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Dr. Pouyan Nejadhashemi is an MSU Research Foundation Professor in the Departments of Plant, Soil and Microbial Sciences and Biosystems & Agricultural Engineering at Michigan State University. He serves as Director of the MSU Institute of Water Research and the Center for Intelligent Water Resources Engineering. His expertise spans ecohydrology, climate change adaptation, environmental impact assessment, and decision support systems for ecosystem sustainability. He holds a Ph.D. in Biological Resources Engineering from the University of Maryland. Dr. Nejadhashemi's research focuses on water quality modeling, non-point source pollution prevention, and integrating machine learning with hydrological systems. Key areas include irrigation optimization, PFAS contamination monitoring, and watershed management. He teaches courses on water resources systems analysis and ecohydrology. Awards: MSU Research Foundation Professor Title Grants: FAA grant for PFAS remediation, grants for developing agricultural innovations in Senegal and Bangladesh Labs/Teams: MSU Institute of Water Research, Center for Intelligent Water Resources Engineering His work bridges computational methods with environmental challenges, addressing global water security, food systems, and sustainable resource management. Recent projects include modeling water quality in the Chesapeake Bay and developing AI tools for agricultural extension platforms.

• Ecohydrology
• Water Quality Management
• Environmental Impact Assessment
• +6 more

Professor Ning Wang is a leading academic in communication systems at the University of Surrey's Institute for Communication Systems (ICS), School of Computer Science and Electronic Engineering. He holds a PhD from the University of Surrey (2004) and has expertise in 5G/6G networks, edge computing, and space-terrestrial integration. As a coordinator for the EuroMaster Programme and Communication Networks and Software (CNS) pathway, he leads research in network management, mobile video delivery, and IoT applications. His work has been featured in IEEE ComSoc Technology News three times since 2012. Current leadership roles include 5GIC Work Area 1 leader for content and network context. Research collaborations span global institutions like UCL, ETH Zurich, and industry partners like BT and InterDigital. Notable contributions include SDN-based space-terrestrial network integration (VDPA scheme) and O-RAN automation via federated DRL. Over 130 publications and active participation in standards bodies (IETF, 3GPP) reflect his impact on future network architectures. Educations: BEng in Computing (Changchun University of Science and Technology, 1996) MEng in Electronic Engineering (Nanyang Technological University, 2000) PhD in Electronic Engineering (University of Surrey, 2004) Research Focus: Future Internet design, network intelligence, content-centric networking, and satellite integration. Key projects include EU Horizon Europe SPIRIT (immersive telepresence), ESA TINA (satellite 5G functions), and EPSRC NG-CDI (converged digital infrastructures). His research emphasizes practical solutions like edge-AI for VNF splitting and holographic frame synchronisation. Grants & Projects: Over £20M in grants from EPSRC, EU Horizon, InnovateUK, and Royal Society. Active in EU-funded SAT5G (satellite-terrestrial 5G) and C-DAX (smart grid cybersecurity).

• 5G and beyond networking
• Future Internet design
• Mobile content delivery technologies
• +5 more

Ozgur Ozdemir is an Associate Research Professor in the Department of Electrical and Computer Engineering at North Carolina State University's College of Engineering. He is affiliated with the university's primary faculty and works closely with platforms like AERPAW and AFAR Challenge. His research focuses on advanced wireless systems, including UAV networks, mmWave technology, spectrum analysis, and radar-communication integration. His work spans experimental testbed development, digital twin applications for AI research, and methodologies for improving coverage in rural and urban environments. Ozdemir has contributed to standards like 5G NR and non-standalone 5G systems, emphasizing practical implementation and environmental impact analysis. He leads efforts in signal processing for autonomous systems and has expertise in software-defined radio (SDR) technologies. Research interests include aerial threat detection, RF signal analysis, and robust localization techniques. He explores challenges in NLOS bias correction, antenna radiation patterns, and passive reflector-based coverage enhancement. His work often combines theoretical models with experimental validation using platforms like AERPAW. His articles highlight advancements in drone detection systems, channel modeling for mmWave, and the integration of radar and communication systems. Key trends show a focus on outdoor/indoor spectrum measurements, UAV navigation, and resilient network design. Ozdemir's contributions are characterized by empirical studies and cross-disciplinary approaches to wireless challenges.

