Matthew Stephenson is a Lecturer at Flinders University's College of Science and Engineering, specializing in Artificial Intelligence applications for games. He leads the Data for Decisions initiative within the Factory of the Future Transdisciplinary Hub, focusing on AI-powered scenario generation for smart digital twins. Additionally, he is a member of IRL CROSSING, an international lab studying human-autonomous agent teaming dynamics. PhD in Computer Science (Australian National University, 2019) B.Sc.(Hons) in Computer Science (University of Canterbury, 2015) His research applies AI, Machine Learning, and Data Science to game domains, including intelligent agent development for physics-based environments, procedural content generation, and game analytics. He also investigates deceptive behaviors in multi-agent systems and leverages games as testbeds for real-world AI solutions. Recent publications focus on large language models for game benchmarking, physical reasoning challenges, and evolutionary game generation. Scientific awards include an honourable mention at Foundations of Digital Games (FDG'18). He supervises students in procedural generation, game AI, and physics-based task creation, with teaching roles in computational intelligence and neural networks courses.
Dr. Tim Conrad is a researcher at the Zuse Institute Berlin in the Visual and data-centric computing department under the Mathematics of Complex Systems division. He leads projects at the intersection of computational biology, AI, and medical data analysis. Projects: Geometric Learning for Single-Cell RNA Velocity Modeling, MODAL MedLab, Sparse Compressed Sensing in -Omics Data, BIFOLD (Big Data and Machine Learning) Research Networks: Affiliated with MATH+ and MODAL Research Campus His research focuses on applying machine learning , network optimization , and sparse data analysis to biological and medical challenges including disease modeling, microbiome dynamics, and ECG classification. Recent work explores hybrid PDE-ODE epidemic models and federated learning in healthcare. 2023-2025 publications highlight trends in AI for biological networks , temporal community detection , and medical signal processing . He co-authored studies on SARS-CoV-2 simulations, proteomics feature selection, and multi-label ECG analysis. His 2004 doctoral thesis at Monash University laid foundations for later work in metabolic pathway analysis. Awarded as a Zuse Fellow , he contributes to open science initiatives like FAIR data sharing . Collaborations span institutions including Freie Universität Berlin and Charité in medical informatics and clinical applications.
Professor Atilla Ansal is a distinguished academic in Civil Engineering at Özyeğin University's School of Engineering, where he has served as a full-time professor since March 2012 and previously as the Founding Chair of the Civil Engineering Department from 2012-2019. With an extensive career spanning over five decades, Professor Ansal has held prominent positions at Istanbul Technical University, Bogaziçi University's Kandilli Observatory and Earthquake Research Institute, and has served as a visiting professor at numerous international institutions including Northwestern University, University of California, and Tokyo University. Northwestern University, 1978 (Doctorate) Civil Engineering, Istanbul Technical University, 1969 (Master's) Civil Engineering, Istanbul Technical University, 1969 (Bachelor's) Professor Ansal's research focuses on Earthquake Geotechnical Engineering, Soil Dynamics, Seismic Hazard Analysis, Landslide hazard analysis, Seismic Microzonation, and Laboratory and In-Situ Testing of Soil Properties. His work has significantly advanced our understanding of soil behavior under seismic loading, site response analysis, and seismic microzonation methodologies. His research has direct applications in urban planning, earthquake risk mitigation, and performance-based seismic design. Professor Ansal has pioneered approaches to site-specific earthquake characterization and developed methodologies for seismic microzonation that have been implemented in numerous Turkish cities and adopted internationally. His extensive publication record demonstrates consistent contributions to earthquake engineering, with recent work focusing on probabilistic seismic microzonation, 2D basin effects, site-specific response analysis, and performance-based design approaches. His research shows a clear evolution from fundamental soil behavior studies to practical applications in urban risk assessment and mitigation. 