Dr. Almas Shintemirov is a Research Fellow at Aalto University's Department of Electrical Engineering and Automation, specializing in robotics, control systems, and human-robot interaction. His research focuses on intelligent robotics, with emphasis on Real-time motion prediction for collaborative robots Nonlinear control algorithms for safe human-robot interaction Open-source robotic hardware design Deep learning applications in autonomous systems
Jonathan Bean is an Associate Professor at the University of Arizona, affiliated with the School of Architecture and School of Landscape Architecture and Planning . As a CUES Distinguished Fellow , he bridges architecture, marketing, and civil engineering through research on market transformation, taste regimes, and sustainable building practices. His work integrates consumer research, human-computer interaction, and building science. PhD, University of California at Berkeley (2011) MS, University of California at Berkeley (2008) BA, University of University of California at Berkeley (2002) Bean's research focuses on high-performance building systems , consumer culture theory , and taste regime analysis . He advocates for energy-efficient AI systems and explores sociomaterial dimensions of cosmopolitan servicescapes. His work on the SunBlock distributed district energy system highlights innovative approaches to carbon reduction. Recent publications examine AI ethics, energy equity, Solar Decathlon innovations, and IoT challenges. Awards include the CUES Distinguished Fellow title and leadership roles in the Passive House Alliance US . Grants from the SSHRC Canada and National Institute for Transportation and Communities support his interdisciplinary work. Bean advises the Master of Science in Architecture Sustainable Market Transformation Concentration and contributes to the Consuming Tech column for ACM Interactions. His TEDx talk Demand Less underscores the potential of passive building principles for net-zero museums and energy stability.
Dr. Jose Paolo Talusan is a Research Scientist at the Department of Computer Science and Computer Engineering , Vanderbilt University, specializing in smart transportation systems , distributed computing , and cyber-physical systems . He is affiliated with ScopeLab , a research group focused on smart cyber-physical systems. Education: PhD from Nara Institute of Science and Technology, Japan (2020) Research Interests: His work addresses challenges in urban mobility through middleware architectures, optimization algorithms, and machine learning. Key areas include incident detection in transportation systems, privacy-preserving route planning, and vehicle-to-building charging optimization. Publication Trends: Recent publications focus on real-time transit optimization (2024-2025), leveraging reinforcement learning for heterogeneous agents in vehicle-to-building systems, and privacy-aware route planning in smart cities. His work integrates IoT , edge computing , and graph neural networks to tackle imbalanced data and sparsity issues in transit analytics. Labs & Teams: Actively contributes to ScopeLab at Vanderbilt University, collaborating on interdisciplinary projects with researchers in computer science, electrical engineering, and urban planning.
Dr. Karthik Akkiraju serves as Assistant Professor in the Department of Materials Engineering within UBC's Faculty of Applied Science, maintaining an active research program at the intersection of materials science and socio-environmental systems. His office (FF 011) and contact email (karthik.akkiraju@ubc.ca) reflect his current institutional affiliation. His research pioneers a techno-social paradigm for planetary health through three synergistic foci: (1) Establishing material poverty benchmarks using household survey data to identify resource-deprived communities; (2) Quantifying socio-environmental impacts across material supply chains; (3) Integrating well-being metrics into heterogeneous catalyst design frameworks. This work fundamentally reimagines materials engineering by centering human well-being within ecological boundaries, developing design methodologies that balance material requirements with equitable environmental constraints. Analysis of his publication trajectory reveals consistent interdisciplinary innovation spanning computational catalysis, environmental policy, and social metrics. His recent work demonstrates particular strength in perovskite catalyst engineering for sustainable chemistry and novel methodologies for spatial well-being assessment, reflecting a unique fusion of traditional materials science with computational social science. Dr. Akkiraju directs the Sustainable Materials Lab (SMAL), where his team develops frameworks connecting material consumption patterns to human development outcomes, creating pathways for resource allocation that simultaneously address poverty alleviation and environmental sustainability.
Dr. Kwang Ho Kim serves as an Assistant Professor in the Department of Wood Science within the Faculty of Applied Science at the University of British Columbia (UBC), having joined the institution in July 2024. Previously, he held positions as a Principal Researcher at the Korea Institute of Science and Technology (KIST) and as an Adjunct Professor at UBC from 2018 to 2021, where he collaborated extensively with campus researchers. His research centers on sustainable biorefinery processes for maximizing biomass carbon conversion into value-added products. Key focus areas include catalytic lignin valorization, deep eutectic solvent applications in biomass pretreatment, and waste plastic conversion technologies. His interdisciplinary work bridges chemical engineering, green chemistry, and materials science to develop circular economy solutions for biomass and polymer waste streams. Analysis of Dr. Kim's recent publications (2022-2024) reveals dominant trends in catalytic biomass conversion, particularly using deep eutectic solvents for lignocellulose fractionation and plastic glycolysis. His work demonstrates strong emphasis on hydrogenolysis techniques for lignin depolymerization, electrochemical battery material analysis, and machine learning applications in renewable energy systems. These publications collectively advance sustainable pathways for biofuels, biobased chemicals, and waste-to-value processes.
