Dr. Adam Rysanek is an Assistant Professor of Environmental Systems at the University of British Columbia (UBC) School of Architecture and Landscape Architecture (SALA). His expertise spans green building design, construction, and operation, with a focus on parametric tools like Rhino/Grasshopper for performative building design. Education: PhD in Engineering, University of Cambridge BASc and MScE, Queen’s University Dr. Rysanek integrates emerging technologies such as augmented reality and machine learning into architectural design optimization, and investigates building performance through Internet-of-Things (IoT) sensors and data analytics. His research also explores future trends in community-scale energy systems, including building-integrated transportation energy systems (BITES). Research Leadership: Supervises postdoctoral and graduate researchers at UBC SALA and Department of Mechanical Engineering Current projects hosted by the Buildings Decisions Research Group (BDRG): bdrg.io
Ulf Hanefeld is a Full Professor and Section Leader in the Department of Biotechnology at the Faculty of Applied Sciences , Delft University of Technology (TU Delft) , where he leads the Biocatalysis research section. His work integrates chemistry and biology to develop sustainable synthetic methodologies using enzymes. PhD from Georg-August-Universität zu Göttingen (1993) Postdoctoral experience at Imperial College London, University of Cambridge, and TU Delft Recipient of a Royal Netherlands Academy of Arts and Sciences (KNAW) fellowship His research interests center on biocatalysis , particularly enzymes that enable difficult chemical transformations such as C–C bond formation , enantioselective hydration , and ozonolysis . He focuses on enzyme discovery, engineering, immobilization, and application in flow chemistry to achieve sustainable and efficient synthesis. His work spans from fundamental enzyme mechanism studies to industrial applications in green chemistry . The publication trends reveal a consistent focus on enzyme immobilization , flow reactor systems , and chemo-enzymatic cascades . His recent work emphasizes the use of hydroxynitrile lyases , aldolases , and methyltransferases for the synthesis of chiral intermediates under environmentally benign conditions. The integration of biocatalysis with continuous manufacturing highlights a strong commitment to industrial applicability and process sustainability. Scientific contributions and recognition : Active contributor to high-impact journals in chemistry and biotechnology Coordinated research in the CassaFLOW project (international academic-industrial collaboration) Author of influential reviews, e.g., in Chemical Society Reviews (2022) Teaching and supervision : He teaches Catalysis (Bachelor) and Advanced Biocatalysis (Master), and supervises numerous Master’s theses (MEP) and Bachelor’s projects (BEP) . Students in his group are actively involved in research and often become co-authors on scientific papers. Projects center on green chemistry, enzyme engineering, and spectroscopic analysis of biochemical systems. Laboratory and research environment : The Ulf Hanefeld Group operates within the Biocatalysis section, a multidisciplinary environment fostering collaboration on enzyme discovery, immobilization, and cascade reactions. The group emphasizes practical innovation, with strong links to industry and international research networks.
Julian McAuley is a Professor in the Department of Computer Science and Engineering at the University of California, San Diego's Jacobs School of Engineering. His research spans recommender systems, machine learning, natural language processing, music information retrieval, and multimodal learning. He maintains an active research group with numerous PhD students and postdocs working on cutting-edge AI problems. His research interests focus on developing advanced algorithms for personalized recommendation systems, with particular emphasis on sequential recommendation, multimodal learning, and integrating large language models with traditional recommendation approaches. His work bridges the gap between theoretical machine learning and practical applications across multiple domains including e-commerce, music, and healthcare. McAuley has published extensively in top-tier conferences including NeurIPS, ICML, KDD, SIGIR, and ACL, with his most recent work exploring the intersection of large language models and recommendation systems. His publications reveal a strong trend toward multimodal approaches that combine text, vision, and audio for more comprehensive understanding and recommendation. He has received significant research funding from major technology companies including Google, Amazon, Facebook, Adobe, and Samsung, as well as government agencies like the National Science Foundation and Department of Defense. His work has practical applications across multiple industries, with a focus on improving user experience through better personalization. McAuley advises numerous PhD students who have gone on to successful careers at leading technology companies and academic institutions. His former students include Wang-Cheng Kang and Jianmo Ni at Google DeepMind, Chris Donahue and Zachary Lipton as assistant professors at CMU, and Ruining He at Google Deepmind.
