Dr. Su Nguyen is a Senior Lecturer in AI and Analytics at RMIT University's Department of Accounting, Information Systems & Supply Chain, located at the City Campus in Australia. His research focuses on integrating artificial intelligence, analytics, and operations research to address challenges in sustainability, safety, and critical domains like healthcare and logistics. Key areas include transparent AI systems, simulation models for dynamic environments, and optimization algorithms for energy and transportation. His work emphasizes making AI systems accountable to mitigate risks such as discrimination and ensures fairness in autonomous decision-making. Collaborations span Australia, New Zealand, and the Asia Pacific region, promoting AI applications in industry. Supervised projects include topics like personalized care plans, workforce rostering optimization, and AI-driven solutions for supply chains and cyber-risk evaluation. Dr. Nguyen's research bridges theoretical advancements with practical industry engagement, aiming to enhance decision-making through advanced analytics and business optimization frameworks.
Mirsad Trobradović is an Associate Professor at the Faculty of Mechanical Engineering , University of Sarajevo , Bosnia and Herzegovina, where he conducts research and teaches in the broad domain of mechanical and automotive engineering. His office is located in room 523, and he welcomes consultations every working day by appointment. Education & Academic Standing: While the page does not detail his prior degrees, his current academic rank of docent (equivalent to Associate Professor) and the title doc. dr. indicate completion of a doctoral degree and fulfilment of all requirements for tenure-track advancement at the University of Sarajevo. Research Interests: Trobradović’s work centres on automotive engineering , electric mobility , additive manufacturing , polymer materials , 3D scanning technologies , and finite element analysis . He explores how electrification of transport affects national energy demands, investigates durability and failure mechanisms of 3D-printed polymer gears, and integrates advanced scanning techniques into furniture manufacturing processes. Additional interests include the biomechanical performance of medical fixation devices, emission reduction in diesel engines, and the mathematical modelling of dynamic systems. Publication Trends: Across more than 15 peer-reviewed articles and book chapters since 2005, Trobradović demonstrates a clear trajectory from foundational vehicle dynamics and alternative fuels toward cutting-edge topics such as electric-vehicle energy regeneration, 3D-printed component reliability, and digital transformation of manufacturing. His most recent 2025 contributions focus on quantifying the electrical-energy impact of vehicle electrification in Bosnia and Herzegovina and on assessing service life of additively manufactured polymer gears. Scientific Awards: No specific awards or distinctions are listed on the University of Sarajevo page. Advising & Projects: Although individual student names are not disclosed, Trobradović collaborates extensively with colleagues such as Adis Muminović, Nedim Pervan, and Vahidin Hadžiabdić, indicating active supervision of graduate researchers and participation in multi-institutional projects. Detailed project listings are absent, yet the breadth of co-authored works suggests ongoing grant activity. Laboratory & Teams: He carries out his investigations within the research environment of the Faculty of Mechanical Engineering, leveraging laboratories for automotive testing, additive manufacturing, and computer-aided engineering simulation.
Dr. Ki-Young Jeong is a Professor of Engineering Management in the College of Science and Engineering at the University of Houston-Clear Lake. He holds a Ph.D. in Industrial Engineering from Texas A&M University and an MBA from the University of Massachusetts. With over 10 years of industrial experience as a project lead, systems engineer, and consultant, he transitioned to academia to focus on research and teaching. Education: M.S. in Industrial Engineering, Texas A&M University Ph.D. in Industrial Engineering, Texas A&M University MBA, University of Massachusetts His research focuses on supply chain design & optimization , humanitarian logistics network design , discrete event simulation , and data envelopment analysis . He has published over 60 peer-reviewed articles, emphasizing applications in disaster relief logistics, emergency supply chains, and operational efficiency. His work combines advanced analytics with real-world challenges in manufacturing, project management, and crisis response. Awards: UHCL Distinguished Professorship in Computer Science and Engineering (2021-2022) Minnie Stevens Piper Teaching Award nominee (2010-2011) Dr. Jeong’s research has explored trade-offs in emergency logistics networks, integrating multi-objective programming and data envelopment analysis to improve decision-making. His recent work addresses disaster recovery center location-allocation, supply chain resilience, and financial ratio analysis in the oil and gas industry. He also investigates simulation-based training for project management and lean Six Sigma implementation. His research has been supported by institutions like NASA, focusing on practical solutions for complex systems. He advises students on topics combining technical skills with humanitarian and industrial applications.