• Unmanned Aerial Systems (UAS)
• mmWave Technology
• Wireless Communication
• +7 more

Silvia Santini is an Associate Professor at the Faculty of Informatics of USI since 2016, leading the People-Centered Computing Lab. Previously, she held roles at TU Dresden (2014–2016) and TU Darmstadt (2011–2014), focusing on embedded systems and wireless sensor networks. She completed her PhD at ETH Zurich in 2009 and earned a Telecommunication Engineering degree from Sapienza University of Rome (2004). Her research centers on wearable computing, human-computer interaction, and sensor networks applied to health monitoring, activity recognition, and physiological signal analysis. Notable projects include BiHeartS (bilateral heart rate monitoring) and studies on sleep quality using wearable devices. Key achievements include being ranked among the World’s top 2% of Scientists (2022) and securing grants for projects like XAI-FinCrime. She advises on PhD and postdoc positions, such as the 2025 Innosuisse-funded project in explainable AI for financial crime detection. Labs/Teams: People-Centered Computing Group (USI), collaborating on cross-disciplinary projects in pervasive computing and healthcare technology.

• Wearable Computing
• Human-Computer Interaction
• Machine Learning
• +3 more

Kaiyu Hang is an Assistant Professor of Computer Science at Rice University, directing the Robotics and Physical Interactions Lab (RobotΠ Lab). He holds a PhD and MSc from KTH Royal Institute of Technology and a B.Eng. from Xi’an Jiaotong University. His postdoctoral research was conducted at Yale University. His research focuses on robotic systems capable of physically interacting with the environment and humans, emphasizing algorithms in optimization, learning, and control. Key areas include manipulation systems (small-scale grasping to large-scale multi-robot manipulation), robust control, and energy-efficient UAV perching mechanisms inspired by nature. His work has been featured in MIT Technology Review, Science Robotics, and NPR. Hang has received notable awards such as the NSF CAREER Award (2023) and ASME Rising Star (2024). He serves on editorial boards for IEEE Robotics and Automation Letters (2019–present), ICRA (2021–present), IROS (2020–present), and Humanoids (2019). He also organizes the 10th Robotic Grasping and Manipulation Competition (RGMC) at ICRA 2024. As a faculty advisor for the Rice Robotics Club and on the CS Graduate Admission Committee, Hang actively mentors students and promotes inclusivity in robotics through initiatives like Inclusion@RSS. His lab’s projects aim to enhance manipulation robustness, develop novel UAV landing gear, and advance nonprehensile manipulation via motion planning and control.

• Robotics
• Robotic Manipulation
• Physical Interactions
• +5 more

Professor Pietro Valdastri is a Full Professor and Chair in Robotics & Autonomous Systems at the University of Leeds. He directs the Science and Technologies Of Robotics in Medicine (STORM) Lab, the Institute of Robotics, Autonomous Systems and Sensing (IRASS), and the Robotics at Leeds network. His expertise spans surgical robotics, robotic endoscopy, and magnetic manipulation, with a focus on developing soft magnetic surgical robots (SMSRs) for minimally invasive medical procedures. Valdastri holds a Laurea in Electronic Engineering (University of Pisa, 2001) and a PhD in Biomedical Engineering (Scuola Superiore Sant’Anna, 2006). He previously served as Assistant Professor at Scuola Superiore Sant’Anna (2006–2011) and Vanderbilt University (2011–2016) before joining Leeds in 2016. His research aims to leverage magnetic actuation for surgical navigation, with applications in cancer therapy and endoscopy. Key awards include the NSF CAREER Award (2015), ERC Consolidator Grant (2019), and KUKA Innovation Award (2019). He is a Royal Society Wolfson Research Fellow, IEEE Fellow, and editor for IEEE Robotics and Automation Letters. His work has been featured in major media outlets like the BBC, New Scientist, and WIRED. Valdastri has secured over £25M in grants from NSF, NIH, ERC, EU-H2020, and industry partnerships. He co-founded WinMedical srl (acquired in 2017) and Atlas Endoscopy Limited, advancing robotic colonoscopy platforms. Current research emphasizes autonomous robotic systems, magnetic tentacles for lung therapy, and patient-specific surgical tools.