7th Prof.N.Ambraseys Lecturer (2024), European Association for Earthquake Engineering 15th Nonveiller Lecturer (2017), Croatian Geotechnical Society Third Prof.Dr. Rıfat Yarar Lecturer (2015), Turkish Civil Engineers Association Third Ord.Prof.Dr. Hamdi Peynircioglu Lecturer (1988) Professor Ansal has advised 15 PhD students and 27 Master's students, shaping the next generation of earthquake engineers. His leadership extends to editorial roles as Editor-in-Chief of the Springer journal 'Bulletin of Earthquake Engineering' since 2002 and Editor-in-Chief for the Springer book series on 'Geotechnical, Geological and Earthquake Engineering'. He served as Secretary General (1994-2014), President (2014-2018), and Vice President (2018-2022) of the European Association for Earthquake Engineering, significantly influencing the field internationally. His work has been supported by numerous grants from Turkish government agencies, international organizations including UNESCO, and collaborative research projects across Europe. Professor Ansal has been instrumental in establishing geotechnical monitoring systems in Istanbul, including vertical arrays for site response analysis. His leadership in the 'Earthquake Master Plan for Istanbul' and 'Seismic Microzonation for Municipalities' projects has created critical infrastructure for earthquake risk management in Turkey's most populous city. His work with GeoIst, Geotechnical Earthquake Engineering and Consultancy Inc. has translated academic research into practical engineering solutions for seismic risk mitigation.
Michael E. McHenry is a Professor of Materials Science and Engineering at Carnegie Mellon University's College of Engineering. He holds appointments with multiple research centers including the Data Storage Systems Center, Engineering Research Accelerator, Materials Research Science and Engineering Center, and Wilton E. Scott Institute for Energy Innovation. Dr. McHenry received his BS in Metallurgical Engineering and Materials Science from Case Western Reserve University in 1980, his PhD in Materials Science and Engineering from MIT in 1988, and completed a postdoctoral fellowship at Los Alamos National Laboratory. His research focuses on soft magnetic nano-composites for power and energy applications, with particular expertise in metal amorphous nanocomposites (MANCs) for high-efficiency electric motors and power systems. His work spans advanced materials processing, magnetic properties under various conditions, and rare earth materials criticality. His research portfolio demonstrates a clear progression toward practical applications of magnetic materials, particularly in high-power density, high-efficiency motors that can operate at high rotational speeds with minimal energy loss. His publications reveal a strong focus on translating fundamental materials science into engineering solutions for energy conversion, with significant emphasis on rare earth-free alternatives and high-frequency applications. IEEE Distinguished Lecturer (2013) TMS Awardee for Research Excellence (2014) Subject of TMS Symposium in Honor of M. E. McHenry (2016) NATO Series Lecturer on Rare Earth Criticality (2016/17) Dr. McHenry has co-founded CorePower Magnetics Inc. with Paul Ohodnicki and Samuel Kernion, commercializing soft magnetic technologies with applications in grid modernization and electric vehicles. His extensive publication record and leadership in major research initiatives including a MURI on high-temperature magnetic materials and an ARPA-E program demonstrate significant impact in both academic and industrial contexts. He has served in various leadership roles for Magnetism and Magnetic Materials and Intermag Conferences, and continues to advise on rare earth scarcity issues for organizations like NATO.