Robyn Fox is an Associate Lecturer in the School of Education and Tertiary Access at the University of the Sunshine Coast (UniSC), Australia, teaching in Bachelor of Education (Secondary)/Bachelor of Recreation and Outdoor Environmental Studies programs with emphasis on foundational outdoor studies and paddling-based engagement methods. Her educational qualifications are: MAIntEd, Endicott College MA, DipEd, LaTrobe University BA, LaTrobe University Her research centers on sustainability integration and ecological literacy in outdoor education, driven by her planned PhD investigating embedded sustainable practices. She champions experiential learning through natural environments to foster environmental consciousness and climate-responsive pedagogy. Analysis of her 2022-2025 publications reveals dominant themes in climate change education within outdoor contexts, featuring innovative approaches like near-peer teaching and nature journaling while addressing eco-anxiety and Indigenous knowledge systems. Her scholarship consistently advocates for curriculum transformation toward ecological stewardship and climate action. Robyn actively involves students in community initiatives: Collaborated with Thai army and Regent’s School students to rebuild tsunami-damaged homes in Thailand (2004) Established sports programs between Khartoum International Community School and local institutions in Sudan Coordinated orphanage library setup with Luanda International School in Angola Current participant in Alexandra Headland Community Association’s foreshore regeneration projects
Tanja Narancic is an Assistant Professor at the School of Biomolecular and Biomedical Science at University College Dublin (UCD). She is also an academic collaborator at the Bioeconomy Research Centre BiOrbic, where she coordinates multiple research projects among PIs, PostDocs, PhD students, and designs projects proposed by industrial partners. Dr. Narancic earned her PhD in Applied Microbiology from the University of Belgrade, Serbia in 2012, followed by postdoctoral research at the Institute of Molecular Genetics and Genetic Engineering in Belgrade. In 2013, she joined University College Dublin as a Postdoctoral Research Fellow under Prof. Kevin O'Connor, where she investigated microbial metabolic pathways using proteomics, metabolomics, and synthetic biology tools as part of FP7 and H2020 projects. She became a Research Fellow at BiOrbic in 2019 before advancing to her current position as Assistant Professor. Her research focuses on elucidating bacterial metabolism and leveraging synthetic biology tools to exploit bacteria for producing high-value products. Key research areas include: Proteomics, Metabolomics, and Transcriptomics for microbial pathway analysis Metabolic engineering for bioproduction Biocatalysis and enzyme optimization Protein engineering and purification Polyhydroxyalkanoate (PHA) production from waste streams Plastic upcycling and biodegradation technologies Dr. Narancic's publication record demonstrates a strong focus on converting plastic waste into valuable biodegradable materials through innovative biotechnological approaches. Her recent work has centered on developing microbial systems for upcycling polyethylene terephthalate (PET), polyolefins, and other recalcitrant plastics into polyhydroxyalkanoates (PHAs) and other high-value products. She has made significant contributions to understanding the metabolic pathways involved in plastic monomer conversion and has developed engineered strains with enhanced capabilities for plastic upcycling. As a principal investigator, Dr. Narancic leads multiple significant research projects including the Ad Astra Studentship (2023-2028), the UPLIFT project on sustainable plastics for food packaging (2021-2025), and the PROMOFER project (2024-2028) on optimizing PHB production. She also serves as a reviewer for numerous prestigious journals including Enzyme and Microbial Technology, Journal of Applied Microbiology, and Microbial Biotechnology. Her teaching portfolio includes coordination of multiple modules such as Bioprocessing, Metabolism and Disease, and SynBio for Bioeconomy, demonstrating her commitment to educating the next generation of scientists in both fundamental and applied aspects of biomolecular science.
