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Wangzhong MuView profile

Senior Lecturer

• Sustainable Metallurgy
• Microstructure Physics
• Alloy Design
• +3 more

Prof. Wangzhong Mu is a Senior Lecturer (Docent) in the Department of Materials Science and Engineering at KTH Royal Institute of Technology, Stockholm. His research focuses on sustainable metallurgy, microstructure physics, and alloy design. He leads the thermo-physical property analysis section in the Hultgren Lab and is affiliated with Digital Futures at KTH. Educations: PhD in Materials Science, KTH Royal Institute of Technology (2015) MSc/Bachelor's in Materials Science, Northeastern University, China Research Interests: Inclusion engineering and microstructure-property correlations in steels High-entropy alloy design using digital tools (AI/thermodynamic modeling) In-situ characterization via confocal microscopy and multiscale analysis Recycling-oriented steel production and CO2 reduction strategies Grants/Projects (selected): SSF Strategic Mobility Grant (2023-2024): Clean steel for sustainable future VINNOVA Mobility Grant (2022-2024): Hydrogen-based metallurgy STINT Project (2022-2023): Inclusion engineering for green steel EIT RawMaterials (ENDUREIT, 2019-2021): Durable steels at intermediate temperatures Labs/Teams: Hultgren Lab (materials characterization), Digital Futures (AI-driven metallurgy), and international collaborations with Hanyang University (South Korea), IIT Bombay (India), and Tohoku University (Japan).

Pekka PeljoView profile

Associate Professor

• Electrochemistry
• Energy Storage
• Flow Batteries
• +5 more

Pekka Peljo is an Associate Professor at Aalto University's Department of Chemistry and Materials Science, leading the Physical Electrochemistry and Electrochemical Physics (PhysElectrochemPhys) research group since September 2018. His work focuses on charge transfer mechanisms at solid-liquid interfaces and within solid materials, with a strong emphasis on developing advanced batteries for large-scale energy storage. Education: Master's degree in Engineering and Technology from Helsinki University of Technology His research bridges Electrochemistry and Energy Storage , particularly in Redox Flow Batteries and Hydrogen Production via hydrocarbon electrolysis. Current projects include computational modeling of redox potentials, experimental flow battery designs, and scalable synthesis of cellulose nanocrystals for electrochemical applications. Selected trends from his 75+ publications include Electron Transfer at interfaces, Operando Battery Monitoring , and Sustainable Energy solutions. His work aligns with UN Sustainable Development Goals (SDGs) for climate action and affordable clean energy. Scientific contributions are recognized through grants from the Academy of Finland, EU Horizon Europe, and strategic funding for projects like CompBat (2020-2023) and H2fromHE (2024-2028). He has presented at international conferences (e.g., ELCAT, Spain, 2011) and hosted collaborations with institutions like EPFL. As Principal Investigator, Peljo leads projects such as PREDICTOR (2024-2028) for high-throughput screening of battery materials and Bi3BoostFlowBat (2025-2026). His group also investigates Hydrogen Production from natural gas and Vitamin B6-based Electrolytes for aqueous batteries.

• Electronic Engineering
• Mechatronics and Robotics
• Human-Robot Interaction
• +7 more

