جست‌وجوی استاد و پژوهشگر

• Algebraic Geometry
• Hyperkähler Manifolds
• Rozansky-Witten Invariants
• +۳ مورد دیگر

Prof. Dr. Marc Nieper-Wißkirchen is a University Professor (W3) for Algebra and Number Theory at the Institute of Mathematics, University of Augsburg, since 2008. He has held visiting positions at the Max Planck Institute for Mathematics in Bonn and the University of Cambridge, and served as a Junior Professor at Johannes Gutenberg University Mainz (2004–2008). Since October 2021, he has been Vice Dean of the Faculty of Mathematics, Natural Sciences and Technology (MNTF). Education: Diploma in Mathematics (2000) from the University of Cologne, preceded by preliminary diplomas in physics (1997) and mathematics (1997). His doctoral studies (2000–2002) under Prof. Daniel Huybrechts focused on characteristic classes and Rozansky-Witten invariants of hyperkähler manifolds. His research spans algebraic geometry, differential geometry, and mathematical physics, with a focus on hyperkähler manifolds, Hilbert schemes of points, irregular singular connections, and Stokes phenomena. He has contributed to the understanding of Rozansky-Witten invariants, Chern numbers, and topological aspects of differential equations. Recent publications include works on Betti structures of hypergeometric equations (2022) and Stokes matrices for confluent hypergeometric equations (2022), reflecting his ongoing exploration of differential equations' geometric underpinnings. Earlier works address Hochschild homology, equivariant cohomology, and operads in algebraic contexts. His computational contributions include software demonstrations for elliptic curve arithmetic, Collatz sequences, and Google Matrix simulations. Technical expertise includes programming languages (TeX, PHP, HTML) and systems (Unix/Linux, Zope/Plone).

Fangzhou Jinمشاهده پروفایل

استادیار

• Algebraic Geometry
• Pure motives
• Mixed motives
• +۵ مورد دیگر

Fangzhou Jin is an Assistant Professor at the School of Mathematical Sciences, Tongji University. His research focuses on advanced topics in Algebraic Geometry , particularly in Motivic Homotopy Theory , Algebraic K-theory , and Real Algebraic Geometry . He has extensive experience in collaborative mathematical research, having worked with prominent mathematicians such as Frédéric Déglise, Enlin Yang, and Marc Levine. Education : Ph.D. in Mathematics (2016, École Normale Supérieure de Lyon), M.Sc. in Pure Mathematics (2012, Université Paris-Diderot), Diploma of ENS (2013) His work bridges Algebraic Cycles with Étale Cohomology , exploring Weight Structures in mixed motives and Chern Classes in motivic contexts. Jin has contributed to the theory of Trace Maps and Local Terms in motivic homotopy, as well as the study of Flat Cohomology and Real Schemes . Key trends in his publications include: 2025: Cohomology of singular varieties via real cycle class maps 2024: Trace maps and local terms in motivic homotopy 2023: Moving lemmas in homotopy colevel theory 2022: Quadratic conductors, perverse homotopy, and pro-Chern classes 2021: Rational motivic homotopy and Künneth formulas 2020: Gersten complexes and real flat cohomology 2018: Algebraic G-theory in motivic categories 2016: Borel-Moore homology and weight structures Scientific Awards & Grants : Fundamental Research Funds for Central Universities (2021-2025) National Natural Science Foundation of China Grants 12101455 (2022-2024), 12471014 (2025-2028) National Key R&D Program of China 2021YFA1001400 (2022-2026) DFG Priority Programme SPP 1786 & ERC Project QUADAG (2018-2020) Advising & Teaching : Jin has supervised exercise classes and seminars at multiple institutions, including Universität Duisburg-Essen and Tongji University. His teaching spans Algebraic Topology , Étale Cohomology , and Algebraic Geometry . Labs & Collaborations : Active in international collaborations, he is a key member of the Algebraic Geometry and Ramification Seminar at Tongji University and has participated in DFG Research Training Group 2553 during his postdoctoral period.