Josiah Hester is Associate Professor of Interactive Computing and Computer Science at Georgia Tech's College of Computing, where he also directs the Center for Advancing Responsible Computing and the Ka Moamoa – Ubiquitous and Mobile Computing Lab . His research focuses on sustainable, battery-free computing systems for health, conservation, and education, informed by his Native Hawaiian heritage. Education: Ph.D. in Computer Science, Clemson University, 2017 B.S. in Computer Science, Clemson University Honors College, 2011 Research Interests: Hester’s group pioneers intermittent computing —devices that harvest ambient energy (solar, radio, thermal, microbial) and operate reliably despite frequent power loss. Applications span: Large-scale conservation sensing with Indigenous communities Battery-free health wearables (smart masks, implantables) Educational tools for sustainable design Carbon-aware IoT and recyclable robotics Recent Work & Trends: His 2024–2025 publications unveil soil-powered sensors, recyclable electronics, and culturally-grounded CS education tools. A consistent theme is co-design with underserved communities and embedding sustainability metrics at every layer—from hardware to curriculum. Scientific Awards: Presidential Early Career Award for Scientists and Engineers (PECASE) – 2025 Alfred P. Sloan Fellowship – 2022 NSF CAREER Award – 2022 Popular Science “Brilliant 10” – 2021 3M Non-Tenured Faculty Award – 2021 Multiple best-paper & best-presentation awards Grants & Teams: Hester’s lab is supported by >$50 million in active funding from NSF, NIH (ARPA-H), DARPA, DoD, Sloan, VMware, and 3M. He leads interdisciplinary teams on projects such as: $35 million ARPA-H bioelectronics initiative for diabetes and cancer $5 million NSF “Coastlines and People” Hub for Manoomin conservation $2 million NSF-DELPHI sustainable edge device design Laboratory & Mentorship: The Ka Moamoa Lab (named with Hawaiian meaning “lamp of the moamoa fish”) hosts graduate, undergraduate, and post-doctoral researchers. Hester actively recruits Native and Indigenous students and has mentored award-winning advisees such as Nivedita Arora (ACM Doctoral Dissertation Award 2024).
Professor Kim Eun-hee is a faculty member in the Department of Defense Systems Engineering at Sejong University, specializing in advanced radar technologies and signal processing. Her work bridges theoretical research and practical applications in defense systems. Ph.D. in Mechanical Engineering (2004), KAIST M.Sc. in Engineering (1996), KAIST B.Sc. in Precision Engineering (1994), KAIST Her research focuses on radar system design, including airborne active phased array radar, automotive radar, broadband noise radar, and over-the-horizon radar. She explores waveform optimization, MIMO architectures, and signal processing algorithms to enhance radar performance in complex environments. Publications highlight her expertise in MIMO radar configurations, Doppler-insensitive waveforms, and machine learning integration for signal analysis. She leads industry-academic collaborations with organizations like Hanwha Systems and LIG Nex1. She contributes to technical committees, including the Sensor and Signal Processing Division of the Korean Society of Military Science and Technology. Her laboratory (Defense Radar Technology Laboratory) focuses on radar design, signal processing, and sensor integration.
