PhD from the University of South Australia (2015) and the prestigious Michael Miller Medal for his outstanding thesis on wireless communication systems. His research focuses on Intelligent Transportation Systems, Machine Learning, IoT, Wireless Networks, and DNA-based data storage. He has published extensively on topics like 6G-V2X systems, time-sensitive networking, and error characterization in DNA storage. His work integrates cutting-edge technologies such as intelligent reflecting surfaces (IRS), federated learning, and ultra-reliable low-latency communication (URLLC). Research Interests : Dr. Rahim's research bridges theoretical advancements and real-world applications in vehicular networks, smart manufacturing, and next-generation communication systems. He explores challenges in autonomous driving, edge computing, and bio-constrained data storage. His contributions include novel coding schemes for anytime transmission and frameworks for mitigating big vehicle shadowing in V2X communications. Key Publications : His recent work includes a comprehensive survey on wireless TSN (2025), analysis of 6G-V2X systems (2022), and breakthrough studies on DNA data storage error modeling (2023). These publications highlight his expertise in both foundational research and industry-relevant solutions. Awards : Recipient of the Michael Miller Medal (2015) for doctoral research excellence. Grants & Labs : While specific grants are not listed in the text, his research portfolio suggests involvement in collaborative projects with industry partners and funding bodies. He leads interdisciplinary efforts in smart manufacturing and vehicular communication systems.

• Architectures for fault-tolerant quantum computing
• Topological error correcting codes
• Magic states
• +۵ مورد دیگر

Professor Earl T. Campbell is a Professor of Quantum Computation at the School of Mathematical and Physical Sciences, University of Sheffield, and serves as VP of Quantum Science at Riverlane. His research focuses on practical quantum technologies with capabilities beyond classical physics, particularly in fault-tolerant quantum computing. His educational background includes: Physics & Philosophy MSc (2001-2005, Bristol University) Quantum computing PhD (2005-2008, Oxford University) Professor Campbell's research centers on the central question 'What are the optimal blue-prints for large-scale, reliable quantum technologies?' His work spans architectures for fault-tolerant quantum computing, topological error correcting codes, magic states, gate synthesis, and Majorana fermions. His team designs protocols and software to operate future quantum computers reliably despite noise and decoherence, including development of error correction codes, magic state factories (which determine quantum computer processing speed), and algorithm compilation into machine-level commands. His recent publications demonstrate a strong focus on practical aspects of quantum error correction, with significant contributions to surface codes, homological product codes, and efficient decoding algorithms. His work bridges theoretical quantum information science with practical implementation challenges, aiming to reduce resource requirements for fault-tolerant quantum computing. His notable scientific achievements include: Royal Commission of Great Exhibition of 1851 fellowship (2008-2010) EPSRC early career Research Fellow (2015-present) Professor Campbell supervises PhD student Luke Heyfron and collaborates with postdoc Mark Howard. He has received significant grant funding including an EPSRC early career fellow project 'Towards fault-tolerant quantum computing with minimal resources' (EP/M024261/1, £675,867) and Royal Commission fellowship funding (~£100,000). He is an active member of the EPSRC Peer Review College and the Institute of Physics QQQ group Committee, and has organized the FTQT2016 workshop in Benasque, Spain.

• Nanoplasmonics
• Nano-optics
• Biochips
• +۷ مورد دیگر

Li Yi is a Tenured Associate Professor at the School of Microelectronics, Southern University of Science and Technology (SUSTech) , with expertise in nanoplasmonics, nano-optics, and biochips. His career spans institutions including KU Leuven, Imperial College London, and Ludwig-Maximilians-Universität München. Education: Ph.D. (2015, KU Leuven & IMEC), M.S. (2010) and B.S. (2007) in Biomedical Engineering from Zhejiang University. Career: Associate Professor (2021–present) and Assistant Professor (2019–2020) at SUSTech; LMU Research Fellow (2018–2019); Research Associate (2015–2018) at Imperial College London. Research Interests focus on single-molecule biochips, DNA data storage, and nanopore sequencing. His work bridges nanotechnology with biomedical applications, including: Integrated circuit-compatible optical/electrical devices Computational lithography and nanoscale imaging Neural network training for biosensing Publications include >60 peer-reviewed articles with 25 H-index. His recent work emphasizes DNA-based data encryption, nanopore engineering, and portable biosensing systems. Key journals: Nature Communications, Nano Letters, ACS Nano. Scientific Awards : LMU Research Fellowship (Marie Curie COFUND) imec Excellent Scientific Award Shenzhen 'Peacock Plan' Category B Talent Outstanding Poster Award at Surface Plasmon Photonics 2017 Participation in Lindau Nobel Laureates Meeting (2019) Grants include Ministry of Science and Technology Key R&D Youth Program, NSFC General Program, and Guangdong Provincial Key Program. His lab develops: Fluidic nanopores for single-molecule sensing Optical antennas for enhanced detection Training programs in biochip design and nano-optics

