Daeyeon Lee is a Professor in the Department of Chemical and Biomolecular Engineering at the University of Pennsylvania and holds the Russell Pearce and Elizabeth Crimian Heuer Professorship. He leads the Soft Materials Research and Technology (SMART) Lab, focusing on interdisciplinary research in soft materials, microfluidics, and biomedical applications. His work spans gas-encapsulating microcapsules, nanozyme-shelled microrobots, and AI-empowered droplet synthesis. Research Interests : Soft materials, polymer-nanoparticle interactions, microfluidics, targeted drug delivery, and AI-driven manufacturing. Grants : NSF Artificial Intelligence-driven RNA BioFoundry (NSF AIRFoundry), Wellcome Leap contract for lipid nanoparticle research. Scientific Awards : Penn CBE Distinguished Teaching Award, 2022 Outstanding Achievement Award in Nanoscience, Nemirovsky Engineering and Medicine Opportunity (NEMO) Prize. The SMART Lab has produced notable publications in ACS Nano , Advanced Healthcare Materials , and Science Advances , with recent work on biofilm treatment, water harvesting, and RNA-lipid nanoparticle manufacturing. The lab relocated to the Vagelos Laboratory for Energy Science and Technology (VLEST) in 2024 and collaborates with institutions like the Technical University of Munich and Carnegie Mellon University.
Elsayed Issa is an Assistant Professor in the School of Languages and Cultures at Purdue University. Specializing in Computational Linguistics and Arabic, his interdisciplinary research bridges Natural Language Processing (NLP) with Second Language Acquisition (SLA), focusing on conversational AI and speech technology for under-resourced languages. Ph.D. in Linguistics from the University of Arizona (2023) Research integrates NLP, conversational AI, and SLA methodologies Develops tools for computer-assisted pronunciation training (CAPT) Focuses on Arabic dialectology and large language models (LLMs) His work employs Transformer architectures and end-to-end machine learning to enhance language learning systems. Recent projects include ArabiBot development and dialect identification models. He specializes in speech-to-text systems , prosody modeling , and emotional speech analysis for Arabic language learning applications.
Dr. Gabriella Pizzuto is a Lecturer in Robotics and Chemistry Automation at the University of Liverpool's Faculty of Science and Engineering, jointly appointed in the Departments of Computer Science and Chemistry. She leads the Pizzuto Group and joined the university in 2021 after completing her PhD at the University of Manchester. Born in Malta, she obtained her undergraduate degree from the University of Malta. Her research focuses on intelligent robotic systems for laboratory automation, specializing in: Contact-based robot skill learning for chemistry labs Failure recovery methods in experimental environments Safe human-robot collaboration frameworks Physics-constrained machine learning Machine vision for laboratory workflows Her work aims to develop robotic scientists that accelerate material discovery through autonomous experimentation. Publication analysis reveals strong emphasis on robotic manipulation (70%), laboratory automation (60%), and machine learning applications (40%), with recent work showing increased focus on multi-modal sensing and physics-informed learning. Her most frequent collaborators include Prof. Andy Cooper and Prof. Michael Mistry. Awards and Fellowships: Royal Academy of Engineering Research Fellowship (2023-2028) Marie Skłodowska-Curie Doctoral Scholarship EPSRC New Investigator Award (2025) Advising and Grants: Currently supervising 4 PhD students and 2 postdoctoral researchers Principal Investigator: £1.2M RAEng Fellowship for 'Upskilling Robotic Scientists' Co-Investigator: £12M EPSRC AI for Chemistry Hub (AIChemy) Lead Researcher: €8M ERC Synergy ADAM project Recipient of Google DeepMind Research Ready Grant (2024) Leads the Autonomous Robotic Chemistry Lab at Liverpool's Leverhulme Research Centre for Functional Materials. Her group combines expertise in robotics, computer science, chemistry, and engineering to develop next-generation robotic scientists.
