Sensor Networks / AMR Professors and Supervisors

Katharina Watsonمشاهده پروفایل

دانشیار

Royal Agricultural UniversityUnited Kingdom

Dr. Katharina Watson is an Associate Professor in Animal Science at the Royal Agricultural University (RAU), where she has held the role of Research Culture Coordinator since 2020. She leads research in livestock disease, antimicrobial resistance, and precision livestock technologies. Prior to RAU, she conducted postdoctoral research at the University of Warwick, focusing on ovine footrot epidemiology. Her academic qualifications include a PhD in Veterinary Epidemiology (University of Warwick, 2017) and a BSc in Animal Science (University of Essex/Writtle College, 2012). She also holds postgraduate certificates in academic practice and teaching in higher education. Her research focuses on animal health, infectious diseases, and innovative technologies to address challenges in livestock production. Current projects include using Far UV light for livestock disinfection and co-designing breeding strategies for net-zero emissions. She has secured significant grants, including a £321,000 Innovate UK award for UV disinfection studies and £250,000 for Enterococcus cecorum research in broilers. Dr. Watson is a Fellow of the Higher Education Academy and actively contributes to networks like the Animal Welfare Research Network and AMR in Agrifood Systems Transdisciplinary Network. Her teaching portfolio includes modules on applied animal science, wildlife ecology, and conservation ethics. Her advising includes PhD candidates Iris McCormick (virtual livestock fencing) and Jennifer Howse (farmer wellbeing). She has published extensively in journals like One Health , Poultry Science , and Nature Scientific Reports , focusing on antimicrobial resistance, molecular diagnostics, and precision livestock technologies.

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Nikhil Bhallaمشاهده پروفایل

مدرس

Ulster UniversityUnited Kingdom

Dr Nikhil Bhalla is a Lecturer in Electronic Engineering at the School of Engineering, Ulster University. His research spans interdisciplinary domains including nanobiosensors, plasmonics, and biofilm dynamics, with applications in healthcare and environmental monitoring. Projects: OPAQUE (PFAS detection), AMR Network (antimicrobial resistance), Microneedle Array Patch (CKD monitoring) Funding: The British Academy, BBSRC, British Council Research focuses on nanoplasmonics, biosensing, and acoustics. Recent work examines viral detection, nanoparticle toxicity, and fluid dynamics at solid-liquid interfaces. Publications highlight trends in nanoplasmonic diagnostics, biofilm mechanics, and interdisciplinary approaches to disease prevention. Collaborations extend to the British Council and BBSRC, with active projects until 2028. Current affiliations include the School of Engineering and Faculty of Computing, Engineering & Built Environment. No formal student advisement or awards are explicitly documented in the provided materials.

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Amr Abdelbariمشاهده پروفایل

استادیار

Near East UniversityCyprus

Assistant Professor Amr Abdelbari is affiliated with the Data Analytics Engineering Department at Near East University. His research focuses on wireless communication systems, signal processing, and machine learning applications in telecommunications. Academic Rank: Assistant Professor University: Near East University Department: Data Analytics Engineering Research interests include: Massive MIMO and 5G network optimization Direction-of-Arrival (DOA) estimation techniques Machine learning for wireless communication IoT applications in civil engineering Probabilistic and fuzzy logic-based signal processing Recent publications (2020-2025) demonstrate expertise in wideband signal processing, NOMA systems, and error probability modeling. Key trends in his work include integrating fuzzy logic for network optimization, improving DOA estimation for 5G systems, and applying neural networks to renewable energy modeling. Contact: amr.abdelbari@neu.edu.tr

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Alanwar Amrمشاهده پروفایل

استاد

Technical University of MunichGermany

Prof. Alanwar Amr is a Professor at the Chair of Cyber-Physical Systems within the TUM School of Computation, Information and Technology at Technical University of Munich (TUM). His research focuses on data-driven reachability analysis, security-assured reinforcement learning, and privacy-preserving estimation techniques using advanced mathematical frameworks like zonotopes. He holds a PhD from TUM and has held prior positions as an Assistant Professor at Jacobs University Bremen and a postdoctoral researcher at KTH Royal Institute of Technology. His work bridges formal verification, control theory, and cybersecurity in cyber-physical systems. Education: PhD in Automation and Control from TUM (under Prof. Althoff) Research Associate at UCLA and Engineer at Siemens/Morpho Research Interests: Data-driven formal verification methods Secure and resilient control systems Privacy-preserving set-based estimation Adversarial attack defense mechanisms His recent publications emphasize advancements in zonotope-based techniques for safety verification, privacy in distributed systems, and AI-driven control systems with formal guarantees. Key contributions include logical zonotopes for boolean function analysis and diffusion-based observers for multi-agent systems. Notable awards include the KTH Postdoctoral Fellowship, Qualcomm Innovation Fellowship finalist distinctions (2017/2018), and a best demonstration award at IPSN 2017. His work addresses critical challenges in autonomous systems, cybersecurity, and privacy in IoT environments.