Jeff Zhang is an Assistant Professor in the School of Electrical, Computer and Energy Engineering at Arizona State University. He joined ASU in January 2023 after completing a postdoctoral fellowship at Harvard University. His research spans deep learning, computer architecture, embedded systems, and EDA, with particular emphasis on energy-efficient and fault-tolerant design for AI/ML systems and hardware accelerators. Education: Ph.D., New York University M.Eng., B.Eng., Hunan University Dr. Zhang's research bridges theoretical machine learning with practical hardware implementation, developing novel architectures that optimize performance, power consumption, and reliability. He has pioneered approaches for hardware acceleration of large language models, efficient sparse matrix operations, and novel memory technologies for AI workloads. His work has received multiple awards including IEEE Top Picks in Test and Reliability (2023) and IEEE Micro Best Paper Award (2022). His recent publications demonstrate a strong trend toward heterogeneous computing, with significant work in chiplet-based AI accelerators, photonic computing for AI, and 2.5D/3D integration techniques. The research spans from high-level compiler frameworks to circuit-level innovations, with a consistent theme of co-designing algorithms and hardware for optimal AI performance. His work on the SODA toolchain has been particularly influential in bridging Python to silicon. Scientific Awards: IEEE Top Picks in Test and Reliability, IEEE ITC, 2023 Best Paper Award, IEEE Micro, 2022 Best Paper Award Candidate, IEEE DATE, 2022 Best Presentation Award Nomination, ACM SIGDA DATE PhD Forum, 2020 Best Paper Award Nomination, IEEE VLSI Test Symposium, 2018 Ernst Weber Ph.D. Fellowship, New York University, 2015, 2016 Dr. Zhang actively mentors a diverse group of graduate and undergraduate students, with several alumni now working at leading technology companies including Apple, TSMC, and Ansys. His research is supported by prestigious grants from NSF, Sandia National Labs, and industry partners. He serves on technical program committees of numerous top conferences and has organized special sessions on emerging topics like Gen AI for Chip Design and LLM-Aided Design. Dr. Zhang leads a vibrant research group that collaborates extensively with industry partners and national laboratories. Current projects focus on next-generation AI hardware, including chiplet-based systems, photonic accelerators, and novel memory technologies for large language models. His group has developed several open-source tools and frameworks, including the SODA toolchain for bridging Python to silicon.
Prof. Dr. Christian Mayer is a Professor in Physical Chemistry at the Faculty of Chemistry, University of Duisburg-Essen. He serves as Head of the working group focusing on origin of life research, nanocapsules, and NMR spectroscopy techniques. His research group is located at Universitätsstraße 5, D-45141 Essen, Germany, with contact information including phone number +49 201 183-2570. Prof. Mayer's research interests primarily focus on the origin of life in deep tectonic fault zones of the first continental fragments, where he collaborates with Prof. Dr. Ulrich Schreiber from the Faculty of Biology and Prof. Dr. Oliver Schmitz from Applied Analytical Chemistry. His work investigates how vesicle formation occurs in tectonic fault systems through cyclic phase transitions of carbon dioxide, creating ideal conditions for molecular evolution. He specializes in pulsed field gradient NMR (PFG-NMR), high-resolution NMR, and solid-state NMR techniques to characterize nanoscale systems including nanocapsules, vesicles, and microemulsions. His recent publication trends reveal a strong interdisciplinary focus spanning physical chemistry, prebiotic chemistry, and astrobiology. The articles demonstrate increasing integration of computational methods with experimental approaches, particularly in analyzing molecular structures and dynamics. His research has evolved from fundamental studies of nanocapsule systems to broader investigations of protocell formation mechanisms under early Earth conditions, with recent work extending to astrobiological contexts including potential life formation on Titan. Prof. Mayer has established significant collaborations across multiple disciplines, particularly with geologists and biologists, to investigate the physical chemical processes that could have led to the emergence of life. His work bridges fundamental physical chemistry with practical applications in nanomedicine, particularly in developing artificial oxygen carriers based on nanocapsule technology. His laboratory utilizes high-pressure facilities to simulate early Earth crust conditions, with a particular focus on supercritical CO 2 environments. The working group combines experimental approaches with theoretical modeling to understand vesicle formation processes and their implications for the origin of cellular life.