Roya Haratian serves as Principal Academic (equivalent to Associate Professor) in Electronic Science and Engineering at Bournemouth University's Department of Design and Engineering within the Faculty of Science and Technology. As Deputy Head of Department and Athena SWAN lead, she spearheaded the department's successful Bronze Award in 2021 for gender equality initiatives. Her leadership extends to curriculum development in Mechatronics and Robotics programs across undergraduate and postgraduate levels. Her academic credentials include a BSc (First Class Honours) and MSc (Distinction) in Electrical and Electronic Engineering, followed by a PhD in Electronic Engineering from Queen Mary University of London (2014). Prior to her current role, she worked as an Associate Lecturer at QMUL and Research Associate at Bristol Robotics Lab, focusing on on-body sensing systems and bio-signal processing for human-machine collaboration. Haratian's research centers on electronic engineering applications in human-robot interaction, with particular emphasis on on-body sensing technologies, signal processing, and machine learning. Her work bridges theoretical innovation with industrial implementation, developing assistive technologies for healthcare and safety-critical systems. Recent projects address diabetic foot ulcer prevention, emotion recognition in VR, and human-machine collaboration safety protocols, demonstrating strong translational impact across medical and industrial domains. Analysis of her 15 most recent publications reveals a strategic progression from foundational signal processing techniques toward integrated human-machine systems. Her work increasingly incorporates game theory for resource allocation, AI-driven predictive modeling, and inclusive design principles, with growing emphasis on real-world implementation challenges and ethical considerations in assistive technologies. Key recognitions include: Athena SWAN Bronze Award (Advance HE, 2021) for departmental gender equality leadership Senior Fellowship of Higher Education Academy (2021) BU Doctoral College Outstanding Contribution Award (2025) Design Review Award from Institute of Mechanical Engineering (2023) Student Experience 'You are Brilliant' Award (2017) As Recognised Research Supervisor (UK Council for Graduate Education), she currently co-supervises five PhD students on topics including AI surveillance, biomechatronics, and digital twin simulation. Her £1.2M+ research portfolio features strategic partnerships with Zimmer-Biomet, Computational Mechanics Wessex Institute, and Daido Industrial Bearing, with recent grants including HEIF-funded AI emotion recognition systems (2025) and QR-funded human-machine safety protocols (2024). She actively mentors through AdvanceHE's Aurora program and leads BU's Inclusivity Curriculum Evaluation project. Haratian directs the department's Athena SWAN initiative and collaborates with the Royal Institute on STEM outreach, designing bioelectronic masterclasses for GCSE students. Her public engagement includes 'Café Scientifique' discussions on machine emotion recognition and keynote addresses at Brockenhurst STEM Awards, focusing on translating on-body sensing research into real-world health applications.

Hwan ChoiView profile

Assistant Professor

• Prosthetic Devices
• Exoskeletal Systems
• Musculoskeletal Analysis
• +3 more

Dr. Hwan Choi is an Assistant Professor at the University of Central Florida (UCF), affiliated with the College of Engineering. He leads the Rehabilitation Engineering and Assistive Device Lab, focusing on advancing prosthetic and exoskeletal technologies to enhance mobility for individuals with disabilities. His work integrates biomechanical analysis, neural control strategies, and assistive device design to address challenges in rehabilitation engineering. Education: Dr. Choi earned his Ph.D. in Engineering from the University of Washington (2016), a Master of Engineering (2006), and a Bachelor of Engineering (2004) from Korea University. He completed a Postdoctoral Research Fellowship at the University of Michigan in 2018. Research Interests: His studies prioritize prosthetic device optimization, exoskeleton system development, musculoskeletal modeling, and neural control mechanisms. He investigates how biomechanical insights can improve device performance and user adaptation, with applications in transtibial amputee mobility, cerebral palsy gait correction, and aging-related mobility issues. Article Trends: Recent work emphasizes multimodal data integration (e.g., IMU sensors, sEMG), adaptive prosthetic systems, and machine learning for gait analysis. Key themes include improving clinical outcomes through smart technologies and addressing unmet needs in orthotic/prosthetic design. Awards: Gatzert Child Welfare Fellowship (2016), Travel Grant from Gait and Clinical Movement Analysis Society (2016), University of Washington Research Assistant Scholarship (2011–2016), Louis and Katherine Marsh Memorial Fellowship (2012). Advising & Grants: While specific advisees are not listed, Dr. Choi’s lab actively engages in collaborative projects, with funding support from scholarships and institutional grants. His research bridges academic and clinical settings, emphasizing translational outcomes. Labs/Teams: The Rehabilitation Engineering and Assistive Device Lab focuses on developing innovative solutions for mobility impairments, including smart adaptive prosthetic sockets and variable-stiffness orthoses. Current projects explore machine learning-driven gait analysis and self-sanitizing medical devices.