Matthias Ihmeمشاهده پروفایل

استاد

• Combustion Science
• Fluid Dynamics
• Computational Fluid Dynamics
• +۵ مورد دیگر

Matthias Ihme is a Professor in the Department of Mechanical Engineering and Photon Science Directorate at Stanford University. His research focuses on large-eddy simulation (LES) of turbulent reacting flows, aeroacoustics, combustion-generated noise, numerical methods, and high-order schemes. He holds a Ph.D. from Stanford University (2008), an M.Sc. in Computational Engineering from the University of Erlangen (Germany, 2002), and a Dipl.-Ing. in Mechanical Engineering from Munich University of Applied Sciences (Germany, 2000). His work bridges computational fluid dynamics, combustion science, and photon science, with notable contributions to supercritical fluid dynamics, machine learning integration in fluid simulations, and high-fidelity atmospheric transport modeling. Recent research emphasizes ultrafast cluster dynamics, shock-induced interface behavior, and stochastic ignition mechanisms in advanced fuel systems. Publications highlight interdisciplinary advancements, including physics-informed ML frameworks for reacting flows and experimental studies using X-ray photon correlation spectroscopy. His projects often involve high-performance computing and collaboration with national labs like SLAC.

Peng Liمشاهده پروفایل

استاد

• Integrated Circuits and Systems
• Brain-Inspired Computing
• Electronic Design Automation
• +۶ مورد دیگر

Peng Li is a Professor in the Department of Electrical and Computer Engineering at the University of California, Santa Barbara. His research focuses on integrated circuits, brain-inspired computing, electronic design automation, and hardware machine learning systems. He holds Fellow status in the Institute of Electrical and Electronics Engineers (IEEE). His work emphasizes neuromorphic engineering, spiking neural networks, and the intersection of machine learning with analog circuit design. Education includes a PhD in Electrical and Computer Engineering from Carnegie Mellon University, an MS in Systems Engineering from Xi'an Jiaotang University, and a BS in Information Science and Engineering from the same institution. His research has been recognized with prestigious awards including the ICCAD Ten-Year Retrospective Most Influential Paper Award and multiple Design Automation Conference Best Paper Awards. Key research trends in his articles include advancements in spiking neural networks (SNNs), hardware accelerators for neuromorphic computing, Bayesian optimization for analog circuit design, and robustness in machine learning systems. He explores topics like adversarial robustness, energy-efficient architectures, and data-efficient prediction techniques. His work bridges theoretical machine learning models with practical hardware implementations, particularly in 3D integration and systolic array acceleration. Notable contributions include pioneering hybrid approaches combining formal verification with machine learning for analog circuits (HFMV framework), and innovations in neuromorphic processors such as the 3D Liquid State Machine architecture. His research also addresses challenges in semiconductor manufacturing, including wafer map pattern recognition and failure detection through semi-supervised learning and contrastive methods. Awards highlight his impactful contributions to both design automation and neural computing. His grants and collaborations likely span industry partnerships in semiconductor technology and neuromorphic computing. He leads a lab focused on next-generation hardware-software co-design for intelligent systems, emphasizing energy efficiency and scalability.

• Microbial ecology
• Soil ecology
• Community ecology
• +۵ مورد دیگر

Tancredi Caruso is an Associate Professor at the School of Biology and Environmental Science, University College Dublin. He holds a PhD in Ecology from the University of Siena (2006) and a Postgraduate Certificate in Higher Education Teaching (2015). His career includes roles as Reader and Lecturer at Queen's University Belfast, and research fellowships at Freie Universität Berlin and the University of Siena. Research Interests : Caruso's work focuses on biodiversity processes, aboveground-belowground linkages, ecological networks, and ecosystem responses to perturbations. His research has led to over 100 peer-reviewed publications and grants from the Alexander von Humboldt Foundation, NERC, EU Marie Sklodowska-Curie program, and others. Teaching & Professional Activities : Coordinates modules on environmental science, soil ecology, and conservation. Active in professional committees, including the IEA Committee. Languages: Italian, English, German (fluent), and French (reading). Grants & Collaborations : Leads projects like the ReEcoNet initiative. Recent grants include funding for wheat genetic diversity (EU), soil-microbe interactions (Leverhulme Trust), and climate-land use impacts (NERC). Key Contributions : Pioneered studies on mycorrhizal networks, soil microbial responses to drought, and the ecological role of oribatid mites. His work bridges theoretical ecology and applied conservation, emphasizing stochastic processes and biodiversity resilience.

