Yang (Gilbert) Ye is an Assistant Professor in the Department of Civil and Environmental Engineering at Northeastern University, joining in January 2025. His research focuses on human-AI/robot teaming, automation in engineering, and assistive technologies, with a particular emphasis on human-centric robotics and sensorimotor processes. He holds a PhD in Civil Engineering from the University of Florida (2024), advised by Dr. Eric Jing Du. **Affiliations**: Member of ASCE, IEEE, and HFES. His work integrates VR/AR, robotics (e.g., drones, exoskeletons), and AI to enhance civil engineering workflows and workforce training. He leads the Ye Lab, actively recruiting PhD students and postdocs with coding experience (Python/C++/C#) and backgrounds in engineering or computer science. **Key Research Themes**: Human-robot interaction, construction automation, exoskeleton training, and delayed feedback mitigation in teleoperation. Over 20 peer-reviewed publications in journals like ASCE JoCEN, IEEE Access, and Advanced Engineering Informatics. **Lab Opportunities**: PhD/postdoc applicants require strong academic records (GPA ≥3.5) and coding skills. Undergrad/master students can apply for thesis/research roles. Funding covers tuition, insurance, and stipends.
Gregory D. Erhardt is an Associate Professor of Civil Engineering at the University of Kentucky and serves as Associate Director of the T-SCORE Center, a multi-university consortium advancing public transit strategies. He holds a PhD from University College London’s Centre for Advanced Spatial Analysis, with prior experience in transportation planning across public and private sectors. His research focuses on transportation forecasting, big data applications, and evidence-based policy decisions, particularly addressing the impacts of emerging mobility technologies like ride-hailing on urban systems. Erhardt’s work emphasizes improving forecast accuracy and advocating for gender equity in engineering. He has been recognized with awards such as the Transportation Research Board’s Certificate of Appreciation and the Chan Wui & Yunyin Rising Star Fellowship. Education: PhD (University College London), M.S. (Northwestern University), B.S. (Cornell University). His research integrates activity-based travel models with big data to evaluate infrastructure investments and mobility trends. Key projects include analyzing public transit ridership decline, ride-hailing effects on congestion, and TNC impacts on urban transportation systems. Current initiatives include developing multi-agent simulation frameworks for on-demand transit systems. As a Hans Fischer Senior Fellow at the TUM Institute for Advanced Study, he collaborates on travel behavior modeling. His advocacy for diversity includes leading 'Advocates and Allies' training to promote gender equity in engineering. Erhardt’s publications span journals like Transportation Research Part A and Science Advances , with a focus on policy-relevant transportation analytics.
Daniele Loiacono is an Associate Professor at Politecnico di Milano's Department of Electronics, Information, and Bioengineering (DEIB), affiliated with the Artificial Intelligence and Robotics Lab (AIRLab). His research focuses on interdisciplinary applications of Artificial Intelligence, Machine Learning, and Deep Learning in medical imaging, radiation therapy, and procedural content generation for games. He leads projects in synthetic image generation for radiotherapy quality assurance, automated treatment planning, and bias analysis in medical AI systems. Key research areas include medical image synthesis using GANs, radiation therapy optimization, and algorithmic game design. His contributions span clinical applications such as total marrow irradiation (TMI) planning and lymph-node segmentation, alongside innovations in shader generation and interactive evolutionary tools for game development. Loiacono collaborates on multi-center studies to validate AI-driven workflows in healthcare and has pioneered methods combining lean Six Sigma with machine learning for treatment process improvement. His work bridges clinical medicine and computer science, addressing challenges in radiation oncology, anatomical imaging, and procedural content automation. The AIRLab serves as a hub for his research, integrating AI advancements into real-world medical and engineering solutions.
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.
Ali Mostafavi is a Professor in the Department of Civil and Environmental Engineering at Texas A&M University, with a joint faculty appointment in Computer Science and Engineering. His research focuses on urban resilience, complex systems, disaster informatics, and applied artificial intelligence. Educational background: Ph.D., Civil Engineering, Purdue University (2013) He leads the UrbanResilience.AI Lab and can be contacted at DLEB 808I, phone 979-845-4856.