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Noorul Aminمشاهده پروفایل

پژوهشگر ارشد

University of QueenslandAustralia

Dr. Noorul Amin is a Postdoctoral Research Fellow at the School of Veterinary Science, The University of Queensland, affiliated with the SAAFE CRC's data analytics program. His research focuses on computational approaches to biological challenges, including omics data analysis, antimicrobial resistance, and machine learning applications in agribusiness and environmental systems. Education: Masters (Research) of Computer Engineering, Kyung Hee University Doctor of Philosophy of Computer Science, La Trobe University Research Focus: His work integrates machine learning, cloud computing, and big data analytics to address biological problems, with emphasis on antimicrobial resistance pathways, omics tool development, and computational genomics. Primary domains include bioinformatics, non-coding RNA classification, and single-cell sequencing methodologies. Publication Trends: Recent articles (2019-2025) predominantly explore machine learning in genomics and non-coding RNA analysis, with emerging focus on single-cell sequencing technologies and antimicrobial resistance mechanisms. Earlier work (2014-2017) centered on computational algorithms for graph theory and sensor networks. Student Advising & Projects: Actively seeking Honours and PhD candidates for projects including: AMR Digital Twin: Machine learning framework for antimicrobial risk assessment Semantic interoperability for OneHealth antimicrobial data integration AI-powered knowledge graphs for agricultural optimization Self-evolving ontology systems for cross-sectoral antimicrobial resistance analysis Collaborations: Contributes to the SAAFE CRC's mission through data analytics program initiatives, collaborating with interdisciplinary teams on food security and environmental health challenges.

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Amr Alanwar Abdelhafezمشاهده پروفایل

استاد مدعو

Constructor University BremenGermany

Amr Alanwar Abdelhafez is an Adjunct Professor of Computer Science at Constructor University Bremen’s School of Computer Science & Engineering. Previously, he held Assistant Professor roles at Technical University of Munich (Heilbronn Campus) and Jacobs University Bremen. His research focuses on Cyber-Physical Systems (CPS), emphasizing safety, privacy, and formal verification. He earned his Ph.D. from TU Munich’s Cyber-Physical Systems Group (2020), with prior roles including postdoc at KTH Royal Institute of Technology and research positions at UCLA and University of Waterloo. Education: Ph.D. in Cyber-Physical Systems, Technical University of Munich (2015–2020) M.Sc. in Engineering Science (Protection and Detection Hardware Trojan), Ain Shams University (2010–2013) B.Sc. in Computer and Control Systems Engineering, Ain Shams University (2005–2010) Research Interests: His work bridges theoretical foundations and practical applications in CPS, including privacy-preserving state estimation, resilient control systems, reachability analysis, and formal verification for autonomous systems. He develops methods to ensure safety and privacy in distributed systems, leveraging tools like zonotopes and homomorphic encryption. Key Contributions: Developed logical zonotopes for efficient representation of discrete systems. Advanced event-triggered control and diffusion strategies for distributed systems. Pioneered privacy-preserving techniques (e.g., CryptoImg, PrOLoc) using homomorphic encryption. Contributed to safety-critical applications like autonomous vehicle situational awareness and secure sensor networks. Awards & Recognition: Best Demonstration Paper Award at IPSN/CPSWeek 2017 Qualcomm Innovation Fellowship finalist (2017 and 2018) First place in TUM Graduate School Competition (2019) Grants & Industry Links: His work is supported by collaborations with institutions like IBM and JetBrains, and his open-source tools (e.g., Event-Triggered Diffusion Kalman Filters, Logical-Zonotope repository) are widely used in CPS research. Labs & Teams: Leads research on CPS safety and privacy at TU Munich, with active contributions to Constructor University’s CPS initiatives and GitHub repositories showcasing implementations of his methodologies.

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Joy Wattsمشاهده پروفایل

استاد

University of PortsmouthUnited Kingdom

Joy Watts is a Professor of Environmental Microbiology and Associate Dean (Research and Innovation) at the University of Portsmouth , affiliated with the Faculty of Science and Health and School of the Environment and Life Sciences . Her work focuses on applying molecular tools to study microbial diversity and interactions, particularly in degrading recalcitrant organic compounds like lignin, antimicrobial resistance (AMR) in aquaculture, and the plastisphere of marine pollution. Research Themes: Microbial degradation of polymers, GI tract microbiomes of wood-eating organisms, AMR dynamics, marine biofilm analysis Notable Roles: Editor-in-Chief for Environmental Microbiome , Expert Panel for European Commission Horizon 2020, Advisor for Marine Microbiome Policy Report Article Trends: Recent publications highlight AMR in wastewater, microplastic-biofilm interactions, and microbial solutions for environmental challenges. Her work spans Environmental Microbiology , Marine Science , and Bioremediation . Funding: European Commission, NERC, Innovate UK Network: Collaborations with European Commission, NERC, National Biofilms Innovation Centre