Ming Yin is an Associate Professor in the Department of Computer Science at Purdue University. Her research bridges human-computer interaction, applied artificial intelligence, computational social science, and behavioral sciences. She focuses on leveraging human behavior data to design intelligent systems that balance machine efficiency with human understanding, trust, and engagement. Education : PhD in Computer Science (Harvard University, 2017), B.E. in Computer Software (Tsinghua University, 2011) Previous Roles : Postdoctoral researcher at Microsoft Research New York City (2017–2018) Teaching : Courses on AI, Human-AI Interaction, Data Mining, and Human-Centered Computing Research Interests center on social computing, crowdsourcing, human-AI interaction, and ethical AI. She employs experimental and computational methods to study how human behavior can improve AI systems' design, fairness, and user trust. Her work has significant implications for gig economy platforms, decision support systems, and algorithmic accountability. Scientific Contributions include over 15 recent articles in top venues like CHI, IJCAI, and ACL. These works explore topics such as LLM-driven trust calibration, adversarial social influence, and ethical AI design. Her research has been recognized with the NSF CAREER Award Siebel Scholar (Class of 2017) Multiple Best Paper and Honorable Mention Awards at CHI, CSCW, and HCOMP Teaching Expertise spans courses like Introduction to Artificial Intelligence (CS 471), Human-AI Interaction (CS 592-HAI), and Data Mining (CS 573). She emphasizes project-based learning and designing systems for real-world problems, such as "learning in a new era" in her 2025 HCI course.
Matthew Kay is an Associate Professor in the Department of Communication Studies at Northwestern University's School of Communication, with a secondary appointment in Computer Science. He serves as Co-Director of Graduate Studies for the PhD in Technology and Social Behavior program. His research focuses on human-computer interaction and information visualization, specializing in uncertainty communication, usable statistics, and personal informatics. He employs mixed-method approaches including behavioral analysis, interactive system development, and visualization technique evaluation to address real-world data interpretation challenges. Analysis of his recent publications reveals dominant themes in visualization literacy development, uncertainty representation for decision-making, and health informatics applications. His work consistently bridges theoretical frameworks with practical implementations, particularly in educational assessment tools and election forecast visualizations. Professor Kay co-directs the Midwest Uncertainty Collective (MU collective), a research group advancing uncertainty communication methodologies. Previously faculty at the University of Michigan School of Information, he maintains active contributions to visualization tool development including the ggdist R package for uncertainty visualization.
Naresh R. Shanbhag is the Jack Kilby Professor in the Department of Electrical and Computer Engineering and the Coordinated Science Laboratory at the University of Illinois at Urbana-Champaign. He serves as Director of the Systems on Nanoscale Information fabriCs (SONIC) Center and held the D.J. Gandhi Distinguished Visiting Professorship at IIT Mumbai from 2015-2020. Previously, he was a visiting faculty member at National Taiwan University (2007) and Stanford University (2014). Dr. Shanbhag received his doctorate from the University of Minnesota (1993) in Electrical Engineering. From 1993 to 1995, he worked at AT&T Bell Laboratories as the lead chip architect for AT&T's 51.84 Mb/s transceiver chips over twisted-pair wiring for Asynchronous Transfer Mode (ATM)-LAN and very high-speed digital subscriber line (VDSL) chip-sets. His research focuses on the design of energy-efficient machine learning, communications, and signal processing systems on resource-constrained embedded platforms. He explores fundamental trade-offs between energy efficiency, latency and accuracy of decision-making systems implemented in nanoscale technologies, with applications to computer vision, biomedicine, automatic target recognition, and imaging. His work spans four primary focus areas: Resource-efficient Machine Learning for the Edge, In-memory Computing (IMC), Energy-efficient High Data Rate Communications, and Shannon-inspired Statistical Error Compensation (SEC). Analysis of his recent publications reveals a strong emphasis on in-memory computing architectures (SRAM, MRAM, RRAM) for machine learning acceleration. His work consistently addresses energy-accuracy trade-offs, with increasing attention to security aspects of hardware implementations and applications to MIMO signal processing and edge AI systems. His research demonstrates a progression from theoretical foundations to practical silicon implementations. 