Mats Erling Høvin is an Associate Professor at the University of Oslo's Department of Informatics, affiliated with the Robotics and Intelligent Systems (ROBIN) research group. His academic work focuses on generative design, CAD/CAM systems, rapid prototyping, and evolutionary robotics. Previously, he conducted significant research in Delta-Sigma noise shaping for analog-to-digital converters. Research Interests: Generative design methodologies for manufacturing Computer-Aided Design (CAD) and Computer-Aided Manufacturing (CAM) systems Rapid prototyping and additive manufacturing techniques Evolutionary algorithms applied to robotics and optimization problems Delta-Sigma modulation for analog/digital signal conversion Robotic locomotion and control systems His publications demonstrate a consistent focus on optimization techniques applied to robotics, signal processing, and manufacturing systems. Recent work explores physics-based simulations for medical robotics and generative design for structural optimization. Earlier contributions established foundations in evolutionary robotics, motion capture filtering, and analog circuit design. Høvin teaches courses including IN5590 and IN1080, and leads research in the ROBIN group focusing on intelligent systems development. His work bridges theoretical computer science with practical engineering applications in robotics and manufacturing.
Martin Escalona is a researcher at the Department of Telematics Engineering, School of Telecommunications Engineering at Polytechnic University of Catalonia . He is affiliated with the GRXCA research group focusing on wireless communication networks and the ISG-MAK group specializing in Information Security and Applied Cryptography. Researcher in Wi-Fi positioning systems and cellular network optimization Primary focus on IEEE 802.11mc (Wi-Fi RTT) and its applications Active contributor to accessibility tools and assistive technologies His recent publications (2021-2025) reveal expertise in RTT-based positioning, ranging error analysis, and protocol implementation for wireless networks. He received the Best Short Paper Award at the 2023 International ACM Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems. Scientific committee memberships include: International Conference on Control, Automation & Information Sciences International Conference on Computer Sciences, Networking and Information Security IEEE Wireless Communications and Networking Conference
Eleni Boumpa is a Researcher and Ph.D. candidate at the Department of Computer Science and Biomedical Informatics, University of Thessaly. She leads the AuDi-o-Mentia research team and is affiliated with the Intelligent Systems Laboratory. Her work focuses on assistive technologies for people with neurodegenerative diseases, smart environments, cyber-physical systems, and healthcare in consumer electronics. Education: BSc in Computer Science & Biomedical Informatics (2018), University of Thessaly Current Role: Ph.D. candidate since 2018, researching 'Ambient Assistive Systems in Smart Environments' Her research interests include developing smart systems for elderly care, gas leakage detection via TinyML, logistics optimization, and security in healthcare wearables. Her work is funded by the EPICS in IEEE program and has led to innovations like home assistive systems for dementia patients. Awards: 1st place in IEEE Mind the Gap 2017 (dementia assistive system) Finalist in Microsoft Imagine Cup 2017 3rd place at ECESCON 2017 (best business idea) Advising & Grants: As team leader of AuDi-o-Mentia, she coordinates interdisciplinary research on memory aids for neurodegenerative diseases. Her projects integrate acoustic-based systems, tinyML, and sensor networks into assistive technologies. Labs & Teams: Member of the Intelligent Systems Laboratory and founder of the AuDi-o-Mentia team, focusing on dementia care technologies.
Vera Hemmelmayr is an Associate Professor at the Institute for Transport and Logistics Management, School of Business, Vienna University of Economics and Business (WU Vienna). She earned her PhD from the University of Vienna and completed her habilitation at WU. Prior to her current role, she held postdoctoral positions at the University of Vienna and CIRRELT in Montreal, and conducted research collaborations at Georgia Institute of Technology, University of Bologna, and Northwestern University. Research Interests: Vera's research centers on combinatorial optimization in logistics, with emphasis on enhancing solution methods and real-world applications. She specializes in metaheuristics, parallel algorithms, and hybrid exact-heuristic techniques. Her work addresses critical challenges in waste collection, city logistics, nonprofit logistics collaboration, and sustainable urban transport—particularly the integration of cargo bikes into freight distribution networks. Publication Trends: Her recent publications reflect a consistent focus on vehicle routing problems, green logistics, and optimization under uncertainty. Themes include two-echelon delivery, drone-truck collaboration, stochastic demands, and multi-depot systems. Methodologically, she advances matheuristics, adaptive large neighborhood search, and simulation-optimization frameworks applied to urban and humanitarian logistics. Scientific Awards: No specific awards mentioned in the provided text. Advising and Grants: While no students are listed, Vera has served as project leader for multiple research initiatives funded by the Austrian Science Fund (FWF) and the Austrian Research Promotion Agency (FFG), indicating leadership in securing competitive grants and managing research teams. Labs and Teams: Although no formal lab name is given, her affiliation with the Institute for Transport and Logistics Management suggests active participation in a research group focused on logistics optimization, likely involving collaboration with national and international partners in both academia and industry.
