Dr. Yelda Turkan is an Associate Professor in the School of Civil and Construction Engineering at Oregon State University, where she leads research in automation, computer vision, and machine learning for sustainable infrastructure. She holds a PhD from the University of Waterloo and dual BS degrees in Civil Engineering and Geomatics Engineering from Istanbul Technical University. Her work focuses on leveraging lidar, digital twins, and BIM to improve construction operations and decision-making in the built environment. She has secured over $4M in grants from NSF, FHWA, and other agencies, and currently leads the NSF Convergence Accelerator-funded 'Deep Reality' project for AI-driven infrastructure management. Education: Ph.D., Civil Engineering, University of Waterloo, 2012 M.S., Engineering Informatics & Remote Sensing, Istanbul Technical University, 2006 B.S., Civil Engineering (double major in Geomatics Engineering), Istanbul Technical University, 2005/2003 Professional Roles: Vice President, International Association for Automation and Robotics in Construction (IAARC) Chair, ASCE Computing Division Education Committee Associate Editor, ASCE OPEN Journal Her research emphasizes automation in construction quality control, infrastructure inspection via drones and lidar, and immersive education tools using VR/AR. Recent projects include automated curb ramp compliance analysis, wildfire impact modeling, and digital twin development for timber structures. She has published over 80 peer-reviewed articles and actively promotes computing integration in civil engineering education and professional practice.
Erick Guerra is a Professor and Associate Dean for Research at the Stuart Weitzman School of Design , University of Pennsylvania, specializing in transportation planning and urban development. He teaches courses on transportation planning, multimodal systems, and studio projects focused on transit-housing integration in Latin America. Education: Ph.D. in City and Regional Planning, University of California Berkeley Master of Urban Planning, Harvard University B.A. from University of Pennsylvania Guerra’s research examines the interconnections between transportation systems, land use patterns, and travel behavior, particularly in developing cities. His work addresses transportation equity, technology adoption, and public health impacts in urban environments. Recent publications analyze highway expansion economics ( Overbuilt: The High Costs and Low Rewards of US Highway Building , 2025), automated vehicle impacts on pedestrian behavior, speed camera effectiveness, and comparative studies of low-income commuting patterns in the U.S. and Mexico. Research trends highlight his focus on sustainable mobility, policy evaluation, and cross-cultural urban dynamics.
Dr. FARKAS Dávid is an Assistant Professor in the Department of Hydraulic and Water Resources Engineering, Faculty of Civil Engineering, Budapest University of Technology and Economics (BME). His office is located in Building K, basement level, room 12/7, and he holds weekly consultation hours on Mondays from 1–3 pm. Educational contributions include teaching core courses in hydrogeology and groundwater engineering: Groundwater (BMEEOVVMV63) Hydrogeology (BMEEOGMMG62) Infrastructural Design Project (BMEEODHAI41) Research activities concentrate on quantitative hydrogeology, with a special emphasis on karstic groundwater systems, seepage hydraulics, and the safety of flood-protection levees. He couples field investigations in iconic Hungarian cave systems (Buda Castle Cave, Molnár János Cave) with laboratory sandbox experiments and numerical modelling to advance understanding of flow and transport processes in fractured carbonates. Over the past decade his work has evolved from fundamental hydrogeological mapping toward the design and deployment of automated monitoring networks that integrate classical hydrological instruments with modern sensor technologies. This progression is evident in his most recent publications (2024-2025) that document the establishment of high-resolution cave monitoring systems capable of capturing rapid responses to precipitation events. Scientific awards currently listed: none. Advising and grants: no specific student names, grant numbers, or funded project titles are provided in the supplied text. Laboratories and teams: while no dedicated laboratory name is stated, his affiliation with the Department of Hydraulic and Water Resources Engineering implies access to the faculty’s hydraulics and hydro-environmental laboratories, including sandbox and seepage modelling facilities.