Dr. Omkar Prabhakar Dastane is a Senior Lecturer and Director of Postgraduate Studies at the Malaysia School of Business, Monash University Malaysia. He holds a PhD in Business from Curtin University and certifications including Certified Management and Business Educator (CMBE) from CABS, UK, and HRDF-approved trainer status in Malaysia. His research focuses on technological impacts on businesses, digital consumer behavior, and customer value perception, with publications in A-ranked journals like the Journal of Retailing and Consumer Services and Asia Pacific Journal of Marketing & Logistics . He has secured MYR 157,549 in research grants and received notable awards like the Best Paper Awards (2017/2018) and Emerald Literati Award (2024). Dr. Dastane has held leadership roles including Head of MBA Programs and Head of Postgraduate Studies at top-tier institutions. He actively contributes to editorial roles for journals like Arab Gulf Journal of Scientific Research and reviews for SSCI/SCIE-indexed publications. His teaching emphasizes strategic branding and services marketing, integrating AR/VR tools for immersive learning. He has also led educational visits across ASEAN countries. His research interests span metaverse applications in business, immersive technologies, and contemporary consumer behavior trends. Recent work explores AI-driven services, live-stream commerce, and digital transformation's role in achieving UN SDGs. He has advised on over 200 research projects and secured multiple teaching grants including the 2025 Learning & Teaching Grant.
Thomas Demeester is an Associate Professor at the Internet Technology and Data Science Lab (IDLab), Ghent University - imec, Belgium. Appointed as Assistant Professor in 2019, he leads an AI research group focused on health applications and drug design, co-directing the Text-to-Knowledge research cluster with Prof. Chris Develder. His educational background includes: M.Sc. in Electrical Engineering from Ghent University (2005), completed with thesis work at ETH Zurich Ph.D. in Computational Electromagnetics from Ghent University (2009), funded by Research Foundation - Flanders (FWO) Demeester's research spans artificial intelligence with emphasis on deep learning and neuro-symbolic methods. Current tracks include energy-based models (Hopfield Networks, Deep Equilibrium Models), diffusion models for drug design, and clinical reasoning systems. His work bridges NLP, healthcare informatics, and generative AI with strong industry partnerships. Recent publications (2023-2025) reveal strategic expansion from NLP into health-centric AI: BioLORD biomedical encoders (2023), synthetic medical data frameworks (UAI/NeurIPS 2024), and novel diffusion model guidance (ICLR 2025). This evolution demonstrates convergence of generative modeling, clinical data analysis, and protein design. He actively mentors 24 PhD students across diverse AI domains: Current Research: Conversational agents, emotion analysis, clinical reasoning, antibody design, and diffusion model optimization Recent Graduates: Interpretable language models, biomedical semantics, task-oriented dialogue, and social media knowledge extraction Research is supported by imec funding and collaborations with Flemish biotech companies, building on his post-doctoral experience securing media-sector projects. Within IDLab, he co-leads the Text-to-Knowledge cluster driving NLP innovations for healthcare, legal, and economic applications.
Deepak Ganesan is a Professor at the Manning College of Information and Computer Sciences (CICS) at the University of Massachusetts Amherst. His research focuses on low-power sensing and communication, networked systems, and machine learning applied to pervasive health monitoring and societal challenges. PhD, Computer Science, University of California, Los Angeles (2004) MS, Computer Science, University of California, Los Angeles (2000) BTech, Computer Science, Indian Institute of Technology, Madras (1998) Ganesan's work bridges wireless sensor networks, smart textiles, and healthcare applications. He designs ultra-low-power wearable devices for tracking health signals like drug use, smoking, and cognitive performance, often integrating machine learning for robust detection. His research emphasizes societal impact, particularly in aging and Alzheimer's care through the Massachusetts AI and Technology Center for Connected Care (MassAITC) and the Center for Personalized Health Monitoring (CPHM). Recent publications highlight innovations in edge-cloud collaboration, fabric-based sensors, and longitudinal health analytics. His NIH-funded MD2K Center for Excellence and affiliations with the Center for Data Science and Computational Social Science Institute further underscore his interdisciplinary approach. ACM Fellow NSF CAREER Award (2006) IBM Faculty Award (2008) UMass Junior Faculty Fellow (2008) UMass Lilly Teaching Fellow (2009) Best Paper at CHI 2013 Best Paper Runner-up at Mobicom 2014 Honorable Mentions at Ubicomp 2013 Ganesan leads the SENSORS: Wireless Sensor Networks Group and contributes to global initiatives like the Internet of Battlefield Things. His work spans academic research, industry partnerships, and policy development in AgeTech and digital health.