Naveed Mahmudمشاهده پروفایل

استادیار

• Quantum Computing
• Hybrid Quantum-Classical Systems
• Machine Learning Applications in Quantum Contexts
• +۳ مورد دیگر

Naveed Mahmud is an Assistant Professor at the Department of Electrical Engineering and Computer Science, Florida Institute of Technology. He specializes in quantum computing, hybrid quantum-classical systems, and reconfigurable computing architectures. His research focuses on optimizing quantum algorithms, data encoding/decoding techniques, and secure communications using quantum technologies. Research interests include quantum-classical integration, algorithm emulation on high-performance reconfigurable computers, and applications of quantum computing in pattern recognition and cryptography. Key areas of exploration are hybrid quantum-classical machine learning, quantum wavelet transforms, and securing free-space optical communications with quantum key distribution. His recent work emphasizes scalability and efficiency in quantum computing frameworks, including frameworks like QASM-to-HLS for quantum circuit acceleration, and decoherence-optimized quantum circuits. Articles highlight advancements in quantum data decoding, algorithm emulation, and secure communication systems. No scientific awards or formal advisees are listed. His profile includes links to ORCID, Google Scholar, and ResearchGate for further details on publications and collaborations.

• Signal Processing
• Error Correction Coding
• Information Theory
• +۳ مورد دیگر

Professor Sarah Johnson is a distinguished academic in the School of Engineering at the University of Newcastle, specializing in Electrical and Computer Engineering. She holds a PhD in Electrical Engineering from the same institution and has been awarded prestigious fellowships including an ARC Future Fellowship. Her research applies engineering solutions to digital information processing and error correction coding, with significant applications in secure communications and biomedical technologies. Her research interests span: Signal processing for secure data transmission Error correction codes for reliable communication systems Biomedical applications of digital signal processing Quantum-enabled secure communications Internet of Things communication protocols Her publications primarily focus on information theory, wireless communication systems, and biomedical engineering. Recent work shows strong emphasis on index coding optimizations, quantum cryptography implementations, and biomedical signal processing techniques for neuroimaging applications. Significant awards include: NSW Premier's Prize for Excellence (2017) Pro Vice-Chancellor's Research Excellence Award (2007) Professor Johnson has secured multiple ARC Discovery grants and industry-sponsored projects, including collaborations with Quintessence Laboratories on quantum key distribution. She co-founded HunterWISE to promote women in STEM fields and has supervised numerous graduate students across engineering disciplines. She leads interdisciplinary collaborations with biomedical researchers on rehabilitation technologies and neuroimaging analysis, developing systems to monitor recovery processes and brain activity patterns.

Maria A. Martinمشاهده پروفایل

پژوهشگر

• Climate Change Modeling
• Glaciology
• Numerical Simulation
• +۳ مورد دیگر

Dr. Maria A. Martin has been affiliated with the Potsdam Institute for Climate Impact Research (PIK) since 2008, initially as a doctoral student and later transitioning to a post-doctoral researcher. Since 2014, she has served as a Research Analyst within the Scientific Directors' Staff department. Her academic background includes a physics degree from the University of Potsdam and Université Pierre-et-Marie-Curie in Paris, where her doctoral thesis focused on synchronization in quantum-optical resonators. At PIK, she co-developed the Parallel Ice Sheet Model and conducted pioneering research on Antarctic ice-flow dynamics using numerical modeling techniques. Dr. Martin's research interests span climate modeling, glaciology, and environmental science, with a particular emphasis on understanding the mechanisms driving ice-sheet dynamics and their implications for sea-level rise. Her work integrates advanced computational models with observational data to address critical questions in climate science. Beyond technical contributions, she has engaged in science communication through initiatives like the children's podcast Pinselohr . Her professional network and collaborations are reflected in her participation in interdisciplinary projects at PIK, including contributions to policy advice and software development related to climate impact research. She holds an ORCID identifier (0000-0002-1443-0891) and maintains active involvement in academic discourse through peer-reviewed publications and institutional outreach activities.