Allen L. Robinson is a Professor and Dean of the Walter Scott, Jr. College of Engineering at Colorado State University (CSU). Previously, he held leadership roles at Carnegie Mellon University, including Head of the Department of Mechanical Engineering (2013-2021) and Director of the EPA-funded Center for Air, Climate, and Energy Solutions (CACES, 2016-2022). He also served as Director of CMU-Africa (2021-2023) and President of the American Association for Aerosol Research (2016-2017). Education: Ph.D. in Mechanical Engineering, University of California, Berkeley (1996) B.S. in Civil and Environmental Engineering, Stanford University (1990) Research Interests: Focuses on emissions from energy systems, air quality, climate change, and public health. Explores policy analysis and decision-making, with teaching experience in thermodynamics, atmospheric chemistry, and air quality engineering. Awards: 2020 David Sinclair Award, American Association of Aerosol Research 2020 University Professor, Carnegie Mellon 2020 Distinguished Professor of Engineering Award, Carnegie Mellon 2015 ASCENT Award, American Geophysical Union Advising & Grants: Led major initiatives like CACES and contributed to global programs like CMU-Africa. His work bridges academia and policy, addressing environmental equity and urban pollution. Labs & Teams: Spearheads the Atmospheric Science and Chemistry mEasurement NeTwork (ASCENT), advancing ground-based air quality monitoring.
Dr. Adnan Rajib is an Assistant Professor of Civil Engineering at The University of Texas at Arlington, leading the H2I Lab (Hydrology & Hydroinformatics Innovation Lab). His research focuses on large-scale hydrology, water quality modeling, and integrating artificial intelligence with remote sensing data to address climate change impacts on water resources. He actively advises doctoral, master's, and undergraduate students in projects related to flood resilience, wildfire hydrology, and nature-based solutions. Dr. Rajib has secured significant grants from NASA, NSF, and USDA, totaling over $4 million, including a major NASA initiative to predict wildfire effects on freshwater supplies and a DOE-funded Coastal Bend Climate Resilience Center. His work spans collaborations with international organizations like the United Nations University and The Nature Conservancy. Key contributions include global studies on floodplain alterations, wetland-mediated nitrate reductions, and the development of cyberinfrastructure tools for open science. He serves on the editorial board of environmental journals and professional committees, including the American Society of Civil Engineers' Wetland Hydrology Technical Committee. His teaching emphasizes advanced topics in civil engineering and research mentorship, with courses like 'Topics in Civil Engineering' and dissertation advisement. Dr. Rajib's lab integrates cutting-edge hydroinformatics to advance climate resilience strategies for vulnerable communities.
R. Michael Alvarez , Flintridge Foundation Professor of Political and Computational Social Science at Caltech, is a leading scholar in election technology, political methodology, and machine learning applications in social science. Affiliated with the Caltech/MIT Voting Technology Project , the Social and Decision Neuroscience Program , and the Resnick Sustainability Institute , his work bridges technology and democracy. Education: B.A. from Carleton College, Ph.D. from Duke University Academic Career: Caltech faculty since 1992 His research spans: Election Integrity : Monitoring election security, fraud detection, and ballot systems Computational Social Science : Applying machine learning to voter behavior and policy analysis Climate Policy : Examining public attitudes and behavioral interventions for sustainability Online Behavior : Analyzing toxicity in gaming and social media dynamics Key article trends show focus on election forensics (2025 Nature Climate Change study), game toxicity analysis (2025 CHI Play paper), and LLM applications in social science. His students include Jacob Morrier, Mitchell Linegar, and teams of postdocs and undergraduates in Caltech's SURF program. Scientific recognition includes: Google Cloud Research Innovators Class of 2022 Co-editor of multiple academic series including Cambridge Elements in Quantitative Methods
Jung Soo Lim is an Assistant Professor in the Department of Computer Science at California State University, Los Angeles, within the College of Engineering, Computer Science, and Technology. He earned his B.S. from Cal State LA and M.S. and Ph.D. from UCLA, returning to his alma mater as a part-time lecturer in 2014 before transitioning to a full-time assistant professor role in 2019. Education: B.S. (Cal State LA), M.S. (UCLA), Ph.D. (UCLA) His research focuses on Internet of Things (IoT) , Cyber-Physical Systems , Wireless Networking , Software Engineering , and Medical Computing . He has active projects in IoT applications for healthcare, urban safety, and wastewater monitoring, including the Center for Inclusive Computing (CIC) Transfer Pathways Project. Recent publications highlight interdisciplinary work bridging IoT, healthcare diagnostics, and smart city infrastructure. Notable topics include stroke detection algorithms , IoT communication protocols , and sensor-based environmental monitoring . Scientific Awards: Outstanding Senior at Cal State LA (1997) He teaches core computer science courses such as Computer Programming Fundamentals and Analysis of Algorithms, and actively mentors graduate students. His lab focuses on developing embedded systems and IoT solutions for real-world challenges.