• Surgical Robotics
• Robotic Endoscopy
• Medical Robotics
• +5 more

Timo Oksanen is a Visiting Professor at Aalto University's Department of Electrical Engineering and Automation. His research focuses on agricultural automation, robotics, and control systems, with a strong emphasis on ISO 11783 vehicle network standards and autonomous systems. He collaborates with industry partners to develop next-generation agricultural machinery solutions, including automated guidance systems, sensor integration, and cybersecurity protocols. Oksanen leads the Autonomous Systems research group and has authored over 100 publications since 2009. Key research areas include precision agriculture technologies, machine learning applications in farming, and the integration of OPC UA with agricultural communication standards. Recent work addresses challenges in autonomous vehicle navigation, dust-resistant vision systems, and safety-critical perception architectures for automated field operations. Notable projects include the AGRIX initiative for ISOBUS-compatible implements and the development of a next-generation task controller using OPC Unified Architecture. Oksanen has also contributed to international standards for tractor-implement communication and four-wheel steering systems. His work bridges academic research with industrial applications, addressing both technical innovations (e.g., LIDAR-based object detection) and operational efficiency improvements in farm machinery fleets.

• Agricultural Automation
• Robotics
• Control Systems
• +5 more

Prof. Michael Schneider is Universitätsprofessor and Chair of Computational Logistics at RWTH Aachen University since 2016. Previously, he held positions at TU Darmstadt (2013-2016) and earned his doctoral degree from TU Kaiserslautern (2012). His research focuses on logistics optimization, including transportation routing, warehouse management, and metaheuristic methods for solving complex operational challenges. He leads the Global Challenges Lab and serves as communication chair of VeRoLog (EURO's vehicle routing group). Research interests include: quantitative modeling for supply chains, heuristic/exact optimization methods, electric vehicle routing, territory design, and production planning. Notable achievements include the INFORMS Journal on Computing Meritorious Paper Award (2021) and editorial roles in journals like Applied Mathematical Modelling. Publications span topics like vehicle routing with time windows, electric logistics networks, and warehouse automation strategies. His work integrates advanced algorithms with real-world industry applications (e.g., DHL, Picnic). The Computational Logistics group collaborates on projects addressing sustainability, autonomous systems, and modern warehousing challenges. Education: Business Admin & Computer Science (University of Mannheim), PhD (TU Kaiserslautern) Professional Roles: VeRoLog Communication Chair, EURO Working Group Key Projects: Electric vehicle routing optimization, warehouse automation, and sustainable logistics networks

• Logistics Optimization
• Transportation Planning
• Operations Research
• +3 more

Dr. Antoine Cully is the director of the Adaptive and Intelligent Robotics Lab at Imperial College London. He previously served as a Research Associate in the Personal Robotics Lab (2016–present) and earned his PhD in Robotics and Artificial Intelligence from UPMC (Paris), focusing on algorithms enabling robots to adapt to mechanical damage swiftly. His work has been internationally recognized, including a Nature cover publication and awards for his PhD thesis. His research interests span evolutionary robotics, stochastic optimization, and quality-diversity algorithms, with current projects involving the EU H2020 'PAL' initiative to develop adaptive robotics for user preferences. Education: M.Sc. in Intelligent Systems and Robotics (UPMC, 2012), Engineer degree in Robotics (Polytech-Paris UPMC, 2012), PhD in Robotics and AI (UPMC, 2015). Research emphasizes adaptive robotics, damage recovery, and autonomous learning. Notable contributions include the T-Resilience algorithm and MAP-Elites optimization framework. Awards include the 'Outstanding Paper 2015' and 'Best Thesis' accolades. His lab focuses on advancing AI-driven robotics for real-world applications.