Edith Tretschkمشاهده پروفایل

پژوهشگر

• Computer Graphics
• Computer Vision
• Machine Learning
• +۵ مورد دیگر

Edith Tretschk is a Research Scientist at Meta Reality Labs Research in the San Francisco Bay Area. She completed her Ph.D. in Computer Science at Saarland University and Max Planck Institute for Informatics (2018-2023), advised by Christian Theobalt . Her work bridges computer graphics , computer vision , and machine learning , with a focus on 3D reconstruction and quantum computing applications. Education Ph.D. in Computer Science (2018-2023), Max Planck Institute for Informatics & Saarland University M.Sc. in Computer Science (2017-2023), Graduate School of Computer Science, Saarland University B.Sc. in Computer Science (2014-2017), Saarland University Research Focus Her research explores 3D reconstruction of dynamic scenes, neural rendering , and quantum computing for vision tasks. Recent work includes time-consistent scene flow (SceNeRFlow), quantum auto-encoders (3D-QAE), and physics-driven template matching (φ-SfT). Article Trends Her publications span 3D vision , quantum algorithms , and neural scene modeling . Key themes include non-rigid deformation, quantum-hybrid approaches, and physics-based reconstruction. Scientific Recognition Bachelor Award (2017) for top CS graduates Deutschlandstipendium scholarship (2015-2017) NeurIPS Top Reviewer (2022) Additional Contributions She has delivered invited talks at World Labs, Meta, Nvidia, and Epic Games. Active as a reviewer for CVPR, ECCV, ICCV, and NeurIPS, she has also contributed to open-source projects and datasets.

Abdul Khaliqمشاهده پروفایل

استاد

• Numerical Analysis
• Scientific Computing
• Financial Mathematics
• +۱۰ مورد دیگر

Dr. Abdul Khaliq is a Professor in the Department of Mathematical Sciences at Middle Tennessee State University (MTSU) . With a career spanning decades, he specializes in developing Numerical Methods for complex systems including Partial Differential Equations (PDEs) , Fractional PDEs , and Stochastic Differential Equations . His work bridges applied mathematics and computational science, focusing on applications in Financial Mathematics , Biochemical Systems , and Public Health Modeling . Ph.D. in Mathematics, Brunel University London (1983) M.Sc. in Numerical Analysis, Brunel University London (1981) M.Sc. in Mathematics, Quaid-i-Azam University (1977) Research Interests include: Numerical Analysis of large-scale systems Scientific Computing with deep learning integration Computational Finance for high-dimensional derivatives Fractional Calculus applications in epidemiology High-Performance Computing for financial and physical systems Article Trends reflect his interdisciplinary expertise in fractional PDEs , stochastic modeling , and machine learning algorithms for financial and epidemiological forecasting. Recent works focus on quantum neural networks for time-dependent systems and physics-informed encoder-decoder architectures for parameter learning. Scientific Awards : MTSU Distinguished Research Award (2015-2016, 2007-2008) Excellence in Professional Service, College of Basic and Applied Sciences (2010-2011, 2006-2007) Faculty Excellence in Research, Western Illinois University (2001-2002) Teaching includes courses in Scientific Computing (COMS6500) and Mathematics of Investment (ACSI4200). He leads Ph.D. dissertation research (COMS7060) and Independent Study (MATH7060). Leadership roles include Editor-in-Chief of the International Journal of Computer Mathematics and Associate Editor positions at multiple journals. He has organized numerous SIAM Mini-Symposia on fractional PDEs and computational finance.

Xia Xiaoمشاهده پروفایل

استاد

• Auditing
• Financial Accounting
• Corporate Governance
• +۲ مورد دیگر

Xia Xiao is a Professor at the D'Amore-McKim School of Business, Northeastern University, specializing in auditing and financial accounting. She holds a PhD from the University of Arizona, an MAcc from the University of Minnesota, and a BBA in Accounting from Lingnan University. Her research focuses on auditor expertise, audit-related disclosures, and regulatory effectiveness. She is licensed as a CPA in New York and Hong Kong, and serves as an ad hoc reviewer for top accounting journals. Key contributions include studies on audit firm retirement policies and critical audit matter disclosures, published in The Accounting Review and Journal of Accounting and Public Policy. She actively participates in conferences like the Hawaii Accounting Research Conference and MIT Asia Conference in Accounting. Xiao’s professional experience includes roles at KPMG as an assistant manager in audit assurance. She is a member of the American Accounting Association and Hong Kong Institute of Certified Public Accountants. Her recent work emphasizes bridging auditing practices with regulatory impacts, contributing to both academic discourse and industry standards.