Mohammadreza Karamad is an Assistant Professor in the School of Sustainable Energy Engineering at Simon Fraser University (SFU), with a joint appointment in the Sustainable Energy Engineering department. His research focuses on computational materials discovery, leveraging quantum-mechanical methods (e.g., DFT) and machine learning (ML) to design advanced energy materials for clean technologies like hydrogen storage and catalysis. He holds a Ph.D. from the Technical University of Denmark (DTU) and completed postdoctoral research at Stanford University. His academic background includes leadership roles in the CMD Lab (Computational Materials Discovery), where he explores novel materials for electrochemical energy conversion processes. Key research areas include electrochemistry, heterogeneous catalysis, and material science, with a particular emphasis on CO2 reduction, ammonia synthesis, and sustainable energy storage solutions. Dr. Karamad collaborates with industry and academic partners to advance materials discovery through high-throughput computational screening and AI-driven approaches. He actively seeks motivated students (undergraduate and graduate) to join his research program, focusing on developing next-generation energy materials. His lab is located in room B8220, and he can be reached at mkaramad@sfu.ca. Notable technical contributions include pioneering work on transition metal nitrides for CO2 reduction, single-atom catalysts for ammonia synthesis, and machine learning frameworks for predicting material properties. His research bridges fundamental theory with practical applications, addressing global challenges in sustainable energy and environmental technology.
Pourang Irani is a Professor and Principal’s Research Chair in Ubiquitous Analytics at the University of British Columbia (Okanagan campus), within the Irving K. Barber Faculty of Science’s Department of Computer Science, Mathematics, Physics and Statistics. Previously, he served at the University of Manitoba for 19 years as a faculty member and Acting Associate Dean of Science. His research focuses on Human-Computer Interaction (HCI), Wearable Computing, and Information Visualization, with an emphasis on designing interactive systems for 'anytime, anywhere' sensemaking using emerging technologies like mixed reality and smart devices. He leads interdisciplinary projects such as the NSERC CREATE grant on Visual and Automated Disease Analytics, training data scientists in health analytics. Education: PhD in Computer Science (University of New Brunswick, 2002), supervised by Dr. Colin Ware. Research Interests: Wearable interfaces (smartwatches, smartrings, and AR/VR) Data visualization for health and pervasive systems Persuasive health technologies and data storytelling Mid-air and hands-free interaction techniques Embodied interaction through social robots Recent Work Trends: Articles emphasize innovations in smartwatch interaction (e.g., bezel-to-bezel gestures), tactile visualizations via skin-dragging, and voice assistant-driven health data queries. Projects like Databiting explore transient personal data exploration, while Data Videos focus on narrative-driven health communication. Grants & Leadership: Principal Investigator of NSERC CREATE Visual and Automated Disease Analytics program. Co-leads UBCO’s Digital Transparency cluster. Active in interdisciplinary teams addressing health informatics and HCI challenges. Labs & Teams: Leads a lab developing prototypes in wearable computing, spatial analytics, and immersive technologies. Collaborates with researchers in medicine, engineering, and data science to translate HCI innovations into practical solutions.
Jan Dirk Wegner is an Associate Professor at the University of Zurich, holding the chair in 'Data Science for Sciences' and leading the EcoVision Lab. He previously served as a Postdoc (2012–2016) and senior scientist (2017–2020) at ETH Zurich's Photogrammetry and Remote Sensing Group, following his PhD (with distinction) from Leibniz University Hannover (2011). His research bridges machine learning, computer vision, and remote sensing to address environmental and geoscience challenges, focusing on large-scale environmental data analysis, vegetation monitoring, and climate change mitigation. Education: PhD (with distinction) in Geodesy, Leibniz University Hannover (2011) Postdoc, ETH Zurich (2012–2016) Senior Scientist, ETH Zurich (2017–2020) Research Interests: Machine Learning, Computer Vision, Remote Sensing, Environmental Science, Climate Science, Geosciences, Explainable AI, Uncertainty Quantification, and Applications in Sustainability. The EcoVision Lab develops data-driven methods for global-scale environmental monitoring, including vegetation parameter mapping, flood prediction, forest degradation detection, and AI-driven ecological modeling. Awards: ETH Postdoctoral Fellowship (2012–2016) Science Prize of the German Geodetic Commission WEF Young Scientist Class 2020 (Top 25 globally under 40) Advising & Leadership: Director of the University of Zurich's Doctoral School in Data Science, leading the EcoVision Lab, and coordinating the CVPR EarthVision Workshops. His roles include Vice President of ISPRS Technical Commission II, member of the ETH AI Center, ELLIS, and UN-ETH Partnership. Labs/Teams: EcoVision Lab focuses on interdisciplinary AI applications for environmental challenges, collaborating with NGOs, governments, and industry to translate research into societal impact.