Hao Liu is a researcher affiliated with institutions like Chinese Academy of Sciences , Beihang University , and Stanford University . His work spans Computer Science , Artificial Intelligence , and Robotics . Key affiliations: National Space Science Center (Beijing), School of Astronautics (Beihang), Key Laboratory of Pervasive Computing (Tsinghua) Research interests include Machine Learning , Image Processing , Graph Neural Networks , and Wireless Communication Optimization His recent publications focus on: Advanced control systems for fuzzy models Medical imaging via hyperspectral analysis Transformer-based approaches in NLP and vision Quantum-safe and edge computing protocols
Helen Suh is a Professor at Tufts University, jointly appointed in the departments of Civil and Environmental Engineering and Community Health . As an internationally-recognized expert in air pollution health effects, she combines environmental epidemiology , exposure science , and data analytics to investigate how pollutants impact human health. Sc.D. , Harvard University (1993) M.S. , Harvard University (1990) S.B. , Massachusetts Institute of Technology (1985) Her research focuses on three areas: air pollutant impacts on cognitive performance and child development , multi-pollutant health effects , and GIS-based spatio-temporal modeling for epidemiological studies. Recent publications highlight her work on PM2.5 measurement error correction , hormonal disruptions in pregnancy , and machine learning applications in environmental health analysis. Current trends include: Advanced statistical methods for exposure assessment Multi-omics approaches to cardiometabolic health International comparative studies (e.g., Tehran, Puerto Rico) Long-term mortality analysis in Medicare populations Pollution-immune system interactions in vulnerable groups Policy-relevant modeling for air quality standards Helen Suh has served as an Associate Editor for the Journal of Exposure Science and Environmental Epidemiology and advised major U.S. and international health organizations. Her work spans over 150 publications and integrates multidisciplinary team leadership in environmental health science. Her laboratory develops large-scale data analytics tools and spatio-temporal exposure models to support population-level health research. Current projects include air pollution and aging cohorts , urban environmental noise measurement , and epigenetic responses to pollutants .
Rui Pedro Figueiredo Marques is a Professor at the Higher Institute of Accounting and Administration, University of Aveiro, where he teaches Information Systems across technical, bachelor's, master's, and doctoral programs. He serves as course director for the Professional Higher Technical Course in Organizational Informatics and Communication and holds a board position at the Institute of Accounting and Administration, University of Aveiro. As a Full Researcher at GOVCOPP's Competitiveness, Innovation and Sustainability (CIS) group, his work focuses on Information Systems for Business, with recent emphasis on AI, Blockchain, and Business Intelligence applications in auditing and accounting contexts. Marques' academic credentials include a Ph.D. in Computer Science (2014, Universities of Minho/Aveiro/Porto), a Master's degree (2008), and a Bachelor's in Electronics and Telecommunications Engineering (2005, University of Aveiro). He has authored/co-authored over 50 publications, including journal articles, conference papers, and book chapters on topics ranging from ERP systems in auditing to digital transformation in low-density territories. He is editor-in-chief of the International Journal of Business Innovation and actively participates in funded research projects addressing governance, competitiveness, and public policies. His research explores intersections between technology and business practices, with notable contributions to AI in auditing, blockchain's role in financial transparency, and sustainable development frameworks for social economy entities. Notable projects include evaluations of ERP systems' impact on internal audit maturity and frameworks promoting accountability in private social solidarity institutions. Marques' work frequently emphasizes practical applications of technology in audit processes, education, and public sector modernization. He collaborates with institutions like the Portuguese Social Solidarity Sector and has advised on digital transformation strategies for tourism and hospitality industries.