Scott Mahlke is a Professor and Associate Chair in the Department of Electrical Engineering and Computer Science at the University of Michigan's College of Engineering. He is affiliated with both the Advanced Computer Architecture Laboratory and the Software Systems Laboratory. Dr. Mahlke joined the University of Michigan in 2001 after completing his Ph.D. at the University of Illinois and working at HP Laboratories. Ph.D., University of Illinois Former Researcher, HP Laboratories Dr. Mahlke's research spans compilers, computer architecture, and high-level synthesis, with particular focus on overcoming challenges in performance, power consumption, and reliability for next-generation computer systems. His work integrates hardware and software co-design approaches to address fundamental limitations in modern computing platforms. His research has evolved from traditional compiler and architecture topics toward increasingly incorporating machine learning acceleration, autonomous systems, and reliability engineering. Analysis of his recent publications (2021-2025) reveals a strong trend toward hardware-software co-design for emerging workloads, particularly in autonomous systems, neural network acceleration, and reliability-aware computing. His work demonstrates consistent innovation in bridging compiler technology with architectural innovations to solve real-world performance and efficiency challenges. Dr. Mahlke has received significant recognition for his contributions to the field: National Science Foundation CAREER Award (2003) for "Compiler-Directed Synthesis of Application Specific Processors" Morris Wellman Faculty Development Assistant Professor appointment (2004) ISCA Most Influential Paper Award (2006) for the 1991 paper "IMPACT: An Architectural Framework for Multiple Instruction Issue Processors" Young Alumni Award from the University of Illinois ECE Department (2007) As an educator, Dr. Mahlke has taught core computer systems courses including EECS 370 (Introduction to Computer Organization), EECS 483 (Compiler Construction), and EECS 583 (Advanced Compilers) since joining Michigan. His teaching philosophy follows Yale Patt's 10 commandments for teaching, emphasizing understanding over memorization, genuine respect for students, and taking responsibility for course content. He has received mixed but generally positive student evaluations, with students noting both his deep subject matter expertise and areas for improvement in lecture delivery. Dr. Mahlke maintains active research leadership through his affiliations with the Advanced Computer Architecture Laboratory and Software Systems Laboratory, where his team continues to explore innovative approaches to compiler and architecture challenges in modern computing systems.
Roger Stirnimann serves as a Lecturer in Agricultural Engineering at the Bern University of Applied Sciences, specifically within the School of Agricultural, Forest and Food Sciences HAFL, Department of Agronomy in Zollikofen. With over a decade of academic experience since 2013, he has established himself as a specialist in agricultural machinery and tractor technology. His educational background includes an Executive Master of Business Administration from Kalaidos Fachhochschule Bern (2007-2008), a degree in Economics Engineering from Private Hochschule für Wirtschaft Bern (2000-2002), and an Agricultural Engineering degree from SHL Zollikofen (1993-1996). He further enhanced his academic teaching skills with a Certificate of Advanced Studies in University Teaching and e-Learning (2013-2014). Agricultural Engineering in general Tractor Technology and development Transport Technology in agriculture Self-propelled harvesting machinery Alternative drive systems for agricultural vehicles Emissions from Nonroad Mobile Machinery Terramechanics and soil-vehicle interaction Trailer braking systems His publication record demonstrates consistent scholarly output, particularly in tractor technology and agricultural machinery. The analysis of his 15 most recent articles reveals a strong focus on tractor development, engine and transmission systems, alternative drive concepts, and classification methodologies. His work bridges theoretical research with practical applications in agricultural machinery, with particular emphasis on performance optimization, sustainability, and technological innovation in farming equipment. Max Eyth commemorative coin in silver (DLG) Stirnimann actively contributes to academic and industry organizations, serving as a co-author for the Yearbook of Agricultural Engineering, Swiss delegate for OECD's Tractor Test Codes, and chair of DLG's Vehicle Technology examination commission. His industry experience prior to academia, particularly with Ammann Schweiz AG and Matra, provides valuable practical context to his academic work. His research often addresses real-world challenges in agricultural machinery, focusing on performance, efficiency, and environmental impact. His work with various tractor chassis concepts, soil pressure analysis, and alternative drive systems demonstrates his commitment to advancing sustainable and efficient agricultural technology. Through his memberships in organizations like ISTVS (International Society for Terrain-Vehicle Systems) and the Club of Bologna, he maintains strong connections between academic research and industry applications.