Dr. Sotirios Stathakis is Chief of Physics at the Mary Bird Perkins Cancer Center (2023–Present) and Associate Director of the Medical Physics Division at the University of Texas Health Science Center San Antonio (2017–2022). He holds an Adjunct Professor position at Louisiana State University's Department of Physics and Astronomy (2023–Present). His expertise lies in radiation oncology and medical physics, with a focus on patient-specific quality assurance, dose verification, and advanced treatment techniques like adaptive radiation therapy and SBRT. Education: Ph.D., Medical Physics, University of Patras (2005) M.S., Medical Physics, University of Aberdeen (1997) B.S., Physics (minor in Mathematics and Computer Science), University of Waterloo (1995) Research Interests: Patient-specific quality assurance Daily dose verification Treatment planning techniques Adaptive radiation therapy Stereotactic body radiation therapy (SBRT) Automation and workflow optimization in radiation oncology Publications: Over 20 peer-reviewed articles since 2020, focusing on topics like Monte Carlo simulations, AI-driven beam analysis, and AAPM task group recommendations for IMRT verification. Key themes include improving dose accuracy, equipment validation, and clinical implementation of advanced radiation technologies. Grants & Awards: Not explicitly listed in provided text. Labs/Teams: Collaborates with institutions like Fox Chase Cancer Center, South Texas Veterans Health Administration, and LSU on medical physics research and clinical applications.
Halim Yanikomeroglu is a Full Professor and Chancellor's Professor at Carleton University's Department of Systems and Computer Engineering, part of the Faculty of Engineering and Design. His research focuses on wireless communications, including 5G/6G networks, non-terrestrial systems (HAPS/LEO satellites), MIMO, and cognitive radio. He has supervised numerous graduate students and holds IEEE Fellow status and the Harold Sobol Award. His work integrates machine learning, federated learning, and sustainability into next-generation networks. Affiliations: Carleton University, IEEE Education: Ph.D. (Toronto), M.A.Sc. (Toronto), B.Sc. (Middle East Technical University) Research interests span cellular networks, relay architectures, and energy-efficient systems. He pioneered cell-switching strategies for green networks and contributed to HAPS and UAV-based infrastructure. His recent work addresses NTN integration, AI-driven spectrum management, and 6G innovations. Awards include IEEE Fellow (2017) and multiple Research.com leadership accolades. His 150+ publications span journals like IEEE Transactions and conferences like ICC. Advising over 50 students, he emphasizes interdisciplinary solutions for future wireless challenges.
Vera Liao is a Principal Researcher at Microsoft Research, where she is part of the FATE (Fairness, Accountability, Transparency, and Ethics of AI) group. She will join the University of Michigan Computer Science and Engineering department as an Associate Professor in fall 2025. Her work focuses on human-AI interaction, explainable AI, and responsible computing. Liao has made significant contributions to IBM products such as AI Explainability 360 and Uncertainty Quantification 360 during her time at IBM T.J. Watson Research Center. Dr. Liao received her education from the University of Illinois at Urbana-Champaign and Tsinghua University. Her academic journey has positioned her at the intersection of human-computer interaction and artificial intelligence, with a strong emphasis on creating AI systems that are transparent, accountable, and user-centered. Vera Liao's research primarily centers around human-centered AI explainability and transparency. She investigates how to design AI systems that effectively communicate their capabilities, limitations, and decision-making processes to users. Her work examines the intersection of AI transparency with trust, control, and user experience. Liao has pioneered approaches to bridging the socio-technical gap in AI evaluation and has developed frameworks for contextualized evaluation of explainable AI systems. Her research spans multiple domains including conversational interfaces, data storytelling, and creative work with generative AI. Liao's publications reveal a clear trend toward addressing the challenges of large language models and their impact on human-AI interaction. Her recent work focuses on understanding how uncertainty communication affects user trust, how to design for appropriate reliance on AI systems, and how to create authentic co-creation experiences with generative models. She has been examining the risks in AI-infused information ecosystems and developing methods for human-centered evaluation of language technologies. Her scientific contributions have been recognized with multiple honors: Best Paper Award, Honorable Mention at CHI 2025 (two