Dr. Christian Jaeger is a Researcher at the Zurich University of Applied Sciences (ZHAW) School of Engineering, focusing on Machine Learning in Optimal Control for Industry. His work bridges engineering and computer science with applications in industrial automation and building systems. His research interests span Machine Learning , Optimal Control , Reinforcement Learning , Energy Management Systems , and Industrial Automation . Jaeger has led multiple research projects including a preliminary study on automated IBN heat pumps and a feasibility study on Reinforcement Learning Control for heating systems. His work demonstrates a clear trajectory from traditional manufacturing technology toward contemporary AI-driven control systems. Jaeger's publication record shows consistent output from 2005 to 2024, with recent focus on energy optimization in building control using reinforcement learning, 3D printing techniques, and model predictive control. His research demonstrates strong interdisciplinary connections between computer science, engineering, and practical industrial applications. His scientific contributions include publications in journals such as Applied Sciences and the Journal of the British Interplanetary Society, along with numerous conference proceedings from international events including EuroSun and the International Symposium on Nonlinear Theory and its Applications. At ZHAW, Jaeger has served as project leader for multiple completed research initiatives including adaptive energy management systems for buildings and automated heat pump systems. His work demonstrates strong industry connections with applications in building automation and industrial manufacturing processes.
Gregory M. Shaver is the Reilly Professor of Mechanical Engineering and Director of Herrick Laboratories at Purdue University's School of Mechanical Engineering. He holds a Ph.D. (2005) and M.S. (2004) in Mechanical Engineering from Stanford University, and a B.S. (2000) from Purdue University where he graduated with highest distinction. His research focuses on model-based control of sustainable transportation systems, with emphasis on: Commercial vehicle powertrain optimization Internal combustion engine and after-treatment controls Flexible valve actuation for diesel/natural gas engines Connected/automated vehicle systems Battery modeling for energy storage Fundamental areas include thermodynamics, combustion, and control systems, applied to sustainable energy and transportation challenges. Publication analysis reveals consistent focus on engine efficiency innovations (cylinder deactivation, valve control), electrified transportation (hybrid systems, battery modeling), and emission reduction strategies. Recent work emphasizes real-world applications in medium-duty vehicles and thermal management. Awards and honors: 2014 Early Career Excellence in Research Award (Purdue Engineering) 2014 University Faculty Scholar 2011 Max Bentele SAE Award for Engine Technology Innovation Purdue BSME with Highest Distinction (2000) He leads research initiatives at Herrick Laboratories, supervising graduate students in projects funded by industry and government grants. Current work explores AI-enabled control for hybrid vehicles and low-emission combustion strategies.
Vasil Georgiev Tsunizhev is a Professor of Computer Informatics at the Faculty of Mathematics and Informatics, Sofia University, with office hours Monday and Wednesday 13:00-14:00 in room FMI-110. Contact: v.georgiev@fmi.uni-sofia.bg, +359 2 8161-594. His research spans cloud computing, distributed systems, and grid technologies with emphasis on resource management, load balancing, and service modeling. Key contributions include numerical solutions for cloud servicing, distributed coordination mechanisms, and fault-tolerant information services. His work integrates open-source components and addresses scalability challenges in cloud environments. Analysis of his 2009-2015 publications reveals consistent focus on cloud infrastructure optimization, with recurring themes in resource frameworks, quality-of-service models, and distributed coordination. His research demonstrates strong technical depth in numerical modeling and system architecture while addressing real-world scalability and fault tolerance requirements. Professor Tsunizhev collaborates internationally through projects like CoreGRID (contributing to grid security white papers) and works with researchers including R. Zhelev and L. Kirchev. His laboratory work focuses on commodity grid platforms and lightweight resource management systems for distributed computing environments.