2024 Semiconductor Research Corporation Innovation Award 2018 Semiconductor Industry Association/Semiconductor Research Corporation University Researcher Award 2018 IEEE International Symposium on Circuits and Systems Best Paper Award 2006 IEEE Fellow 1996 National Science Foundation CAREER Award Professor Shanbhag has mentored over 50 graduate students who now work at leading technology companies including Qualcomm, Amazon, Nvidia, Intel, and Apple. His research has been generously supported by the National Science Foundation, DARPA, AFRL, Semiconductor Research Corporation, Texas Instruments, Sandia National Laboratories, and industry partners including IBM, GlobalFoundries, and Intel Corporation. He led the Alternative Computational Models research theme (2006-2012) and was the founding Director of the SONIC Center (2013-2017), a 5-year multi-university center funded by DARPA and SRC. Currently, he leads research themes in the SRC and DARPA funded JUMP 2.0 Program's Center for Co-Design of Cognitive Systems and the Center for Ubiquitous Connectivity, and in the NSF IUCRC Center for Advanced Semiconductor Chips with Accelerated Performance (ASAP). As Director of the Systems on Nanoscale Information fabriCs (SONIC) Center, Professor Shanbhag leads a multidisciplinary team exploring novel computing paradigms for the nanoscale era. His group has benchmarked an extensive collection of in-memory computing and digital accelerator IC designs, maintaining a publicly available IMC benchmarking repository of metrics extracted from published IC prototypes. His research philosophy integrates concepts from information theory, statistical signal processing, detection and estimation, VLSI architectures, and digital and analog integrated circuits to develop energy-efficient systems from algorithms to silicon implementations.
Takeshi Ikenaga is a Professor at Waseda University’s School of Fundamental Science and Engineering and Graduate School of Information, Production and Systems . He earned his Ph.D. in Information & Computer Science from Waseda University in 2001, following B.E. and M.E. degrees in Electrical Engineering (1988–1990). His career spans roles at NTT LSI Laboratories (1990–2002), Kitakyushu Foundation for Advancement of Industry, Science and Technology (FAIS) (1999–2002), and visiting researcher at the University of Massachusetts (1999–2000). Research Interests : Application-specific SoCs for video/image processing, including compression (H.264/AVC, H.265/HEVC), filters (super-resolution, noise reduction), recognition systems (feature detection, object tracking), and communication (UWB, LDPC). He also works on many-core processor design, ultra-low-delay vision systems, and sports analytics (volleyball, figure skating) with real-time 3D pose estimation and ball tracking. Awards : Recipient of the Furukawa Sansui Award (Waseda University, 1988) IEICE Research Encouragement Award (1992) Multiple Best Paper/Presentation Awards (2006–2022) at conferences including DAC/ISSCC, LSI IP Design, ISOCC, ISPACS, and CVIT APSIPA Distinguished Lecturer Certificate (2015) Waseda University Presidential Teaching Award (2020)
Sean Foley is a Professor of Applied Finance at Macquarie University, specializing in Fintech, Cryptocurrencies, Trading, and Market Design. He leads the Decentralized Assets division at the Digital Finance Cooperative Research Centre (DFCRC), bridging academia, industry, and government. His research focuses on blockchain applications like automated market makers, DeFi protocols, and stablecoins. Education: PhD in Finance from the University of Sydney (2014), focusing on 'The Impact of Regulation on Market Quality'. Research Interests: Decentralized finance (DeFi) systems Cryptocurrency market dynamics and regulation Market microstructure and liquidity provision Energy market crises and policy Regulatory frameworks for financial markets Key Projects: Leading the DFCRC's Industrial PhD Scholarships (2021–2031), mentoring students like Arvind Rangarajan and Juuso Artturi Itkonen. Research on Australia's National Electricity Market (NEM) suspension and energy policy. Awards: Best Paper Award at the Cryptocurrency Conference (2019) Philip Brown Prize for Best Australian Paper (2021) Exceptional Research Prize (2019) Advising & Grants: Supervised over 10 PhD students through DFCRC scholarships. Secured $181 million for the Digital Finance CRC. Lead applicant in the Gunns Ltd shareholder class action. Labs/Teams: Head of Decentralized Assets at DFCRC, collaborating on policy and technology. Co-researcher on 'Electricity Markets in Crisis' and cryptocurrency illicit use studies.