Cihat Cetinkaya is a Professor in the Department of Software Engineering at Mugla Sitki Kocman University. He holds a PhD in Information Technologies from Ege University and has supervised research on deep learning applications in medical imaging and network optimization for video streaming. Bachelor's: Pamukkale University - Computer Engineering Master's: Ege University - Information Technologies Doctorate: Ege University - Information Technologies His research focuses on Software-Defined Networking (SDN) , Dynamic Adaptive Streaming over HTTP (DASH) , and Machine Learning applications in network management and medical imaging. He has pioneered SDN-based architectures for secure IoT systems and optimized DASH streaming via dynamic routing and MPTCP integration. Key trends in his publications include blockchain network optimization , SDN-driven quality of service (QoS) , and deep learning for radiograph analysis . He has developed tools like NetSim for network simulation and contributed to 5G UPF design via XDP programming. Scientific Awards: Distinguished Paper Award (2017) Student Travel Grant Award (2016) Best Paper Award (2014) As Head of the Department of Software Engineering since 2021, he has taught courses in Software Ethics , Software Testing , and Software-defined Networking . He serves on academic incentive committees and international project evaluation panels.
Professor Jim Harkin serves as Head of the School of Computing, Engineering and Intelligent Systems at Ulster University's Magee Campus in Derry~Londonderry. He is a prominent member of the Computational Neuroscience and Neuromorphic Engineering team within the Intelligent Systems Research Centre (ISRC), where he leads cutting-edge research bridging biological neural processes with hardware implementations. Harkin's research focuses on developing intelligent embedded systems capable of self-repair under error conditions, drawing inspiration from neural network models. His work explores how computer models of neural networks can be mapped to hardware to build highly efficient and reliable embedded computers. Key innovations include Networks-on-Chip strategies and hardware implementation of self-repairing Spiking Neural Networks. His research spans multiple domains including fault tolerance, neuromorphic computing, and AI hardware acceleration, with applications in healthcare, structural monitoring, and energy systems. Analysis of his recent publications reveals a strong trend toward practical applications of neuromorphic computing, particularly in healthcare monitoring systems, structural health assessment, and energy-efficient computing. His work shows increasing integration of spiking neural networks with real-world hardware implementations, demonstrating a clear trajectory from theoretical models to deployable systems with commercial applications. Harkin has received numerous scientific accolades including the Life and Health Startup Company of the Year 2019 from InventNI Ulster Distinguished Learning Support Fellowship Multiple awards for innovative routing strategies in neural network hardware implementations Professor Harkin has secured significant research funding exceeding £3.5 million from diverse sources including EPSRC, MRC, Innovate UK, HSC R&D, InvestNI, and DEL. His grant portfolio demonstrates strong industry and healthcare sector engagement, particularly through his co-founded startup Respiratory Analytics which focuses on medical analytics. He has supervised numerous research students and has been instrumental in Ulster University's Computer Science submissions to major research assessment exercises including RAE 2008, REF2014, and REF2021. As Head of School and leader within the Intelligent Systems Research Centre, Harkin oversees multiple research teams focusing on computational neuroscience, neuromorphic engineering, and intelligent embedded systems. His lab has developed specialized FPGA-based platforms for simulating and implementing self-repairing neural networks, including the AstroByte multi-FPGA architecture for accelerated simulations of fault-tolerant spiking astrocyte-neuron networks.
Thomas G. Fevens is a Professor in the Department of Computer Science and Software Engineering at Concordia University, and an Adjunct Professor in the Department of Surgery at McGill University. He holds a PhD in Computing and Information Science from Queen's University (1999), with prior degrees in Astrophysics and Physics. His research focuses on medical imaging applications of deep learning, computational geometry, and surgical software innovation. Notable work includes computer-aided diagnosis systems for breast cancer using cytological images, 3D surgical planning algorithms, and motion tracking frameworks for ACL injury assessment. Education: PhD in Computing and Information Science, Queen's University (1999) MSc in Computing and Information Science, Queen's University (1994) MSc in Physics (General Relativity), Queen's University (1993) BSc in Astrophysics (Honours), Queen's University (1990) Research emphasizes interdisciplinary applications of AI in healthcare, including: Medical image segmentation using U-Net architectures Deep learning for tumor localization Kinect-based motion analysis systems Generative adversarial networks (GANs) for medical imaging Publications demonstrate contributions to both core computer science (mobile ad hoc networks, computational geometry) and clinical applications (surgical planning, cancer diagnosis). Active in industry collaboration through the ML-MVP lab, focusing on translating AI research into clinical tools.