Dr. Ugur Turhan is a Senior Lecturer in aviation at UNSW Canberra with over two decades of experience in academic and professional settings. His expertise spans Air Traffic Management, Airport Operations, Aviation Safety, and Human Factors in Aviation. Previously, he served as Assistant Professor at Eskisehir Technical University and Anadolu University, and held a visiting professorship at Embry Riddle Aviation Academy. Dr. Turhan earned his Ph.D. in Civil Aviation Management from Anadolu University. His academic journey includes significant contributions to aviation education and research across multiple institutions in Turkey and internationally. Dr. Turhan's research focuses on critical aspects of aviation safety and efficiency. His work explores human factors in air traffic control, aircraft maintenance procedures, and emergency management in aviation contexts. He has developed innovative approaches to training air traffic controllers using 3D simulation technology and has investigated the relationship between safety culture and operational performance in aviation organizations. His research bridges theoretical frameworks with practical applications to enhance aviation safety standards globally. Analysis of Dr. Turhan's recent publications reveals a strong emphasis on human factors across aviation domains. His work consistently addresses safety management systems, cognitive workload assessment, and maintenance procedures. A notable trend is the integration of neurophysiological measurements with operational data to assess air traffic controller performance. His research also demonstrates growing interest in the application of advanced technologies for improving maintenance documentation and technician performance. Dr. Turhan has secured significant research funding through multiple international projects. His leadership roles include: Researcher and Eskisehir Technical University Coordinator for the FACT project under European Commission HORIZON2020 SESAR call (2020-present) Researcher and Eskisehir Technical University Coordinator for the Skill-UP project under Erasmus+ (2020-present) Researcher and Anadolu University Coordinator for the STRESS Project under HORIZON 2020-SESAR-2015-1 (2016-2018) Researcher and Anadolu University Coordinator for the IMPACT Project under HORIZON 2020-DRS-2014 (2015-2018) Researcher and Anadolu University Coordinator for SECONOMICS project under European Commission FP7 (2012-2015) Researcher for Boeing-sponsored International Project on Aviation Educational Software (2014-2016) Dr. Turhan has supervised multiple doctoral and master's students in aviation-related fields. His doctoral students include Birsen Acikel (2016) who researched flight training airspace complexity and Tarık Güneş (2021) who assessed aircraft maintenance technician competency. His master's students have investigated topics ranging from Turkish airspace flexibility to aircraft maintenance documentation. Dr. Turhan also serves as a valuable resource for prospective PhD students interested in human factors and safety in aviation and air traffic management.
Chinmay Kulkarni is an Assistant Professor at Carnegie Mellon University's Human-Computer Interaction Institute, where he leads the Expertise@Scale lab. His research integrates large-scale data and automation to transform learning, work, and mentoring systems. Education : Ph.D. in Computer Science from Stanford University (recipient of the Arthur P Samuel Award) Previous Affiliations : Microsoft Research, Barcelona Supercomputing Center His research spans: Human-Computer Interaction design for massive collaboration Voice-controlled interfaces and AI tools Future of work in remote/hybrid environments Behavioral economics through tech interventions Creative entrepreneurship support systems Algorithmic feedback in education Recent publications with AI and education focus show strong trends in voice technology, peer feedback mechanisms, and scalable learning platforms. His lab's systems have been used by >100,000 users across 150 countries. Scientific Awards : Arthur P Samuel Award (Stanford thesis award) Advising & Grants : NSF grant recipient US Department of Education funding Office of Naval Research support Departmental fellowship Labs : Directs Expertise@Scale lab developing systems adopted by Coursera and edX. Current research group includes PhD students Yasmine Kotturi, Julia Cambre, Pranav Khadpe and Masters student Sayan Chaudhry.
SangHyung Ahn is a Lecturer at the School of Civil Engineering , University of Queensland (UQ), since 2017. He joined UQ as a postdoctoral research fellow in 2015 after earning his PhD in Civil Engineering (Construction Engineering and Management) from Purdue University, USA. Prior to his academic career, he worked as an assistant manager at Hyundai Engineering and Construction Co., Ltd. (2003-2007) and holds an MBA in international business from Hanyang University and a B.Sc in Civil Engineering from Korea University. Research Focus: Construction process modelling with virtual reality, decision support systems for construction, automation of data-driven simulation modelling, sensor-based operations analysis, and integration of Building Information Modelling (BIM). Teaching: Coordinates undergraduate courses Introduction to Project Management (CIVL3510) and Construction Engineering Management (CIVL4522) . Research Trends: His recent publications highlight interdisciplinary work in transportation engineering, structural design, and AI-driven simulation tools. Key themes include application of machine learning to car-following models, drone-based vehicle identification, and optimization of public transport systems using agent-based simulations. Supervision: Available for supervision, with completed supervision of PhD and Master’s theses on topics such as BIM-LCA integration, pedestrian trajectory analysis, and AI-driven driving behavior models.