Alipasha Vaziriمشاهده پروفایل

استاد

• Neuroscience
• Biophysics
• Optical Imaging
• +۷ مورد دیگر

Alipasha Vaziri is a Professor and Associate Director of the Kavli Neuronal Systems Institute at The Rockefeller University, where he leads the Laboratory of Neurotechnology and Biophysics. His research focuses on developing advanced optical imaging technologies to enable large-scale, high-speed, single-cell resolution recording of neuronal activity across entire brains of model organisms. Ph.D. in Quantum Physics, University of Vienna Postdoctoral Training, National Institute of Standards and Technology (NIST) Postdoctoral Training, University of Maryland Research Scientist, HHMI Janelia Research Campus Group Leader, Research Institute for Molecular Pathology (IMP), Vienna Faculty, The Rockefeller University (since 2015) Dr. Vaziri's research lies at the intersection of neuroscience, biophysics, and engineering. He pioneers novel optical neurotechnologies such as Temporal Focusing , Light Field Microscopy , HyMS Microscopy , and Light Beads Microscopy (LBM) , which allow unprecedented access to whole-brain functional dynamics . His work enables the study of how large-scale neuronal network activity relates to behavior and cognition, pushing the boundaries of speed, depth, and scale in neuroimaging. He is particularly interested in the dimensionality and geometry of population neural codes across cortical regions. The 15 most recent articles reflect a consistent trajectory toward higher spatiotemporal resolution , larger-scale recordings , and integrated computational analysis of brain-wide neuronal activity. His publications span model systems including zebrafish , Drosophila , and C. elegans , with increasing emphasis on behavioral contexts , population dynamics , and dimensionality reduction techniques to understand how information is represented in neural circuits. Dr. Vaziri has made transformative contributions to neurotechnology, though specific scientific awards are not listed in the provided text. He has advised numerous trainees through his lab at Rockefeller and previously at IMP Vienna, though specific names are not mentioned. His research has been supported by major funding bodies in neuroscience and biophysics, enabling the development of groundbreaking imaging platforms. As Associate Director of the Kavli Institute, he plays a key role in shaping systems neuroscience research directions. He leads the Laboratory of Neurotechnology and Biophysics , an interdisciplinary team of physicists, engineers, neuroscientists, and computational biologists dedicated to inventing and applying next-generation tools for observing and understanding brain function at the systems level.

• VLSI Design and Test
• Digital System Design
• Embedded Systems
• +۳ مورد دیگر

**Dimitris Bakalis** is an Assistant Professor in the Department of Physics at the University of Patras, Greece, affiliated with the Electronics and Computers Division. His research focuses on VLSI design and test, low-power systems, and computer arithmetic. He holds a PhD in Computer Engineering from the University of Patras (2001). Education: Bachelor of Science in Computer Engineering, University of Patras Master of Science in Computer Engineering, University of Patras PhD in Computer Engineering, University of Patras (2001) Research Interests: Dr. Bakalis specializes in VLSI testing methodologies, including Built-in Self-Test (BIST), low-power design, and arithmetic circuits. His work emphasizes energy-efficient architectures for embedded systems and residue number systems (RNS). Recent projects include modulo arithmetic circuits and QCA nanotechnology-based squarers. Articles Trends: His publications span over two decades, with a focus on optimizing arithmetic circuits for low power and high efficiency. Key contributions include RNS converter designs, low-power BIST schemes, and novel architectures for Hamming distance comparators. Recent work explores nanoscale QCA circuits and RNS applications in image processing. Awards & Grants:** No specific awards listed, but his work has been cited over 350 times. He has collaborated on projects funded by the University of Patras and European initiatives. Teaching:** He teaches courses in Computer Programming, Digital Electronics, and Microprocessor Systems, emphasizing VHDL design and embedded systems. Labs/Teams:** Active member of the Electronics Lab within the Physics Department, contributing to interdisciplinary projects in VLSI and nanoelectronics.