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Marius Volmerمشاهده پروفایل

دانشیار

Transilvania University of BrasovRomania

Marius Volmer is an Associate Professor at the Technical University of Brașov , affiliated with the Department of Electrical Engineering and Applied Physics within the Faculty of Electrical Engineering and Computer Science . His research focuses on nanostructured magnetic systems , spintronics , magnetic sensors , and graphene-based devices , with expertise in magnetic and electrical characterization techniques . He has contributed to advancements in biosensor design, low-field magnetic sensing, and nanotechnology applications. Volmer’s work spans lab-on-a-chip systems , nanoparticle detection , and IoT-enabled monitoring solutions . His recent publications highlight innovations in planar Hall effect sensors, magnetoresistive bridge sensors, and optoelectronic microfluidic devices for biomedical applications. He has also explored the integration of LoRa networks for renewable energy monitoring and cost-effective telemedicine systems. His research often bridges materials science and applied physics , with a focus on translating fundamental discoveries into practical technologies. Notable contributions include optimizing GMR-based current sensors and developing antibody-functionalized nanoparticles for cancer diagnostics. Volmer’s expertise is further reflected in his simulation work using tools like OOMMF for magnetization dynamics modeling and structural analysis of thin films and nanomaterials.

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Hemant Purohitمشاهده پروفایل

استادیار

Florida Institute of TechnologyUnited States

Dr. Hemant Purohit is an Assistant Professor and Program Chair (Electrical and Computer Engineering) at the Florida Institute of Technology , affiliated with the College of Engineering and Science and the Department of Electrical Engineering and Computer Science . His expertise spans Model-Based Engineering, Mobile Communication, Digital Communication, and Microprocessors . He holds IEEE Senior Membership and active roles in IEEE Circuits and Systems Society, IEEE Communications Society, IEEE Systems Council, and IEEE Council on RFID. Dr. Purohit has over 19 years of teaching experience with students from diverse nationalities. He received the 2024 Faculty Excellence Award for Teaching at Florida Tech and the Best Teacher Award (three times) at JIET Jodhpur. His research focuses on optimizing communication networks, including Data Interleaving Techniques for resilient systems, RFID system optimization, and pandemic impact analysis on mobile networks. Notable contributions include work on Model-Based Systems Engineering (MBSE) for contingency planning in cellular networks, autonomous systems assurance , and genetic adaptation in fowl under climatic stress . His publications address challenges in wireless communication, network security, and environmental resilience. Grants and collaborations are not explicitly detailed in the text, but his active IEEE memberships suggest involvement in industry-academia partnerships. No lab or team affiliations are specified in the provided data.

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JAVIER DÍEZ GONZÁLEZمشاهده پروفایل

استاد

University of León (ULE)Spain

JAVIER DÍEZ GONZÁLEZ is a Professor at the Universidad de León , affiliated with the College of Industrial, Information and Aerospace Engineering and the Department of Mechanical, Computer and Aerospace Engineering . He leads research in intelligent systems for manufacturing ( SINFAB research group), focusing on cutting-edge applications of localization technologies, robotics, and optimization algorithms. Research Interests : Advanced localization systems for autonomous vehicles and robots Smart manufacturing and Industry 4.0/5.0 integration Optimization techniques for wireless sensor networks Metaverse applications in industrial and educational contexts Hybrid AI and fuzzy logic for aerospace engineering problems Scientific Contributions : His recent work (2025-2024) explores asynchronous localization architectures, collaborative robotics, mixed reality training, and metaverse-human interaction. He has pioneered UWB-based positioning solutions for UAVs and AMRs, with a strong focus on error characterization, sensor deployment, and robustness under failure conditions. Academic Background : Earned a PhD (2020) from Universidad de León with a thesis on time-based local positioning systems, supervised by Dr. Hilde Pérez García.

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Amr Mahmoudمشاهده پروفایل

استادیار

University of PittsburghUnited States

Dr. Amr Mahmoud is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Pittsburgh. His work focuses on neuromorphic computing systems, machine learning, and FPGA-based accelerators for image processing and video prediction. PhD in Computer Engineering, University of Pittsburgh (2019) MSc in Engineering Physics, Cairo University (2015) BSc in Electronics and Electrical Communications Engineering, Cairo University (2011) Dr. Mahmoud’s research bridges neuromorphic computing and machine learning, particularly for biomedical and sensor applications. He designs systems leveraging memristor crossbar arrays to emulate biological neural networks, enabling energy-efficient hardware solutions for tasks like cardiac arrhythmia classification and optical sensor prediction. His recent publications highlight advancements in memristor modeling, hybrid spiking neural networks, and hardware implementations using neuromorphic architectures. Key trends include real-time biomedical diagnostics, LSTM-based sensor prediction, and crossbar array optimization for machine learning. Contact: AMM418@pitt.edu

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