Nezihe Merve Gürel is an Assistant Professor in Computer Science at Delft University of Technology (TU Delft), affiliated with the Pattern Recognition & Bioinformatics Group within the Intelligent Systems Department of the Faculty of Electrical Engineering, Mathematics and Computer Science. Her research focuses on developing robust, reliable, and efficient machine learning methods with enhanced reasoning capabilities, bridging theoretical rigor and practical applications. She emphasizes data-centric approaches to improve ML systems. Education: PhD in Computer Science from ETH Zurich, MSc from EPFL (Switzerland). Research Interests: ML robustness, reliability, reasoning, data-centric ML, federated learning, and explainable AI. Her recent work includes certified robustness for retrieval-augmented models and time-efficient learning algorithms. She has contributed to the Journal of Data-centric Machine Learning Research as an executive editor and served as a reviewer for top ML conferences (NeurIPS, ICML, ICLR). She previously held roles at IBM Research, Stanford University's Human-Centered AI Lab, and Westlake Institute for Advanced Study. Her awards include the Generation Google Scholarship and Cisco Research Funding . Scientific Awards : Generation Google Scholarship (2021) Cisco Research Center University Funding Labs & Teams : She leads research in the Pattern Recognition Laboratory at TU Delft and collaborates with international institutions like Stanford and Westlake Institute for Advanced Study.
Dieu Tien Bui is a Full Professor in the Department of Business and IT at the University of South-Eastern Norway (USN) School of Business. His research focuses on Geospatial Artificial Intelligence Machine Learning GIS and Remote Sensing Natural Hazard Modeling Environmental Problems (landslides, floods, soil salinity, biomass) . He has contributed to over 15 recent publications in journals like Science of the Total Environment , Remote Sensing , and Geomorphology , emphasizing hybrid AI models for landslide and flood susceptibility. His work spans Vietnam, India, China, and Iran with applications in climate change adaptation and disaster management. Scientific Awards: Global Highly Cited Researcher PhD Supervision: He has supervised 8 PhD students at institutions including USN, NTNU, and Vietnamese universities.
Jelena Mirkovic serves as Principal Scientist at USC Information Sciences Institute (USC/ISI) and Research Associate Professor at the University of Southern California's Thomas Lord Department of Computer Science. She has held faculty positions at USC since 2010, progressing from Research Assistant Professor to her current role as Research Associate Professor since 2017, while also serving as Project Leader at USC/ISI. Her educational background includes: PhD in Computer Science from UCLA (2003) MS in Computer Science from UCLA (2000) B.Sc. in Computer Science from University of Belgrade, Serbia (1998) Mirkovic's research spans network security, human-centered attacks, and cybersecurity experimentation infrastructure. Her work focuses on critical security challenges including botnets, denial-of-service attacks, IP spoofing, vulnerability scanning, and user-centric privacy. She has pioneered methodologies for security experiments and led major infrastructure projects including the DETER testbed and SPHERE (Security and Privacy Heterogeneous Environment for Reproducible Experimentation). Analysis of her recent publications reveals consistent innovation across multiple security domains. Her work demonstrates strong technical depth in DDoS defense systems (particularly DNS protection), binary vulnerability analysis, privacy-preserving systems, and security experimentation infrastructure. A notable trend is her focus on bridging theoretical security concepts with practical implementation through large-scale testbeds and real-world data analysis. Her significant scientific achievements include: IEEE Senior Member distinction Best paper award at IEEE COMSNETS 2023 for DNS DDoS defense research Mirkovic has secured substantial research funding as Principal Investigator or Co-PI on numerous grants from NSF, DHS, and other agencies. Current major projects include SPHERE (Security and Privacy Heterogeneous Environment for Reproducible Experimentation), DISCERN (Datasets to Illuminate Suspicious Computations), and modernizing DeterLab education infrastructure. She has successfully led multiple REU sites focused on cybersecurity education and workforce development. She directs the STEEL (Security Research Lab) at USC/ISI, which develops innovative security solutions through interdisciplinary research in network security, human factors in security, and cybersecurity experimentation infrastructure. The lab emphasizes practical implementations that address real-world security challenges while advancing theoretical understanding of security systems.