Jussi Kangasharju is a Professor in the Department of Computer Science at the University of Helsinki and leads the Collaborative Networking research group . He is also a supervisor for the Doctoral Programme in Computer Science and a member of IEEE and ACM . Research Interests: Edge Computing Information-Centric Networking Content Distribution Green Networking Future Internet Development Scientific Awards: Best Paper Award (2015) Winner of 9th Helsinki Science Slam Competition (2016) Best Paper Award (2004) Key Projects: He has led initiatives like ELLIS-instituutti (2025–2032) and University Profiling Funding (2025–2030), focusing on transdisciplinary networks and future Internet sustainability. Academic Visits: Notable visits include Seoul National University (2012) and the International Computer Science Institute (2013), further enriching his collaborative work.
Jean-Daniel Penot is a Researcher at CESI's Research and Innovation Department , with expertise in additive manufacturing, materials science, and industrial integration. His work bridges advanced manufacturing technologies with environmental sustainability and educational innovation. Doctorate in Materials Physics (2010) Engineering Degree in Physics (2007) Research Master in Optoelectronics (2007) Penot's research spans Additive Manufacturing and its applications in automotive, nuclear, and construction sectors. He focuses on Laser-Material Interaction , Machine Learning for process optimization, and Sustainable Engineering through life cycle assessments and geopolymer applications. His recent publications emphasize BIM , AM Modular Plants , and Defect Analysis in 3D-printed metals. Penot leads France Additive initiatives and contributes to International Standards as a board member. Penot supervises PhD students including Maryam Houhou and Amal Khabouchi , with a focus on Industrial Security and Energy Transitions . His projects integrate Thermal Comfort , Ultrasonic Inspection , and Quality Assurance in additive manufacturing systems.
John Paparrizos is an Assistant Professor of Computer Science and Engineering at The Ohio State University's College of Engineering, where he directs The DATUM Lab (Data Analytics, Understanding, Mining, and Management Lab). He maintains an adjunct affiliation with the School of Informatics at Aristotle University of Thessaloniki. His research spans databases, data science, machine learning, and artificial intelligence , with focus areas including: Time-series analysis (clustering, anomaly detection) Scalable data mining for structured/unstructured data Adaptive algorithms for resource-constrained environments Foundational technologies for data-intensive applications His work addresses real-world challenges across relational, time-series, multimedia, text, graph, web, and IoT data domains. Notable recognition includes: 2025 ACM SIGMOD Test-of-Time Award for k-Shape time-series clustering 2023 IEEE TCDE Rising Star Award ACM SIGMOD Research Highlight Award NetApp Faculty Award His research has been featured in New York Times (front page), Washington Post , Forbes , and adopted by Fortune 500 companies (Exelon, Nokia) and the European Space Agency. He actively serves on program committees for premier conferences including ACM SIGMOD, VLDB, IEEE ICDE, ACM SIGKDD, and NeurIPS. His open-source tools have exceeded 100,000 downloads and are integrated into academic curricula at Brown, Columbia, Purdue, and University of Chicago.
Jari Vepsäläinen is an Assistant Professor at Aalto University's Department of Energy and Mechanical Engineering under the College of Engineering. He serves as Director of the Fluid Power group and specializes in mechatronics design, energy efficiency, and generative design methodologies. Research focuses on physics-based modeling for energy recovery AI/ML applications in electromechanical system design Applications in robotics, heavy machinery, and sustainable transportation His recent publications demonstrate expertise in hybrid systems, fluid power optimization, and AI-driven engineering, with a strong emphasis on electrification and efficiency across automotive, maritime, and industrial domains. Key areas: Mechatronics, Energy Systems, Generative Design Technologies: Digital Twins, IoT, Machine Learning Current projects involve thermal energy systems, electric motor optimization, and advanced control algorithms for mobile machinery.