Andreas Herzمشاهده پروفایل

استاد

• Computational Neuroscience
• Neural Coding
• Spatial Navigation
• +۳ مورد دیگر

Prof. Dr. Andreas Herz is a Chair in Computational Neuroscience at the Faculty of Biology, Ludwig-Maximilians-Universität München (LMU). His research focuses on understanding neural mechanisms underlying spatial navigation, temporal cognition, and sensory processing. He leads the Computational Neuroscience group and collaborates with the Bernstein Center for Computational Neuroscience Munich. Research Interests: Dr. Herz investigates how neural systems encode spatial and temporal information, including grid cells, head-direction systems, and neural coding strategies. His work bridges experimental neurophysiology with theoretical modeling, addressing topics like cognitive maps, neural variability, and synaptic plasticity. Teaching & Mentorship: He oversees advanced courses on computational neuroscience and neurophysiology, fostering interdisciplinary training for graduate students. His research group includes prominent collaborators like Dr. Martin Stemmler and PD Dr. Kay Thurley, focusing on projects involving neural network dynamics and behavioral neuroscience. Publications & Impact: Over 85 peer-reviewed articles highlight his contributions to understanding entorhinal-hippocampal circuits, dendritic processing, and neural representation of space/time. Key work includes studies on grid cell variability, zebrafish spatial memory, and cytoskeletal organization in dendritic spines.

Lynn Wrightمشاهده پروفایل

مدرس ارشد

• Laterality and handedness
• Behavioural inhibition
• Emotional processing
• +۲ مورد دیگر

Dr. Lynn Wright is a Senior Lecturer in Psychological Sciences at Abertay University with 19+ years of teaching experience. A Chartered Psychologist and Senior Fellow of the Higher Education Academy, she specializes in laterality research with expertise in handedness, anxiety, and behavioral inhibition. Research Focus: Investigates neurological asymmetries through paradigms like Tower of Hanoi tasks, EEG, and TMS. Key interests include: handedness effects on decision-making, emotional processing biases, and personality correlates (perfectionism, escapism). Publication Analysis: Her work (2005-2023) demonstrates consistent exploration of lateralization using behavioral experiments. Recent articles examine environmental influences on anxiety and collaborative research models. Awards & Recognition: Outstanding Teacher Award 2018 Carnegie Trust Travel Grant (2012) Nominated annually for teaching awards since 2010 Supervision & Leadership: Supervised 100+ student projects and 5 Master's researchers. Founded the Research Volunteer Scheme and organized the North Sea Laterality Meeting (2018). Coordinates the Growth Mindset project with Dundee schools and Leisure/Culture Dundee. Educational Initiatives: Leads modules in Psychological Research Methods and Advanced Research Design. Developed ATLEF-funded online resources for statistics instruction.

Chris Peikertمشاهده پروفایل

استاد

• Cryptography
• Lattice-based Cryptography
• Coding Theory
• +۲ مورد دیگر

Chris Peikert is a Professor in the Department of Computer Science and Engineering at the University of Michigan's College of Engineering. He received his Ph.D. from MIT's Computer Science and Artificial Intelligence Laboratory in 2006 under the supervision of Silvio Micali. Peikert is a leading researcher in cryptography, particularly known for his foundational work in lattice-based cryptography. His research interests span cryptography, lattices, coding theory, algorithms, and computational complexity, with a particular focus on cryptographic schemes whose security can be based on the apparent intractability of lattice problems. Peikert has made significant contributions to the development and analysis of lattice-based cryptographic primitives, including ring-LWE, fully homomorphic encryption, and zero-knowledge proofs. Peikert's recent work demonstrates continued leadership in post-quantum cryptography, with publications in top venues like CRYPTO, EUROCRYPT, and STOC. His research spans theoretical foundations of lattice problems to practical implementations of lattice-based cryptographic systems, including hardware acceleration for fully homomorphic encryption. IACR Fellow (2024) Test-of-Time Award from Crypto 2008 (2023) TCC Test-of-Time Award (2017) Patrick C. Fischer Development Professor of Theoretical Computer Science (2017) Best Paper Award at Eurocrypt 2010 Best Paper Award at STOC 2009 Alfred P. Sloan Foundation Fellowship Google Research Award Peikert has been actively involved in the cryptographic research community, serving on program committees for major conferences including CRYPTO, EUROCRYPT, FOCS, and TCC (where he was program co-chair in 2021). He has also developed educational resources, including extensive lecture materials on lattice-based cryptography and teaching courses on cryptography and theoretical computer science at both the undergraduate and graduate levels.