• Robotics
• Artificial Intelligence
• Evolutionary Robotics
• +3 more

Professor Javid Taheri is a leading academic at Karlstad University (2019–present), previously serving as Associate Professor (2015–2019) and Senior Lecturer (2015). His research focuses on cloud computing, edge computing, distributed systems, and AI-driven networking. He holds a Ph.D. in Information Technologies from The University of Sydney (2007) and an M.Sc./B.Sc. in Electrical Engineering from Sharif University of Technology (2000/1998). Research interests include cloud-edge continuum systems , resource optimization , 5G/6G networking , and AI for IoT . Notable contributions include frameworks like PerfSim (microservice performance simulation) and MultiScaler (auto-scaling for cloud applications). Publications highlight innovations in edge computing optimization, security for distributed systems, and machine learning for resource management. He has co-authored over 150 papers across top venues like IEEE Transactions and ACM conferences. Academic leadership includes roles as conference chair (IC2E 2023) and editorial work for journals on cloud and edge computing.

• Cloud Computing
• Distributed Computing
• Parallel Computing
• +10 more

Sajib Chakraborty is a Researcher at the MOBI - Electromobility Research Centre and the Department of Electrical Engineering and Power Electronics. His research focuses on condition monitoring, reliability assessment of power electronic systems, and advanced battery management systems (BMS). He has contributed to projects like HARPOONERS and FLEXMCS, aiming to optimize electric powertrain systems and vehicle-to-grid technologies. His work spans over 80 research outputs since 2018, with a strong emphasis on multi-objective optimization, physics-of-failure modeling, and digital twin technologies for electric vehicles. Collaborations include institutions in Europe and beyond, addressing challenges in renewable energy integration and high-voltage electric mobility. Advised 5 Master's theses on topics like DC-DC converter design and SiC MOSFET reliability. Active in editorial roles for IEEE Transactions on Transportation Electrification . Led projects funded by EU grants, totaling € multi-million investments. Key research themes include battery thermal management, EV charging infrastructure, and multi-physics modeling for power electronics reliability.

• Power Electronics
• Electric Vehicles
• Battery Management Systems (BMS)
• +3 more

Zhiyi Huang is an Associate Professor of Computer Science at the University of Hong Kong, leading the Computer Science Division within the School of Computing and Data Science. He holds a PhD from the University of Pennsylvania (2013) and completed a postdoctoral fellowship at Stanford University (2013–2014). His research focuses on Theoretical Computer Science, Algorithmic Game Theory, Online Algorithms, and Differential Privacy, with notable contributions to Machine Learning and Computer Networks. Education: PhD in Computer and Information Science, University of Pennsylvania (2013) Postdoctoral Researcher, Stanford University (2013–2014) Bachelor's Degree from the Yao Class at Tsinghua University (2008) Research interests span foundational areas including algorithmic game theory, online optimization, and privacy-preserving mechanisms. He has pioneered work on revenue maximization in single-parameter settings and developed novel frameworks for analyzing price of anarchy in game theory. Key Awards: Early Career Award (Research Grant Council of Hong Kong, 2014) Best Paper Award at ACM Symposium on Parallelism in Algorithms and Architectures (SPAA 2015) Morris and Dorothy Rubinoff Dissertation Award (2013) Simons Graduate Fellowship in Theoretical Computer Science (2012–2013) Recent grants include studies on algorithmic foundations of Bayesian mechanism design (HK$675,647), online primal dual techniques (HK$496,028), and privacy-preserving mechanisms (HK$931,737). His work bridges theoretical advancements with practical applications in healthcare, autonomous systems, and cybersecurity. Notable Projects: Medical predictive systems for acute cardiopulmonary events AI-driven maritime navigation using AIS data Secure federated learning frameworks with blockchain

• Theoretical Computer Science
• Algorithmic Game Theory
• Online Algorithms
• +3 more