Professor Aruna Prasad Seneviratne serves as the Foundation Professor of Telecommunications at the University of New South Wales (Australia), where he holds the prestigious Mahanakorn Chair of Telecommunications. He is currently the Research Director for the Cyber Physical Systems Research Program within Data61, following the merger of NICTA with CSIRO. Previously, he directed the Australian Technology Park Laboratory of NICTA and led their Networked Systems research activities. Professor Seneviratne's research focuses on physical analytics - technologies enabling applications to interact intelligently and securely with their environment in real time. His recent work includes behavioral biometrics, wearable device optimization, and IoT system verification. His extensive publication record spans cybersecurity, artificial intelligence, communications engineering, and mobile technologies, with particular emphasis on integrated communications and sensing systems. His scholarly contributions include over 180 refereed technical papers and book chapters, reflecting his leadership in telecommunications and networked systems research. Professor Seneviratne's work demonstrates a consistent trajectory toward developing practical solutions for next-generation digital services and security frameworks. His scientific recognition includes prestigious fellowships at British Telecom and Telecom Australia Research Labs, underscoring his industry impact alongside academic contributions. Professor Seneviratne has supervised 30 PhD dissertations throughout his career, mentoring the next generation of telecommunications researchers. His leadership extends to directing major research initiatives at NICTA and Data61, where he has guided the development of new technologies for establishing trust, energy-efficient content storage, search, and distribution within digital economies. His laboratory work centers on the Cyber Physical Systems Research Program at Data61, where his team develops innovative approaches to secure and intelligent interaction between digital systems and physical environments.
Maurice Gagnaire is a Full Professor at Télécom Paris in the Computer Science and Networks (Infres) department, affiliated with the Networks, Mobility and Services (RMS) research team and the Information Processing and Communication Laboratory (LTCI). He has contributed extensively to optical network design, cloud computing, and network virtualization. Education: Engineering degree from Télécom SudParis, Master's in Computer Systems (Paris VI), Ph.D. (Télécom ParisTech), HDR (University of Versailles) Research Interests : His work focuses on translucent WDM networks , green networking , dynamic resource allocation , and physical layer impairments . Key projects include traffic grooming , failure detection , and energy-aware routing . Publications & Awards : He co-authored Springer's Traffic Grooming for Optical Networks and received the IBM Faculty Award 2014 . His research spans optical access systems , cloud brokering , and multi-layer traffic engineering . Scientific Honors: IBM Faculty award, Chevalier de l'Ordre des Palmes Académiques Academic Service : He served as expert for NSF (USA), IEEE, and ARCEP. His leadership includes coordinating the RMS research group and leading the Optimization and Networking Cluster.
Amir Taherkordi is a Professor in the Networks and Distributed Systems group at the Department of Informatics, University of Oslo, Norway. His research focuses on resource-efficiency, scalability, adaptability, and mobility in distributed systems for emerging technologies like IoT, Fog/Edge/Cloud Computing, and Cyber-Physical Systems (CPS). University: University of Oslo Department: Informatics Academic Rank: Professor His research spans IoT, Edge/Fog Computing, and Cyber-Physical Systems, emphasizing energy efficiency, privacy preservation, and self-adaptive architectures. Key areas include network traffic classification, computation offloading, and federated learning applications in vehicular systems. Recent publications highlight advances in latency-aware IoT data transmission , federated vehicular networks , energy-efficient wireless charging , and privacy-preserving data integration . These works often integrate machine learning with network optimization. Projects include the CPS Lab at UiO, DILUTE (Fluid Service Abstraction), and the Gemini Centre on IoT . He collaborates on initiatives like PACE for energy informatics curricula development.
Yafeng Yin is Professor of Civil and Environmental Engineering and Professor of Industrial and Operations Engineering at the University of Michigan, College of Engineering, where he serves as Donald Malloure Department Chair of Civil and Environmental Engineering and holds the Donald Cleveland Collegiate Professorship in Engineering. His educational background includes: PhD in Civil Engineering from University of Tokyo (2002) ME in Civil Engineering from Tsinghua University (1996) BE in Environmental Engineering from Tsinghua University (1994) BE in Structural Engineering from Tsinghua University (1994) Dr. Yin's research centers on developing sustainable and economically efficient transportation systems through analysis, modeling, design, and optimization. He investigates how emerging technologies—including connected/automated vehicles, electric vehicles, drones, and mobile sensing—impact transportation demand and supply. His work extends to interdependencies between transportation, power, and communications networks in urban infrastructure systems. Key focus areas include mobility services, ride-sourcing markets, traffic management, and integration of artificial intelligence in transportation. His recent publications (2023-2025) demonstrate a pronounced shift toward leveraging large language models and agent-based frameworks for transportation analysis, with significant emphasis on on-demand mobility services (ride-sourcing, food delivery), traffic control with connected vehicles, and economic implications of emerging technologies. The research spans theoretical foundations in game theory and optimization to practical applications in urban settings. As director of the Lab for Innovative Mobility Systems, Dr. Yin leads interdisciplinary research developing solutions that enhance transportation efficiency, reliability, safety, and service diversity through technological integration. His work bridges theoretical modeling with real-world implementation challenges in evolving transportation ecosystems.