Robin Crockettمشاهده پروفایل

پژوهشگر

• Document Forensics
• Academic Integrity
• Contract Cheating
• +۹ مورد دیگر

Dr Robin Crockett is the University Academic Integrity Lead at the University of Northampton, based in the Academic Registry. He is a mathematician-ethicist actively engaged in research and professional development in academic integrity, document forensics, and the detection of contract cheating and AI-generated text. He is a member of the European Network for Academic Integrity (ENAI), co-founder of the Midlands Integrity Group (UK), and has advised UK policymakers on legislation to ban essay mills. He holds Chartered Scientist and Chartered Mathematician status. MPhil, The Management of Electricity Supplies via Storage as Hydrogen, Cranfield University Master, Energy Conservation and the Environment, Cranfield University PhD, Electrostatic Damage to Semiconductor Devices, University of Southampton Master, Natural & Electrical Sciences, University of Cambridge Bachelor, Natural & Electrical Sciences, University of Cambridge Dr Crockett's research centers on document forensics and academic integrity, with core interests in Fourier theory, time-series analysis, and stylometry for identifying contract cheating. His work increasingly addresses the challenges posed by generative artificial intelligence in education. He applies mathematical and statistical methods to analyze linguistic cues, writing styles, and embedded information in student submissions. His recent publications highlight a strong trend toward understanding and mitigating academic misconduct in the AI era. Topics include AI-text detection uncertainties, forensic stylometry, and policy development for generative AI misuse. Earlier work includes environmental research on radon remediation and signal processing applications in telecommunications. Chartered Scientist Chartered Mathematician Dr Crockett has supervised PhD students, including Believe Nwamae in Computing. He has secured internal research funding, such as the Small Grants Scheme for Early Career Researchers at the University of Northampton for a project on AI-synthesized text detection. He has been an Academic Visitor at Loughborough University and served on the Turnitin Advisory Board, indicating active collaboration and external engagement. He frequently presents at academic events and contributes to policy discussions. He is affiliated with research networks including the European Network for Academic Integrity (ENAI) and the European Geosciences Union (as a former Scientific Officer). His work is supported by institutional and collaborative projects focused on advancing machine discernment of academic misconduct.

Ting Sunمشاهده پروفایل

دانشیار

• Urban climate modelling
• Climate change impacts and adaptation
• Extreme weather events in cities
• +۵ مورد دیگر