• Human-Computer Interaction (HCI)
• Multimodal Interaction
• Visual Analytics
• +5 more

Denis Lalanne is a full Professor in the Department of Informatics at the University of Fribourg, leading the 'human-building interaction' group at the Smart Living Lab and directing the Human-IST institute . He specializes in Human-Computer Interaction (HCI), focusing on multimodal interaction, visual analytics, and Human-Building Interaction (HBI). His work bridges computer science with architecture and urban design to improve building occupants' comfort and accessibility. His research spans topics such as assistive technologies for visually impaired individuals, energy-efficient lighting systems, and predictive models for indoor environmental quality. He has led projects like the Human-IST Lab and SWICE (Sustainable Well-being in Energy Transition), emphasizing interdisciplinary collaboration between academia, industry, and public institutions. Key contributions include the development of frameworks for human-centric lighting, wearable sensors for urban comfort analysis, and empathic systems to enhance HCI. His work is published in top venues like ACM Transactions on Accessible Computing , IEEE , and CHI . Education and career highlights include a PhD from EPFL (Swiss Federal Institute of Technology), postdoctoral research at IBM’s USER Group, and prior teaching roles at the University of Avignon. He is a Swiss representative at IFIP TC13 and has organized major conferences like IHM 2016.

Tarunraj SinghView profile

Professor

• Target tracking
• Human-vehicle control
• Optimal control
• +7 more

Tarunraj Singh is a Professor in the Department of Mechanical and Aerospace Engineering at the University at Buffalo, part of the School of Engineering and Applied Sciences. His research focuses on control systems, robotics, and dynamics, with emphasis on target tracking, optimal control, and vibration mitigation in complex systems. He holds a PhD from the University of Waterloo (1991) and earlier degrees from Indian educational institutions. His work integrates advanced mathematical techniques like polynomial chaos expansions and differential flatness with practical applications in aerospace, robotics, and biomedical engineering. Education : PhD, Mechanical Engineering, University of Waterloo, 1991 ME, Mechanical Engineering, Indian Institute of Science, 1988 BE, Mechanical Engineering, Bangalore University, 1986 Research Interests : Dr. Singh specializes in developing robust control strategies for nonlinear systems, with notable contributions to: Reference shaping for precision motion control Uncertainty quantification in dynamical systems Vibration suppression in robotic systems Bioengineering applications including blood glucose control for diabetics Space systems and tethered satellite dynamics His lab focuses on bridging theoretical advancements with real-world implementation through experiments involving UAVs, robotic manipulators, and biomedical devices. Research Trends : Recent work emphasizes energy-efficient trajectory planning, probabilistic control under uncertainty, and real-time sensor integration. His publications (2020–2025) consistently address challenges in optimal control with practical applications across robotics, aerospace, and biomedical systems. Lab Activities : Directs the Control, Dynamics and Estimation Laboratory, which develops novel algorithms for motion control, system identification, and safety-critical applications. Current projects include UAV payload stabilization, autonomous vehicle navigation, and smart agricultural robotics.

Alagan AnpalaganView profile

Professor

• Wireless Communication
• Radio Resource Management
• Green Communication
• +7 more