Dr. Frank Loh is a researcher at the Department of Computer Science III, University of Würzburg, specializing in energy efficiency, network performance, and Quality of Experience (QoE) in communication networks. His work focuses on optimizing LoRaWAN deployments, serverless computing, and edge-cloud environments, with an emphasis on reducing message collisions and improving resource utilization. He actively contributes to methodologies for gateway placement, traffic modeling, and energy consumption metrics. Research Areas Energy Efficiency in Communication Networks Quality of Service (QoS) and Quality of Experience (QoE) LoRaWAN Network Planning Edge and Serverless Computing Network Resource Analysis Recent Publications 2025: Energy modeling for 6G base stations 2025: Server cluster resilience via Markov models 2024: Serverless computing in edge-cloud environments 2024: LoRaWAN channel access optimization
Hua Ge is a Professor in the Department of Building, Civil and Environmental Engineering at Concordia University's Faculty of Engineering and Computer Science. She holds a Tier II Concordia University Research Chair in High Performance Building Envelope for Climate Resilient Buildings and leads extensive research in building science and climate adaptation. Her research focuses on wind-driven rain analysis , hygrothermal performance of building envelopes , advanced building facades , innovative wood-frame construction , and low-energy buildings . Current work examines climate change impacts on wind-driven rain loads, urban micro-climate effects, climate-resilient building envelopes, dynamic facades, and low-carbon healthy buildings. Her methodology combines large-scale laboratory testing, field monitoring, and computational modeling. Her 15 most recent publications demonstrate strong trends in nature-based climate resilience solutions , overheating risk mitigation in educational buildings , advanced hygrothermal modeling of wood-frame systems , and carbon sequestration strategies for buildings. The work spans multiple sub-disciplines including computational fluid dynamics, life cycle assessment, stochastic modeling, and field validation studies across Canadian climates. Tier II Concordia University Research Chair (CURC) in High Performance Building Envelope for Climate Resilient Buildings Professional Engineers of Ontario American Society of Heating, Refrigerating and Air-conditioning Engineers ASHRAE TC4.4 Building materials and building envelope performance (Subcommittee Chair) Professor Ge has supervised 42 graduate students (26 PhD, 16 MASc), including current advisees working on nature-based solutions, climate-resilient envelopes, and building integrated photovoltaics. Her research is supported by Concordia University Research Chair funding and collaborative projects with institutions like BCIT. She directs activities at Concordia's Building Envelope Test Facility and contributes to national standards through ASHRAE.
Omobolanle Ogunseiju is an Assistant Professor in the School of Building Construction at Georgia Institute of Technology . She holds a Ph.D. in Environmental Design and Planning from the Department of Building Construction at Virginia Tech. Education: Ph.D. in Environmental Design and Planning, Virginia Tech Current Role: Assistant Professor, Georgia Tech School of Building Construction Her research focuses on integrating wearable robotics and Artificial Intelligence (via digital twin , cyber-physical systems , and data sensing ) to improve construction workforce safety, health, and well-being . She explores ethical implications of automation in construction, particularly in human-technological dynamics. Key research trends include: Advancing smart communities through robotics and AI Exoskeleton evaluation for ergonomic risk reduction Mixed reality environments for construction education Data analytics for cognitive and physical risk assessment Professional identity development in construction engineering students Industry-academia alignment for sensing technology integration Scientific awards: Outstanding Doctoral Candidate, Myers-Lawson School of Construction Outstanding Doctoral Student, College of Architecture and Urban Studies at Virginia Tech Teaching philosophy emphasizes experiential learning , engagement techniques , and hierarchical assessments . She developed the Construction Cost Management course at Georgia Tech and will lead Construction Technology courses. Previously, she taught Smart Construction , Building Systems Technology , and Wireless Sensing in Construction Management at Virginia Tech.