Aurélie Labbe is a Full Professor in the Department of Decision Sciences at HEC Montréal, holding the prestigious FRQ-IVADO Chair in Data Science. Appointed as Co-Scientific Director – Academic Partnerships at IVADO in October 2023, she plays a key leadership role in establishing connections between IVADO and partner universities. Her academic journey includes a PhD in Statistics from the University of Waterloo, a Master's degree in Statistics from the University of Montreal, and dual Bachelor's degrees in Applied Mathematics and Social Sciences from Paris-Dauphine University and Pure Mathematics from Versailles-St Quentin University. Her research spans multiple interdisciplinary domains with a focus on developing advanced statistical and machine learning methodologies for big data analysis. Labbe's work bridges theoretical statistics with practical applications across diverse fields including genomics, neuroscience, transportation systems, and health informatics. She has made significant contributions to kernel methods, matrix factorization techniques, random forest applications, and spatiotemporal data analysis, with publications appearing in top journals across multiple disciplines. Analyzing her recent publications reveals a clear trend toward methodological innovation applied to complex real-world problems. Her work demonstrates expertise in handling high-dimensional data from diverse sources including neuroimaging, transportation networks, and genomic studies. The interdisciplinary nature of her research connects statistical theory with applications in healthcare, transportation safety, and biological sciences, reflecting her ability to develop methods that address domain-specific challenges while advancing statistical methodology. Holder of the FRQ-IVADO Chair in Data Science Member of the Center for Mathematical Research Training Professor Labbe actively mentors the next generation of data scientists, supervising numerous doctoral and master's students. Her supervision portfolio includes 1 doctoral thesis (2023), 4 master's theses (2022-2024), and 32 supervised projects spanning 2019-2025. Her students' work covers diverse applications including transportation safety, healthcare analytics, financial modeling, and environmental analysis. Through her leadership of the FRQ-IVADO Chair in Data Science, she coordinates research activities that integrate mathematical, statistical, and computer science expertise with domain knowledge from various data-generating fields. As Co-Scientific Director at IVADO, Professor Labbe leads efforts to establish connections with faculties and departments across five partner universities, integrating them into IVADO's research and knowledge transfer activities. Her leadership role positions her at the forefront of advancing data science research and applications in Quebec's academic ecosystem.
Markus König is a Professor of Informatics in Civil Engineering at Ruhr University Bochum, where he has been researching and teaching since October 2009. His work focuses on Building Information Modeling (BIM), digital construction technologies, and civil engineering informatics, with significant contributions to the development and implementation of digital methods in German construction industry. Dr. König earned his degree in civil engineering with a focus on applied computer science at Leibniz University Hannover, where he also completed his doctorate on cooperative building planning at the Institute for Building Informatics. He subsequently held a junior professorship for Theoretical Methods of Project Management at Bauhaus University Weimar before joining Ruhr University Bochum. His research spans multiple cutting-edge areas including Building Information Modeling (BIM), construction process simulation, tunneling informatics, infrastructure asset management, and the application of artificial intelligence and computer vision in civil engineering. As chair of the Building Informatics Working Group from 2012-2016, he played a key role in developing the first national BIM curriculum for German universities and serves as editor of the book 'Building Information Modeling: Technological Foundations and Industrial Practice.' Analysis of his recent publications reveals a strong trend toward semantic technologies, digital twins, automated compliance checking, and the integration of AI in construction processes. His work increasingly focuses on information containers, ontology development, and the application of large language models to infrastructure data, reflecting the evolving landscape of digital construction. Dr. König's significant contributions to digital construction have been recognized with prestigious awards: Lower Saxony-Bremen Construction Industry Award (2017) for 'services in the development and introduction of digital construction in Germany' Konrad Zuse Medal (2020) While specific details about his advising and grant activities aren't explicitly mentioned in the provided text, his extensive publication record with numerous co-authors suggests active supervision of doctoral students and research staff. His involvement in multiple collaborative research projects is evident from his publication history. At Ruhr University Bochum, Professor König leads a research group focused on civil engineering informatics, with particular emphasis on BIM, digital construction technologies, and their application across the building lifecycle. His team appears to work at the intersection of computer science and civil engineering, developing innovative solutions for construction process optimization, infrastructure management, and digital transformation of the AEC industry.
Dr. Ulas Bagci is an Associate Professor at Northwestern University's Feinberg School of Medicine, Department of Radiology. He holds courtesy appointments in Biomedical Engineering (BME), Electrical and Computer Engineering (ECE) at Northwestern, and Computer Science at the University of Central Florida. As the director of the Machine and Hybrid Intelligence Lab, his research focuses on AI and machine learning applications in biomedical and clinical imaging. Education: BS: Bilkent University (2003) MS: Koç University (2005) Fellow: University of Pennsylvania (2009) PhD: University of Nottingham (2010) ISTP Fellow: NIH (2012) Research Interests: Dr. Bagci’s work spans artificial intelligence, machine learning, and their integration into medical imaging workflows. His lab develops algorithms for tumor segmentation, radiomics analysis, and ethical AI frameworks in healthcare. Notable projects include large-scale MRI segmentation of cirrhotic livers and predictive models for clinical outcomes in oncology and cardiology. Publications: His recent work emphasizes AI-driven solutions for challenges in radiology, including lung disease detection, pulmonary embolism mortality prediction, and ethical considerations in foundational AI models. His articles reflect a focus on bridging clinical needs with advanced computational methods. Lab & Affiliations: The Machine and Hybrid Intelligence Lab collaborates with the Robert H. Lurie Comprehensive Cancer Center. Research themes include federated learning, medical image synthesis, and AI ethics in clinical decision-making.