Alagan Anpalagan is a Full Professor in the ELCE Department at Toronto Metropolitan University, previously Ryerson University. He holds a PhD in Electrical Engineering from the University of Toronto. His research focuses on radio resource management (RRM), green communication, IoT networks, and wireless communication systems. He directs the WINCORE Lab, specializing in radio access & networking (RAN) and cross-layer design. Dr. Anpalagan has authored/co-edited multiple books and holds IEEE Fellow status (2024). He has received awards including the Ryerson Sarwan Sahota Distinguished Scholar Award (2022) and the IEEE Canada Outstanding Engineering Educator Medal (2018). He has served in editorial roles for IEEE Communications Surveys & Tutorials and led industry collaborations with companies like Bell Mobility and IBM. Education: B.A.Sc. in Electrical Engineering, University of Toronto M.A.Sc. in Electrical Engineering, University of Toronto Ph.D. in Electrical Engineering, University of Toronto Research Interests: His work spans RRM, energy-efficient networks, cognitive communication, and smart grid technologies. Recent projects include digital twin applications in IoT and 6G-based user localization for emergencies. Publications: His 15 most recent articles include studies on network routing protocols, IoT scheduling with digital twins, and AI-driven disaster response systems. These reflect his focus on integrating AI and edge computing into next-gen communication systems. Awards: Recognized for both research and teaching excellence, including IEEE Fellowships and institutional awards for graduate education and service. Labs/Teams: Lead researcher at the WINCORE Lab, collaborating with academia and industry on wireless resource management and heterogeneous networks. The lab’s alumni network includes over 100 researchers.

Yang LiView profile

Assistant Professor

• Computer Architecture
• Machine Learning
• On-Device AI
• +4 more

Yang Li is an Assistant Professor of Computer Science at Iowa State University, specializing in computer architecture, machine learning, and their intersection. He holds a Ph.D. and M.S. from Carnegie Mellon University (2020), an M.S.E. from the University of Texas at Austin (2013), and a B.E. from Tsinghua University (2011). Prior to academia, he worked as a Senior Research Scientist at Meta, a Research Scientist at Meta, and a Researcher at Microsoft. His research focuses on large language models (LLM) acceleration, on-device AI, cloud infrastructure optimization, and spatiotemporal forecasting. He has contributed to over 20 peer-reviewed publications at top venues like ASPLOS, EMNLP, and ICASSP. Research Interests: Algorithmic and systems-level acceleration of LLMs On-device AI co-design and privacy Cloud memory/power management Graph-based spatiotemporal forecasting Teaching: Taught COMS 6730 (Advanced Topics in ML), COM S 321 (Computer Architecture), and guest-lectured on graph signal processing. Recent teaching scores include 4.75/5.0 (Fall 2024) and 4.67/5.0 (Spring 2025). Awards: IBM Patent Application Award (2021) and multiple patents on power management systems for data centers. Service: Program committee member for DAC 2024, NeurIPS 2024, and ICLR 2025. Reviewer for ACM TACO, IEEE TPAMI, TPDS, and others.

• Service-Oriented Architectures
• Cloud Computing
• Data Management
• +7 more

Professor Kyriazis Dimosthenis holds a faculty position at the Department of Digital Systems, University of Piraeus. He earned his diploma in Electrical & Computer Engineering from the National Technical University of Athens (2001) and a cross-disciplinary MSc in Techno-Economic Systems (2004). His academic rank is Professor specializing in service-oriented architectures with a focus on quality of service and workflow management. He has led European projects like BigDataStack, CrowdHEALTH, and CYBELE, addressing challenges in cloud computing, edge computing, and AI-driven solutions for healthcare, finance, and industrial sectors. His research emphasizes resilient service-oriented systems, AI explainability, and human-centric digital transformation. Notable contributions include frameworks for dynamic resource allocation in hybrid cloud/edge environments, AI applications for maritime safety, and data governance solutions for cross-sector integration. He coordinates initiatives such as the Future Internet Architecture Board and Cloud QoS&SLAs, driving advancements in federated data marketplaces and sustainable computing practices. His recent work explores Large Language Model (LLM) applications in financial decision-making, conversational AI for MLOps, and neurosymbolic systems for defect detection. He also investigates XAI methodologies, including VirtualXAI, which leverages GPT-generated personas for explainability assessment. His projects often bridge technical innovation with societal impact, such as the iHELP platform for holistic health records and SmartCHANGE for behavioral change strategies in youth health. Key themes in his publications include bias mitigation in machine learning, dynamic deployment prediction in hybrid cloud settings, and energy-efficient data spaces for mobility. He has contributed to standards like the H2020-funded IRMOS and 5GTANGO, emphasizing interoperability and fault-tolerant architectures. His work frequently intersects with EU policy frameworks, particularly in data governance and ethical AI implementation.