Liaoyuan Cheng is a Researcher at the Chair of Design Automation, Technical University of Munich, focusing on Electronic Design Automation and Optical Networks-on-Chip. His work centers on wavelength-routed optical networks, with an emphasis on bandwidth allocation, fault detection, thermal variation, and design optimization. Published 8 peer-reviewed articles in top-tier venues (IEEE/ACM ICCAD, DAC, GLSVLSI, ASP-DAC) between 2024-2025 Key research topics include fault detection in optical NoC, process variation-aware design, thermal management, and resource allocation Collaborated with Prof. Ulf Schlichtmann and other researchers like Zhidan Zheng and Tsun-Ming Tseng
Dr. Alexandre Truppel is a researcher at the Chair of Electronic Design Automation, Technical University of Munich (TUM), working under Prof. Ulf Schlichtmann. His affiliation spans the university's core engineering research units, focusing on advanced methodologies for integrated circuit design and photonic interconnect systems within the Department of Electrical and Computer Engineering framework. Truppel's research centers on Optical Networks-on-Chip (ONoC) and Wavelength-Routed Architectures , with deep specialization in crosstalk modeling, bandwidth optimization, and physical layout co-design. His work addresses critical bottlenecks in on-chip communication through algorithmic innovations like Pareto simulated annealing, significantly advancing signal integrity and power efficiency in photonic interconnects for high-performance computing. Analysis of his 2019-2025 publications reveals a cohesive trajectory from foundational PSION topology optimization (2019) to sophisticated multi-objective frameworks (2025), consistently targeting laser power reduction and crosstalk mitigation. The research demonstrates escalating methodological rigor while maintaining focus on practical EDA implementation for next-generation optical NoCs. As part of TUM's Chair of Electronic Design Automation, Truppel operates within a high-impact research ecosystem specializing in analog/mixed-signal EDA, neural network accelerators, and emerging microfabrication technologies. The group's collaborative environment drives innovation in optical interconnects through funded projects and industry partnerships, positioning Truppel's work at the forefront of photonic integration challenges.
Armand Kapaj is a Postdoctoral Researcher at the University of Zurich's Faculty of Science, Department of Geography, affiliated with the Geographic Information Visualization and Analysis (GIVA) research group. His work explores mobile map design, spatial cognition, and navigation in spatially enabled societies. Research Focus: Mobile cartography, spatial cognition, and human-computer interaction Labs: GIVA research group Contact: armand.kapaj@geo.uzh.ch Research examines how mobile maps influence visual attention, spatial learning, and cognitive load during navigation tasks. Key themes include landmark visualization, attention guidance, and navigation interface effectiveness. Scientific contributions include 15 recent publications analyzing mobile map design's impact on spatial knowledge acquisition, landmark memory, and route cognition through experimental studies and VR simulations.
Li-Shiuan Peh is a Provost's Chair Professor in the Department of Computer Science at the School of Computing, National University of Singapore (NUS) . She previously held faculty positions at MIT (2013-2016) and Princeton University (2002-2009), advancing from Assistant to full Professor. Education: B.S. from National University of Singapore (1995) Ph.D. from Stanford University (2001) Her research focuses on energy-efficient hardware systems , spanning neural network accelerators for edge computing , privacy-preserving embedded systems , on-chip communication networks , and hardware security . Current projects include AI-on-skin interfaces , secure Network-on-Chip (NoC) architectures , and low-power wearable sensors . Scientific Awards: IEEE Fellow (2017) National Research Foundation Returning Singaporean Scientist Award (2016) ACM Distinguished Scientist (2011) MICRO Hall of Fame Award (2011) National Science Foundation CAREER Award (2003) Her work has driven innovations in bufferless NoC architectures , collaborative traffic advisory systems , and laser attack benchmarks , with publications in top venues like DATE, NOCS, and DAC. She leads an interdisciplinary research group at NUS, advising graduate students in computer architecture and hardware security.
Mihai Ispas is a Professor at the Department of Wood Processing and Design of Wood Products, Faculty of Furniture Design and Wood Engineering, Transilvania University of Brașov, Romania. His research focuses on wood properties, mechanical processing techniques, and optimization of wood industry technologies. Institution: Transilvania University of Brașov Department: Wood Processing and Design of Wood Products Email: ispas.m@unitbv.ro Professor Ispas's research spans two decades, with recent work emphasizing the application of artificial intelligence (e.g., artificial neural networks) and statistical methodologies (e.g., response surface methodology) to optimize drilling and milling processes for wood composites. His studies analyze surface quality, delamination, and mechanical properties across materials like MDF, particleboard, blockboard, and thermally modified hardwoods such as beech and maple. Key trends in his publications include: Integration of computational modeling with empirical testing Focus on drilling parameter optimization for industrial applications Comparative analysis of tool geometries and processing methods Thermal modification effects on wood machinability Advancements in CNC routing and surface decoration Sustainable practices in furniture and wood industries Contact details: Office: Building L, Room L II 7 Phone: 0372 910037 Address: St. Universității, No 1, Brașov, Romania