Ryan P. Huang is an Associate Professor in the Computer Science & Engineering department at the University of Michigan, College of Engineering, where he leads the Order Lab. Previously, he was an Assistant Professor at Johns Hopkins CS department from 2017 to 2022. His research focuses on computer systems, particularly operating systems and distributed systems, with emphasis on reliability, efficiency, and defensibility across cloud data centers and mobile devices. Dr. Huang's research interests center on pushing the boundaries of cloud systems availability and observability. His work addresses critical challenges such as gray failures and partial failures in distributed systems, developing principled techniques for failure detection and localization. His research spans multiple thrusts including Panorama for enhanced observability, Watchdog for runtime checking, OmegaGen for partial failure localization, and Narya for predictive failure mitigation. He also investigates energy-efficient mobile systems and system misconfiguration prevention. His recent publications demonstrate a strong trend toward addressing silent failures in distributed systems, with multiple papers accepted to top-tier conferences including SOSP and OSDI in 2025. His work bridges theoretical principles with practical system implementations, focusing on real-world challenges in cloud infrastructure and distributed computing environments. NSF CAREER award recipient Multiple Best Paper Awards (OmegaGen, Argus, LeaseOS) CRA Outstanding Undergraduate Researcher Award honorable mentions for advisees Dennis Ritchie doctoral dissertation award honorable mention Dr. Huang actively mentors PhD students including Yuzhuo Jing, Wanning He, Yuxuan Jiang, and others. His lab has produced graduates who have gone on to faculty positions at institutions like University of Virginia and Boston University. He serves on program committees for major systems conferences including SOSP, OSDI, and NSDI, contributing significantly to the academic community. The Order Lab maintains active research collaborations and regularly publishes in top-tier venues, with multiple papers accepted to SOSP and OSDI in 2025.
Sainyam Galhotra is an Assistant Professor in the Department of Computer Science at Cornell University. His research focuses on developing data science tools for effective and responsible analytics, leveraging techniques from causal inference, data management, theoretical computer science, machine learning, and human-computer interaction to address challenges in trustworthy system design including robustness, explainability, and fairness. Education: Postdoc: University of Chicago PhD: University of Massachusetts Amherst (supervised by Barna Saha) BTech: Indian Institute of Technology Delhi (IIT Delhi) (supervised by Prof. Amitabha Bagchi) Research Interests: Dr. Galhotra's research spans several interconnected areas in data science and artificial intelligence. His work primarily focuses on Responsible Data Science , where he develops methods to ensure that data-driven systems operate fairly and transparently. Within this broad area, his specific interests include: Causal Inference techniques for understanding cause-effect relationships in complex data Algorithmic Fairness approaches to mitigate bias in machine learning systems Explainable AI methods that make black-box models more interpretable Data Management systems for efficient and reliable data processing Entity Resolution techniques for integrating data from multiple sources Trustworthy System Design that addresses robustness, explainability, and fairness His recent publications demonstrate a clear trend toward developing frameworks that combine causal reasoning with practical data management systems, particularly focusing on how to make data-driven decisions more transparent and equitable. The intersection of database systems with fairness considerations appears to be a particularly active area of his research. Scientific Awards: Rising Star in Data Science at the Data Science Institute, UChicago (Oct 2021) Computing Innovation Fellowship Award Recipient (by CRA, CCC and NSF) (Apr 2021) DAAD AInet Fellow (Feb 2021) ACM SIGMOD Entity Resolution Programming Contest – Top 5 finalist (May 2020) Most reproducible paper award in SIGMOD 2018 and 2019 (Jun 2019) First recipient of Krithi Ramamritham Computer Science Scholarship (Jun 2019) Best paper award in SIGSOFT FSE 2017 (May 2017) Dr. Galhotra is actively seeking students to collaborate with on his research projects. His work has been supported by various fellowships and awards, including the prestigious Computing Innovation Fellowship. He has mentored several students through his research projects, with a focus on developing the next generation of data scientists who can build responsible and trustworthy systems. His research group appears to focus on the intersection of database systems and responsible AI, developing tools like HypeR for causal reasoning, Ver for view discovery, and Nexus for correlation discovery in spatio-temporal data. This work suggests a cohesive research agenda centered around making data systems more transparent, fair, and user-friendly.