• Parallel and Distributed Computing
• Database Systems
• Network-Centric Computing
• +2 more

Professor Ajit Singh is a faculty member in the Department of Electrical and Computer Engineering at the University of Waterloo , affiliated with the Faculty of Engineering . His expertise spans Parallel and Distributed Computing , Database Systems , Network-Centric Computing , and Software Architecture and Design . Education: BSc (BIT, India) MPhil (Jawaharlal Nehru University, New Delhi) MSc and PhD (University of Alberta) Research & Industrial Work: Founded SlipStream Data (acquired by Research in Motion/BlackBerry) to accelerate internet content delivery on low-bandwidth networks. Consulted for IBM Canada, Bell Canada, Nortel, and other tech firms. Current projects include Energy Efficient Mobile Computing and Processing Data Streams . Advising & Students: Current advisees: Liton Chakraborty, Mohammad Mursalin Akon, Rajesh Palit, Tan Wang. Past students include Dhrubajyoti Goswami, Afzal Mawji, and others. Research Themes: Focuses on scalable caching, distributed systems, and energy-efficient computing. Explores disk-based optimization for stream joins and parallel architectures.

• Information Systems Engineering
• Logic and Computation
• Smart Grids
• +3 more

Prof. Sandford Bessler is affiliated with the Technische Universität Wien's Faculty of Informatics, specifically within the Compilers and Languages department. His research focuses 75% on Information Systems Engineering and 25% on Logic and Computation. He teaches courses such as Bachelor Thesis for Informatics and Business Informatics . His work emphasizes smart grids, electric vehicle management, scheduling algorithms, and distributed systems. Research interests include optimizing energy networks, resilience in power grids, and integrating renewable energy systems. He has contributed to projects like ARTE (2012–2017) , exploring disruption-tolerant vehicle-infrastructure communication. Supervised theses include Electric vehicles recharge scheduling with time windows and A service overlay network for telematic applications . Key projects involve improving grid resilience through demand-side management and collaborative frameworks. He collaborates with industry and academia on smart grid technologies and electric vehicle infrastructure.

Josep CasanovasView profile

Professor

• Modelling and Simulation
• Internet and Information Systems
• Urban Mobility
• +4 more

Josep Casanovas is a Full Professor at the Statistics and Operations Research Department of the Technical University of Catalonia (UPC), affiliated with the Barcelona School of Informatics. He previously served as head of inLab FIB (2012-2020) and as dean (1998-2004) and vice-rector (2006-2011) of UPC, leading strategic initiatives in university governance and ICT policies. His research focuses on Modelling and Simulation , Internet and Information Systems , and Urban Mobility . He has led projects for the European Union, including C-ROADS Spain, REMEDiAL, and ECHORD++, addressing intelligent transport, software automation, and robotic innovation. Recent publications highlight his work on agent-based simulation for urban health, deep learning applications in traffic and energy savings, and wildfire management tools . He co-directs LogiSim and coordinates the Severo Ochoa Research Excellence Program at the Barcelona Supercomputing Center (BSC-CNS).

Yucheng XieView profile

Assistant Professor

• Security in Machine Learning
• Smart and Mobile Healthcare
• Mobile Computing and Sensing
• +3 more