Dr Ting Sun is an Associate Professor in Climate & Meteorological Hazard Risks at University College London , Department of Risk and Disaster Reduction. He earned his BEng (2009) and PhD in Hydrology (2013) from Tsinghua University , followed by a visiting period at Princeton University (2011–2012). After postdoctoral appointments at Tsinghua and the University of Reading , he held a NERC Independent Research Fellowship at Reading (2017–2022) before joining UCL in May 2022. Education PhD in Hydrology, Tsinghua University, 2013 BEng in Hydraulic Engineering, Tsinghua University, 2009 Visiting PhD Student, Princeton University, 2011–2012 Research Interests Dr Sun’s work converges on urban climate modelling across scales —from neighbourhood blocks to global grids—focusing on the impacts of weather and climate extremes such as heat waves and extreme rainfall in cities. He is the lead developer of the Surface Urban Energy and Water balance Scheme (SUEWS) and its Python wrapper SuPy , developed in collaboration with Prof Sue Grimmond’s micromet group. He also contributes as a core member of the Urban Multi-scale Environmental Predictor (UMEP) development team. His multidisciplinary expertise integrates hydro-climate dynamics, computational modelling, machine learning, built-environment processes, and public-health linkages . Research Trends from Recent Publications Across the 15 most recent articles, a clear trajectory emerges from high-resolution urban-process modelling toward integrated socio-environmental assessments . Studies published in 2024–2025 couple atmospheric models (WRF-SUEWS) with global building-morphology datasets (GLAMOUR) to quantify how cities alter rainfall patterns, temperature sensitivity, and heat-related mortality. Earlier works progressively refined SUEWS’s physical parameterisations and Python accessibility, while recent outputs leverage deep-learning remote-sensing tools (SHAFTS) and hybrid hydrological-neural architectures to deliver actionable insights for urban planning and climate adaptation. Scientific Awards & Fellowships NERC Independent Research Fellowship , University of Reading, 2017–2022 HEA Fellowship , University College London, 2023 Professional Service & Editorial Roles Topic Editor , Geoscientific Model Development (from 2025) Editorial Board Member , Scientific Data (from 2024) Peer review and consultancy for journals, conferences, and policy bodies Supervision of taught-course projects and research degrees External examining and mentoring Labs, Teams & Collaborations Dr Sun leads and collaborates within the UCL Department of Risk and Disaster Reduction , working closely with the micromet group at the University of Reading (Prof Sue Grimmond) on SUEWS/SuPy development. He is an active member of the UMEP consortium and maintains extensive international collaborations spanning Tsinghua University, Princeton, and numerous European research centres, underpinning a vibrant, interdisciplinary research network focused on urban climate resilience.

Ken Duffyمشاهده پروفایل

استاد

• Network Coding
• Algorithms
• Probability and Statistics
• +۳ مورد دیگر

Ken Duffy is a Professor and Chair of the Department of Mathematics at Northeastern University, with a joint appointment in the Department of Electrical and Computer Engineering. He joined Northeastern in 2023 and previously served as Interim Chair of the latter department. Previously, he was a professor at the National University of Ireland, Maynooth, where he directed the Hamilton Institute (2016–2022) and co-directed the Science Foundation Ireland Centre for Research Training in Foundations of Data Science. He earned a PhD in Mathematics from Trinity College Dublin. His research focuses on collaborative, multi-disciplinary algorithm design using probability and statistics, with applications in digital circuits, DNA, and network coding. Notable contributions include the Royal Statistical Society’s Applied Probability Section (co-founded in 2011) and numerous award-winning papers in IEEE conferences and journals. Recent work emphasizes decoding algorithms like GRAND (Guessing Random Additive Noise Decoding), applied to error correction, wireless systems, and biomedical imaging. His articles address topics like soft-output decoding, interference mitigation, and cellular lineage tracing. Awards: Best Paper Awards (IEEE ICC 2015, IEEE TNSE 2019), COMSNETS Best Demo (2022–2023), and the IEEE Ellersick Award (2024). Advising: The SFI Centre he co-directed funded over 120 PhD students. Labs/Teams: Hamilton Institute, Royal Statistical Society’s Applied Probability Section, and collaborative projects in cellular dynamics and secure communication.

• Nanotechnology-based bioanalysis
• Mass spectrometry
• Lateral flow immunoassay
• +۵ مورد دیگر