Seth Frey is an Associate Professor in the Department of Communication at the University of California, Davis, with affiliate status at Indiana University's Ostrom Workshop and as Research Director at Metagov. His research focuses on computational social science approaches to understanding self-governance in complex social systems, particularly through the lens of online communities as model institutions. Education: Ph.D. in Cognitive Science and Informatics (complex systems), Indiana University, 2013 B.A. in Cognitive Science, UC Berkeley, 2004 Research Interests: Frey specializes in computational approaches to institutional analysis and the cognitive science of strategic behavior . His work examines how communities design governance systems to overcome collective action problems, with emphasis on: Emergent institutional structures in digital commons Policy-as-data through NLP and institutional grammar frameworks Cognitive mechanisms underlying cooperative behavior Design principles for participatory change in online platforms His methodology integrates large-scale data analysis, web-based experiments, and computational modeling across diverse contexts including Minecraft, Reddit, and professional sports ecosystems. Publication Trends: Recent publications (2023-2025) demonstrate a cohesive trajectory toward computational institutional analysis, with increasing focus on NLP-driven policy analysis (e.g., NLP4Gov), decentralized governance architectures (DAOs, multi-level platform governance), and the cognitive foundations of collective action. His work consistently bridges theoretical institutional analysis with practical applications in digital community design, showing particular growth in translating Ostrom's design principles into computational frameworks. Awards: Honorable Mention Award for Best Paper at ACM CSCW 2019 Advising and Grants: Frey mentors students interested in data science applications at the intersection of communication, cognition, and complex systems, emphasizing resourcefulness and intellectual curiosity. His research has secured substantial funding from: National Science Foundation (NSF) NASA Ford Foundation Google Open Source Foundation He actively encourages aspiring graduate students with strong self-directed research skills to explore computational approaches to social phenomena. Labs and Teams: He leads the Computational Communication Lab at UC Davis and co-directs the Institutional Grammar Research Initiative. Through Metagov, he develops the 'Governance API' framework for modular community governance. His past affiliations include Disney Research (Walt Disney Imagineering) where he applied complexity science to theme park systems, and the New England Complex Systems Institute (NECSI). Current collaborations span Ethereum governance, Minecraft server ecosystems, and Colorado's cannabis monitoring infrastructure.
Stefano Grivet-Talocia is a Full Professor at the Department of Electronics and Telecommunications at the Polytechnic University of Turin, where he also serves as Director of the Doctoral School and President of the Doctoral School Council. He is a member of the Interdepartmental Center SmartData@PoliTO - Big Data and Data Science Laboratory, the University Committee for Research, Technology Transfer and Services to the Territory, and the Commission for the Promotion of Library, Archive and Museum Heritage. His academic career spans over two decades at Politecnico di Torino, where he has established himself as a leading researcher in electromagnetic modeling and signal integrity. Grivet-Talocia earned his Laurea degree (summa cum laude) in Electronic Engineering in 1994 and his Ph.D. in Electronic and Communication Engineering in 1998, both from the Polytechnic University of Turin. Between 1994 and 1996, he conducted research at NASA/Goddard Space Flight Center in Greenbelt, Maryland. His educational background laid the foundation for his expertise in electromagnetic modeling, wavelet analysis, and signal processing. His research focuses on behavioral modeling, electromagnetic compatibility, macromodeling, model order reduction, numerical modeling, passivity, power integrity, signal integrity, transmission lines, and wavelets . Grivet-Talocia is particularly renowned for his work on passive macromodeling of interconnect structures, development of the TOPLine technique for transmission line simulation, and pioneering contributions to passivity enforcement algorithms. He has co-authored the first book entirely dedicated to Macromodeling (2016) and developed innovative approaches to waveform relaxation and wavelet-based signal processing. His recent publications (2024-2025) demonstrate continued leadership in model order reduction, with significant contributions to