Dr. Ahmed Mohammed is an Associate Professor in Supply Chain Management and Programme Director for the MSc Supply Chain Management at the University of Birmingham, Dubai Campus. He is affiliated with the Management Department and brings over 13 years of combined academic and industrial experience from the UK and the Middle East. Educational Background: Ph.D. in Engineering, University of Portsmouth, UK (2017) MSc in Communication Network Planning and Management, University of Portsmouth, UK (2010) Lean Six Sigma – Black Belt (2022) Fellow, Higher Education Academy, UK (2022) Dr. Mohammed's research focuses on the modeling and optimization of supply chains with an emphasis on sustainability and resilience. His work spans areas such as multi-tier supplier selection, circular economy, food waste management, Industry 4.0 integration, and last-mile logistics. He employs advanced methodologies including multi-criteria decision-making (MCDM) techniques like AHP, TOPSIS, and VIKOR, and develops hybrid optimization models for complex supply chain challenges. His recent publications, spanning from 2021 to 2023, reflect a strong trend in resilient and sustainable supply chain network design, pandemic-related disruptions, digital sourcing, and risk modeling under uncertainty. These works appear in high-impact journals such as International Journal of Production Research , Transportation Research Part E , Computers & Industrial Engineering , and Expert Systems with Applications . Scientific Awards and Recognitions: Fellow, Higher Education Academy, UK (2022) Lean Six Sigma Black Belt (2022) Fellow Member, Chartered Institute of Logistics and Transport (CILT) Member, MCDM Society Dr. Mohammed has secured multiple research grants from MOHERI, Oman, including projects on last-mile logistics sustainability, supply chain resilience, and online food waste management. He actively supervises research students and serves as a reviewer for leading journals including International Journal of Production Economics (IJPE) , Transportation Research Part D (TRD) , Omega , and International Journal of Production Research (IJPR) . He is also an external academic program reviewer for logistics-related programs and contributes to the academic community through peer review and collaborative research.

• Sustainable and Resilient Supply Chain Management
• Supply Chain Network Design
• Multi-objective Optimization
• +11 more

Styliana Avraamidou is an Assistant Professor in the Department of Chemical and Biological Engineering at the University of Wisconsin-Madison. She leads research in Process Systems Engineering, focusing on expanding Circular Economy supply chains through mathematical optimization and control. Education: PhD (2018, Imperial College), MEng (2014, Imperial College) Her research interests span Mathematical Optimization and Control , Circular Economy Systems Engineering , Energy Systems Engineering , and the Food-Energy-Water Nexus , with applications in sustainable industrial processes and smart manufacturing. Her recent publications highlight trends in bilevel optimization , distributed model predictive control , and circular economy frameworks for plastic recycling and energy systems. These works integrate data-driven models and multi-parametric programming to address industrial challenges. Scientific Awards: 2024 AIChE’s Institute for Sustainability Managing Board Member 2023 iSoGO Young Researcher Award 2022 Bluemke Assistant Professorship 2022 Faculty Sustainability Fellowship Multiple AIChE and Elsevier awards (2016–2020) Avraamidou teaches graduate courses in process optimization, including CBE 750 (Advanced Process Synthesis) and CBE 470 (Process Dynamics), while mentoring research on sustainable chemical systems.

• Mathematical Optimization
• Process Systems Engineering
• Circular Economy Systems Engineering
• +4 more

Reza Zadeh is a Computational Mathematics professor at Stanford University's School of Engineering and Founder & CEO of Matroid . He previously served as a Technical Advisory Board member for Databricks and leads the Spark Tutorial at Stanford. Research Interests: Specializing in Machine Learning and Distributed Computing , his work bridges theoretical mathematics with practical implementations in big data systems. Key focus areas include Optimization of Apache Spark 3D Convolutional Neural Networks Discrete Mathematics and Graph Theory Medical Imaging Applications Academic Contributions: His publications reveal trends across multiple disciplines: Adapting machine learning for medical diagnostics (2019-2022) Advancing distributed computing frameworks (2014-2016) Developing mathematical foundations for social networks (2009-2013) Creating scalable optimization algorithms (2014-2016) Scientific Awards: Best Paper Award runner-up at KDD 2016 Academic Leadership: He has taught SMACC Consulting and designed courses including CME 323: Distributed Algorithms and Optimization (2015-2024) and CME 305: Discrete Mathematics and Algorithms (2010-2017). His lectures cover graph theory, approximation algorithms, and spectral sparsification. Labs & Teams: Organized Spark Summit workshops and leads Scaled Machine Learning Conference . Collaborates with Stanford's ICME computational consulting services.

• Machine Learning
• Distributed Computing
• Discrete Mathematics
• +7 more