Professor Alec Wilson holds the position of Professor in Computational Aeroacoustics at the University of Southampton, where he serves as Director of the Rolls-Royce University Technology Centre (UTC) in Propulsion Systems Noise within the Faculty of Engineering and Physical Sciences. His career spans academic research and industrial collaboration, focusing on aeroengine noise sources, sound propagation modeling, and computational fluid dynamics (CFD) applications for aerospace systems. University of Southampton (2016–present): Professor in Computational Aeroacoustics Rolls-Royce (prior to 2016): Technical specialist in aeroengine noise and CFD Research Interests: Alec’s work centers on advancing eigen analysis techniques for acoustic propagation in complex duct geometries and mean flows. His research addresses challenges in next-generation aircraft noise modeling, including boundary layer effects, transonic fan optimization, and multi-disciplinary design approaches. Key contributions include developing fast, computationally efficient methods for noise prediction and sensitivity analysis in propulsion systems. Recent Research Trends: His 2024 publications focus on tone noise propagation and buzz-saw noise under flow distortion, while earlier works (2019–2022) explore non-uniform duct modeling, adjoint optimization for blade design, and error quantification in eigen analysis. Scientific Awards: Rolls-Royce Engineering Fellowship (Associate Fellow in Aerodynamics, Hydrodynamics, and Computational Fluid Dynamics) Teaching & Supervision: Alec supervises PhD students and teaches in acoustics, aerodynamics, and mechanical engineering. He currently advises Joseph Stephen Paul Binns, focusing on aeroacoustic modeling and optimization. External Roles: Vice-chair of CEAS/ASC (Council of European Aerospace Societies, Aeroacoustics Subcommittee).
Prof. Dr. Harald Reiterer is a leading researcher in Human-Computer Interaction at the University of Konstanz, where he has served as Professor since 2009. His academic journey includes a Ph.D. (1991) and habilitation (1995) from the University of Vienna, followed by roles including Senior Researcher at Fraunhofer FIT and Associate Professor at Konstanz. He currently holds multiple leadership roles: Dean of the Faculty of Sciences , Senator of Section 1 , and Consulting Dean . Ph.D. in Computer Science (University of Vienna, 1991) Venia Legendi (Habilitation) in HCI (University of Vienna, 1995) His research focuses on: Interaction Design for mixed reality environments Information Visualization in immersive contexts Hybrid User Interfaces combining physical and virtual elements 3D Object Manipulation in handheld AR Behavioral Analytics through mHealth interventions Recent work explores: Avatar representation in Augmented Reality (2024) Node selection efficiency in Virtual Reality (2024) Peripheral vision toolkits for Head-Mounted Displays (2023) Hybrid interface optimization for Mixed Reality (2023) Smartphone AR extensions for Spatial Memory (2023) Key scientific contributions: Landeslehrpreis 2021 for interdisciplinary exhibition design Development of Colibri cross-reality toolkit (2023) Foundational work on Re-locations for remote collaboration (2022) He leads numerous projects including: SMARTACT (Smart Mobility, 2015-2023) SFB TRR 161 (2009-2027) on XR interface measurement Blended Library (2011-2015) for future library design
Lisa Wu Wills is an Assistant Professor in the Department of Computer Science and Electrical and Computer Engineering at Duke University, leading the APEX Lab (Application-driven Programmable Efficient Accelerated Systems Lab). Her research focuses on hardware acceleration for big data analytics in genomics, graphs, and databases to advance healthcare and natural sciences. Education: Ph.D. in Computer Science, Columbia University, 2014 Research Interests: Dr. Wills pioneers computer architecture and hardware-software co-design to create efficient accelerators for emerging applications. Her work targets genomics , graph analytics , and database systems , emphasizing simplified hardware deployment and energy efficiency for scientific breakthroughs in healthcare and AI. Publication Trends: Her 2022-2025 publications reveal a strong focus on open-source frameworks (Beethoven, PyTFHE) for accelerator development, hardware acceleration in privacy-preserving computing, and optimization for large language models. Key themes include transfer learning for EDA, domain-specific architectures for genomics, and energy-efficient image processing. Scientific Awards: Google ML and Systems Junior Faculty Award (2025) Advising and Grants: Dr. Wills mentors three PhD students: Chris Kjellqvist (Beethoven framework architect), Mason Ma (PyTFHE lead for FHE applications), and Mansi Choudhary (COCOSSim simulator creator). Her 2025 Google award funds research on accelerating vector databases and retrieval-augmented generation for LLMs. Labs and Teams: She directs the APEX Lab at Duke, developing tools like Beethoven (open-source accelerator composer) and PyTFHE for hardware-software integration, enabling domain scientists to leverage custom acceleration with minimal hardware expertise.