data-driven modeling of linear and nonlinear systems, power integrity analysis, and electromagnetic compatibility. His work spans both theoretical advances in numerical methods and practical applications in circuit design, with strong industry relevance particularly for semiconductor and electronic design automation companies. IEEE Fellow (2018-present) Three Intel SRS Grants (2022-2024) Three IBM SUR Grant Awards (2007-2009) Best Associate Editor Award - IEEE Transactions on Components, Packaging and Manufacturing Technology (2020) Multiple Best Conference Paper Awards (2006-2020) URSI Young Scientist Awards (1999) Ranked among the "top 2% worldwide researchers" (Stanford) since 2019 Grivet-Talocia actively supervises doctoral students including Michele Cusano, Sara Paknezhad Panahi, Antonio Carlucci, and Kun Zhao. He has secured numerous research grants from competitive national calls (PRIN) and commercial contracts with industry partners including Intel, IBM, Nokia, Hitachi, Infineon, and Cadence. His technology transfer activities include co-founding the spin-off IdemWorks (2007-2016), which was acquired by CST in 2016. He also developed the autoCircuits web service for automated circuit problem generation, widely used in electrical engineering education. He leads the EMC Group (Electromagnetic Compatibility) at DET and has been instrumental in establishing the Compact Dynamical Modeling research area. His work has practical applications in high-speed electronics design, with algorithms embedded in commercial tools like IBM PowerSPICE. Grivet-Talocia maintains strong industry connections through his research projects and serves as Associate Editor for IEEE Transactions on Components, Packaging and Manufacturing Technology.
Murat Kantarcioglu is a Professor of Computer Science at Virginia Tech, affiliated with the College of Engineering. He is also a Faculty Fellow at the Commonwealth Cyber Initiative (CCI) and directs the Data Security and Privacy Lab. Previously, he held the Ashbel Smith Professorship at the University of Texas at Dallas. His research focuses on data and AI security, privacy, blockchain, and cybersecurity. He has received notable awards, including the NSF CAREER Award and IEEE Technical Achievement Award, and is a Fellow of AAAS and IEEE. Education: Ph.D. in Computer Science (Purdue University), B.S. in Computer Engineering (Middle East Technical University). Research Interests: Privacy-preserving machine learning and data analytics Adversarial machine learning and cybersecurity Blockchain technology and applications Healthcare data security and genomics privacy Risk and incentive models for assured data sharing Awards and Recognition: NSF CAREER Award AMIA Homer R. Warner Award IEEE ISI Technical Achievement Award Fellow of AAAS and IEEE Distinguished Member of ACM Advising and Labs: Directed over 20 PhD/Master’s students, many in cybersecurity and privacy domains. Founder and director of Virginia Tech’s Data Security and Privacy Lab. Associate at Harvard’s University Data Privacy Lab. Service and Leadership: Extensive program committee roles in top conferences (KDD, AAAI, IEEE ICDE). Former CCI co-chair for IEEE TrustCom. Co-authored influential textbooks on adversarial machine learning.
Dr. Yujie (Julie) Chen is an Associate Professor (on leave) at the University of Toronto's Faculty of Information, affiliated with the Department of Communication, Culture, Information & Technology (CCIT). Her work focuses on digital media's political economy, platform capitalism, and digital labour studies. She authored Super-Sticky WeChat and Chinese Society , analyzing WeChat's societal integration and platform power dynamics in China. Her research critiques how labour is marginalized in datafication discourse, particularly in platform-mediated sectors like ride-hailing (DiDi) and food delivery. Key themes include algorithmic control, worker resistance, and the interplay between technology, state policies, and labour conditions in China. Dr. Chen’s work bridges sociotechnical systems analysis with critical political economy frameworks. Her recent studies explore temporal exploitation in platform labour (e.g., food delivery workers’ time management), gamification of work processes, and the 'digital utility' concept deployed by platforms to justify market dominance. She frequently presents at conferences like AoIR and ICA, emphasizing global platform capitalism’s socio-economic impacts. Dr. Chen is completing a book manuscript examining labour’s erasure in datafication narratives and advocating for analytical frameworks that foreground embodied labour experiences. Her research also intersects with global South labour comparisons, notably between China and the Philippines in platform economies.