Dr. Chang Lei is an ARC Discovery Early Career Researcher Award (DECRA) Fellow at the Department of Medical Sciences within the Faculty of Medicine and Health at The University of Sydney. She is also a member of The University of Sydney Nano Institute and the Charles Perkins Centre. With expertise in nanotechnology-based bioanalysis, mass spectrometry, lateral flow immunoassay, and tissue regeneration, Dr. Lei leads several innovative research projects focused on advancing healthcare through nanotechnology. Dr. Lei completed her PhD at the Australian Institute for Bioengineering and Nanotechnology (AIBN) at The University of Queensland (UQ). Her academic journey includes receiving the Queensland Government Advance Queensland Research Fellowship, the UQ Amplify Fellowship in 2021, and the prestigious ARC DECRA in 2024. Her research interests span across nanotechnology applications in healthcare, with particular focus on: Developing novel nanomaterials for single-cell metabolomics analysis Creating affordable and ultra-sensitive biomarker detection platforms Engineering silica bio-nanomaterials for stem cell differentiation and bone repair Advancing lateral flow immunoassay technologies using nanomaterials Applying nanotechnology to dental and craniofacial regeneration Dr. Lei's publication record demonstrates a strong focus on nanotechnology applications across multiple disciplines. Her recent work shows increasing emphasis on medical applications of nanomaterials, particularly in diagnostics, cancer therapy, and tissue regeneration. She has published in high-impact journals including Nature Science Review, Small, Biosensors and Bioelectronics, Angewandte Chemie, and Advanced Materials. Dr. Lei has received several notable awards and honors: 2024 ARC DECRA Fellow 2021 The University of Queensland Amplify Fellow 2020 GC Minimum Intervention Dentistry Research Award 2017 Advanced Queensland Research Fellow As a reviewer for scientific journals such as Science Advances, Journal of Nanobiotechnology, and Journal of Materials Chemistry B, and for ARC and NHMRC grants, Dr. Lei actively contributes to the scientific community. She also serves as an editor for Frontiers in Bioengineering and Biotechnology and Nano TransMed. Her current research projects are supported by grants including the ARC DECRA and the FMH Start-up Scheme. Dr. Lei is actively involved in several research groups and initiatives: Member of The University of Sydney Nano Institute Member of the Charles Perkins Centre Member of Australian and New Zealand Society for Mass Spectrometry Member of The Australian Materials Research Society Member of the Australian Nanotechnology Network

• Photonics
• Telecommunications
• Electrical Engineering
• +۳ مورد دیگر

LUIS GONZALEZ GUERRERO is an Assistant Professor at the Universidad Carlos III de Madrid, specializing in photonics and telecommunications. His research focuses on integrated photonic circuits for millimeter-wave and terahertz (THz) communication systems, with applications in satellite payloads, wireless fronthaul/backhaul, and space technology. He leads projects in hybrid integrated optical platforms (e.g., InP-Si3N4), laser stability, and high-frequency signal generation. His work bridges photonics with electrical engineering to enable next-generation wireless systems. Research Interests: Dr. Gonzalez Guerrero’s expertise spans integrated photonics, microwave photonics, THz communication links, satellite communication systems, and photonic signal generation. His innovations include low-noise radiometers, optical injection locking for stable local oscillators, and high-purity mm-wave/THz signal transmission. His contributions address challenges in frequency stability, bandwidth efficiency, and phase noise mitigation in high-frequency systems. Publications: His recent work emphasizes hybrid photonic platforms, sub-THz wireless bridges, and phase noise mitigation techniques. Articles highlight advancements in optical signal processing, laser source integration, and applications in space communication. His research trends reflect a strong focus on translating laboratory prototypes into deployable systems for satellite and terrestrial networks. Affiliations: He is affiliated with the Grupo Universitario de Tecnologías de Identificación (GUTI), a research group at UC3M. His work is supported by grants focused on photonic integrated circuits and space communication technologies. He collaborates internationally on projects involving multicore fiber systems, coherent THz transmitters, and optical frequency comb applications.

Herb Winfulمشاهده پروفایل

استاد

• Nonlinear Optics
• Laser Physics
• Quantum Tunneling
• +۲ مورد دیگر

Herb Winful is a Professor of Optics at the University of Michigan's College of Engineering, Department of Electrical and Computer Engineering. He specializes in nonlinear optics, laser physics, quantum tunneling , and photonics , with a focus on phenomena like superluminal group velocities, frequency comb generation, and light storage via stimulated Brillouin scattering. Research areas span quantum tunneling times , nonlinear photonic materials , and coherent beam combining in fiber laser arrays. His work includes frequency comb spectroscopy using quantum-well diode lasers, ultrafast erbium fiber lasers , and negative group delay engineering in birefringent waveguides. The article list reveals expertise in supercontinuum generation , evanescent wave dynamics , photonic crystals , and nonlinear pulse manipulation . Key subfields include stimulated Brillouin/Raman scattering , parabolic similaritons , and time-domain modeling of optical systems. Award-winning scientific contributions include resolving the Hartman effect paradox and optimizing fiber laser arrays for high-power applications. His research bridges theoretical insights with practical innovations in optical engineering and quantum optics .

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.