Prof. dr. Nico Van de Weghe is a full Professor of GIScience at the University of Ghent (UGent), affiliated with the CartoGIS research unit. His work bridges computer science, social science, and natural science through geospatial information studies, focusing on enabling machines to reason spatially (GeoAI). Since 2004, he has specialized in knowledge-based AI, particularly spatiotemporal reasoning and moving object analysis, with applications in animal behavior, criminology, healthcare, mobility, and sports. Van de Weghe's research emphasizes hybrid GeoAI systems combining knowledge-driven and data-driven approaches. Keywords include GeoAI, GIScience, Spatiotemporal Analysis, Moving Objects, and Data Mining. Recent publications highlight urban road network analysis, hybrid trajectory modeling, BIM semantic enrichment, and cycling safety studies using virtual reality.
Prof. Eva-Marie Meemken is an Assistant Professor at the Department of Environmental Systems Science, ETH Zürich. Her research focuses on sustainability goals in global food systems, analyzing policies and institutional arrangements related to poverty reduction, gender equality, and food security in lower-income countries. She leads the Food Systems Economics and Policy Group, affiliated with the Institute for Environmental Decisions (IED), Institute of Agricultural Sciences (IAS), World Food System Center (WFSC), and ETH4D. Education: PhD Agricultural Economics (summa cum laude), University of Göttingen (2017) MSc Agricultural Economics, University of Hohenheim (2013) BSc Agricultural Sciences, University of Kassel-Witzenhausen (2011) Professional Experience: Since 2022: Assistant Professor (tenure track), ETH Zürich 2020–2022: Assistant Professor, University of Copenhagen 2019–2020: Postdoc, Cornell University 2018–2019: Postdoc, University of Minnesota 2017–2018: Postdoc, University of Göttingen Research Interests: Her work explores diverse actors in food systems (farmers, cooperatives, companies) and their roles in sustainable development. Current research emphasizes policy design for decent work, gender equality, and resilience in global agrifood supply chains. Teaching: She teaches the course World Food System in ETH Zürich’s Autumn Semester 2025.
Takako Fujioka is an Associate Professor of Music at Stanford University, affiliated with the Center for Computer Research in Music and Acoustics (CCRMA). Her research focuses on the neural mechanisms underlying auditory perception, auditory-motor coupling, and music-supported therapy for neurorehabilitation. She holds a Ph.D. in Physiology from the Graduate University for Advanced Studies, Japan, and M.Sc./B.Eng. degrees in Electrical Engineering from Waseda University. Her work combines neurophysiological techniques such as MEG and EEG to study brain plasticity in development, aging, and stroke recovery. Notable contributions include investigating how music influences motor and cognitive recovery in stroke patients, as well as exploring the neural basis of musical perception through rhythmic synchronization and pitch discrimination studies. Supported by awards from the Canadian Institutes of Health Research during her postdoctoral work at the Rotman Research Institute, her research bridges clinical neuroscience and music cognition. Dr. Fujioka’s expertise spans auditory neuroscience, neurorehabilitation, and technology-assisted music therapy. She has pioneered studies on tactile mapping for cochlear implant users and networked music performance systems, emphasizing cross-modal perception and human-technology interaction. Her findings contribute to both theoretical understanding of auditory processing and practical applications in medical and educational settings. Awards: Canadian Institutes of Health Research Awards (postdoctoral phase) Labs/Teams: CCRMA, Stanford Music Perception Laboratory, Rotman Research Institute collaborations Key Themes: Neuroplasticity, Music-Mediated Rehabilitation, Auditory-Motor Integration, Multisensory Processing Her recent work examines aging-related changes in binaural hearing and the role of beta/gamma oscillations in rhythmic processing. She advocates for translational research that connects neural mechanisms with real-world therapeutic interventions.