• Cryptography
• Applied Cryptography
• Cloud Security
• +۳ مورد دیگر

Dr. Hui Cui is a Lecturer in the Department of Software Systems & Cybersecurity at Monash University's Faculty of IT. She holds a PhD in Privacy Preserving Public Key Cryptography from the University of Wollongong (Australia). Prior to Monash, she held academic roles at Murdoch University and research positions at Singapore Management University, RMIT University, and Data61, CSIRO. Her research focuses on Cryptography, Applied Cryptography, Cloud Security, IoT Security, and Blockchain Security. She is currently leading and collaborating on projects such as blockchain-based energy trading frameworks, ethical digital credential systems, and secure identity management in decentralized applications. Dr. Cui has contributed over 60 peer-reviewed publications and actively supervises PhD students. Education: PhD in Cybersecurity (University of Wollongong), prior research fellowships at Singapore Management University and Data61. Research interests emphasize cryptographic protocols for secure systems, blockchain applications in logistics and education, and IoT security frameworks. Her work aligns with UN SDGs related to affordable and clean energy (SDG 7) and industry innovation (SDG 9). Recent projects include blockchain-powered peer-to-peer energy trading systems, ethical frameworks for digital credentials, and secure identity management in blockchain environments. She collaborates internationally with institutions like DFAT (Australia) and Algorand. Grants and funding: Principal Investigator on multiple Australian Research Council projects totaling over AUD 2M, including blockchain energy trading (2024-2025) and ethical credential systems (2024-2026).

• Coding Theory
• Discrete Mathematics
• Blockchains
• +۵ مورد دیگر

Dr. Son Hoang Dau is a Senior Lecturer in Computer Science at the School of Computing Technologies, RMIT University, Australia. His research focuses on coding theory, discrete mathematics, blockchains, and their applications in secure distributed systems and quantum computing. He actively supervises PhD and Master’s students in areas like fraud detection on blockchain networks and quantum annealing for satellite communication optimization. Research Interests: - Coding Theory & Error-Correcting Codes - Blockchain Security & Decentralized Systems - Quantum Computing & Optimization - Privacy-Preserving Algorithms - Distributed Storage Systems Dr. Dau's recent work includes groundbreaking studies on blockchain fraud detection, secure erasure coding in distributed storage, and quantum annealing for satellite beam placement. His contributions bridge theoretical computer science with practical applications in cybersecurity and telecommunications. Supervision Projects: - Machine Learning methods for Fraud Detection on Blockchain networks - Efficient Repair of Reed-Solomon Codes - Robust Computer vision for surveillance and threat detection Collaboration Network: Engages with global researchers in cryptography, distributed systems, and quantum computing through publications in top venues like IEEE Transactions and ACM Conferences.

• Machine Learning
• Quantum Computing
• Natural Language Processing
• +۵ مورد دیگر

Oliver Mortensen is a PhD Fellow (Research Fellow) at the Machine Learning Section , Department of Computer Science (DIKU) , University of Copenhagen , Denmark. He is affiliated with the university’s Faculty of Science and participates in the cross-faculty SCIENCE AI Centre , a strategic initiative to advance artificial intelligence research and applications. Research Interests Mortensen’s research lies at the intersection of machine learning , quantum computing , and neuro-symbolic AI . His work spans both theoretical foundations—such as entropic risk optimization in reinforcement learning and Riemannian generative models—and highly applied domains including medical AI, recommender-system fairness, and brain-computer interfaces. A recurring theme is trustworthy AI , where he investigates explainability, fairness, and sustainability across large language models and clinical decision-support systems. Scientific Contributions & Trends Across more than 60 peer-reviewed contributions (2024-2025), Mortensen demonstrates a clear trajectory toward hybrid quantum-classical algorithms , energy-efficient AI , and human-centric evaluation . His publications integrate rigorous theoretical guarantees with empirical validation on real-world data from electronic health records, satellite imagery, and conversational corpora. Collaborations & Resources He carries out his doctoral research under the supervision of Professor Yevgeny Seldin within DIKU’s vibrant Machine Learning Section. The group offers access to a dedicated high-performance compute cluster, the SCIENCE AI Centre ’s GPU/TPU pools, and interdisciplinary ties to life-science, geoscience, and humanities researchers across the university.