Yucheng Xie is a Tenure-track Assistant Professor in the Graduate Department of Computer Science and Engineering at Yeshiva University, affiliated with the Katz School of Science and Health. He holds a Ph.D. in Electrical and Computer Engineering from Purdue University and a Master’s in Computer Science from Stevens Institute of Technology. His research focuses on Security in Machine Learning/AI Systems , Smart and Mobile Healthcare , and Mobile Computing and Sensing . Notable contributions include non-invasive wireless sensing via mmWave and Wi-Fi signals for health monitoring, adversarial attacks on activity recognition systems, and secure mobile deep learning. His recent articles explore topics like contactless human concentration monitoring, palm-based authentication, and environment-invariant eating behavior tracking. These works highlight innovations in mmWave technology, cybersecurity for AI systems, and healthcare applications. Awards : Best Paper Runner-up (IEEE Conference on Communications and Network Security, 2024) Best Paper Runner-up (IEEE International Conference on Computer Communications and Networks, 2022) Best Paper Award (EAI International Conference on IoT Technologies for HealthCare, 2019) While no advising or grant details are provided, his work emphasizes practical applications of wireless sensing and secure AI systems. No specific lab affiliations are mentioned, though his research often involves interdisciplinary collaboration.

• Data Privacy
• Cyber Security
• Cloud Security
• +5 more

Professor Xun Yi is a faculty member at RMIT University's School of Computing Technologies, specializing in cybersecurity, data privacy, and distributed computing. His research focuses on privacy-preserving technologies in cloud systems, blockchain applications, federated learning, and secure communication protocols. He has published over 150 papers in top-tier journals and conferences, including IEEE Transactions on Dependable and Secure Computing. Since 2014, he has served as an Associate Editor for the IEEE Transactions on Dependable and Secure Computing, and has organized major events like the Australasian Information Security Conference (AISC) in 2015 and 2016. Professor Yi actively supervises PhD and Master's research projects, focusing on topics like secure IoT systems, privacy-aware machine learning, and blockchain-enabled frameworks. His work emphasizes practical solutions for real-world challenges in data security and privacy. Research Interests: Data Privacy, Cyber Security, Cloud Security, Wireless/Mobile Security, Applied Cryptography Blockchain-based Systems, Federated Learning, Privacy-Preserving AI Recent Contributions: Developed frameworks for secure data aggregation in smart grids and healthcare systems Advanced techniques for privacy-preserving federated learning and graph neural networks Contributed to standards for secure authentication in vehicular networks (VANETs) Supervision: Open to mentoring students in cybersecurity, privacy-enhancing technologies, and IoT security.

Mario Di FrancescoView profile

Professor

• Wireless Networking
• Mobile and Ubiquitous Computing
• Internet of Things
• +4 more

Mario Di Francesco is a Professor at the Department of Computer Science, Aalto University. He holds the position of Professor in Computing Systems (ComputingSystems) Research Area and leads multiple research projects in networking and IoT. Previously, he was a research associate and adjunct faculty at the University of Texas at Arlington (2012–2014), and completed his PhD in Information Engineering at the University of Pisa under Prof. Giuseppe Anastasi. He also served as a research fellow at Scuola Superiore Sant'Anna in 2009. Research Interests : His work focuses on wireless networking, mobile and ubiquitous computing, and the Internet of Things (IoT). Key areas include edge computing, fog networks, virtual/augmented reality, and AI-driven resource management. His research contributes to UN Sustainable Development Goals related to innovation and infrastructure (SDG 9), sustainable cities (SDG 11), and industry/infrastructure development (SDG 9). Publications : His recent work spans topics like private virtual reality conversations, cloud-based network measurement frameworks (CLAIM), microservice connectivity analysis, and edge-DNN optimization. These publications reflect a trend toward integrating AI with distributed systems for real-time, low-latency applications in IoT and edge computing. Awards : Recipient of the Google Internet of Things Technology Research Award (2016) and MobileHCI Honorable Mention (2020). Grants & Projects : CRUISE (2023–2025): Cross-system architecture for autonomous wireless networks using lifelong machine learning. MeXICO (2020–2024): Mobile cross-reality through immersive computing. ASPECT (2016–2018): Spectrum utilization for mobile video. Labs & Teams : Leads research groups focused on edge computing, IoT systems, and immersive technologies. Collaborates with international partners on projects like fog radio networks and autonomous system design.