papers) Best Paper Award at CHI 2024 Best Paper Award, Honorable Mention at FAccT 2023 Best Paper Award, Honorable Mention at HCOMP 2022 Best Paper Award, Honorable Mention at CHI 2021 Best Paper Award, Honorable Mention at CHI 2014 Outstanding Paper Award at IUI 2019 Dr. Liao is an active mentor, having guided numerous research interns from top universities including Cornell, Princeton, CMU, Stanford, and MIT. She serves in editorial roles as Co-Editor-in-Chief of the Springer Human-Computer Interaction Book Series and as an Editor for ACM CSCW. Liao has secured research funding through her work at Microsoft Research and previously at IBM, focusing on projects related to AI explainability, transparency, and responsible AI development. As part of Microsoft Research's FATE group, Liao collaborates with a multidisciplinary team of researchers focused on the ethical implications of AI technologies. Her work bridges the gap between technical AI development and human-centered design principles, ensuring that AI systems are developed with user needs and societal impacts in mind.
Yasmin Kafai is a Professor at the University of Pennsylvania's Graduate School of Education (GSE), Department of Learning Sciences. Her research focuses on computational thinking, AI education, and equitable K-12 computing pedagogy. She has pioneered work on integrating electronic textiles (e-textiles) and participatory design into STEM education to engage youth in critical perspectives of technology. Kafai's recent work emphasizes algorithmic literacy, youth-led auditing of machine learning systems, and bridging technical and societal dimensions of computing. Key research areas include: computational empowerment, AI ethics in education, youth agency in technology design, and culturally responsive computing curricula. Her projects often involve hands-on making activities, such as constructing generative AI models or debugging e-textile systems, to foster both technical and critical understandings. Publications from 2024-2025 highlight trends in youth engagement with generative AI, algorithm auditing frameworks, and the intersection of physical computing with growth mindset practices. She has also explored the role of storytelling methodologies in reimagining computing narratives for marginalized groups. Kafai collaborates extensively with teachers to develop scalable professional development programs addressing equity in CS education. Her work frequently appears in learning sciences and computing education journals, with a focus on practical classroom implementations and systemic educational reforms. Ongoing efforts include designing 'Hour of Code' activities that integrate critical AI literacy and fostering youth as co-designers of ethical technology solutions.
Gregory Crane is Professor of Classical Studies and Computer Science at Tufts University, where he holds the Winnick Family Chair in Technology and Entrepreneurship and serves as Chair of the Classical Studies Department. He also maintains a professorship in the School of Engineering's Computer Science department. Previously, he was Alexander von Humboldt Professor of Digital Humanities at Leipzig University in Germany from 2013-2019. PhD in Classical Philology, Harvard University (1985) BA in Classics, Harvard University (1979) Crane's research bridges traditional classical scholarship with digital technology. His work in classical studies focuses on ancient Greek authors, particularly Thucydides, with two major books published on the subject. Simultaneously, he has been a pioneer in digital humanities, beginning work on digital tools for classics as a graduate student in 1982. He is the Editor-in-Chief of the Perseus Project, which he has directed since 1985, developing morphological analysis systems and overseeing the project's evolution through multiple generations of digital library technology. His recent publications demonstrate a strong trend toward integrating artificial intelligence with classical language studies, developing next-generation digital libraries, and exploring new methods for engaging with classical texts in the digital age. Crane's work increasingly focuses on making ancient languages more accessible through technology, with research spanning digital philology, language learning tools, and corpus-based approaches to historical languages. Winnick Family Chair in Technology and Entrepreneurship Alexander von Humboldt Professor of Digital Humanities Crane has secured substantial research funding from major organizations including the National Endowment for the Humanities, the Andrew W. Mellon Foundation, the National Science Foundation, and Google. His current and recent projects include "Reinventing the study of ancient languages" and "Beyond Translation -- new possibilities for reading in a digital age." He has advised numerous students through senior honors theses and directed dissertation research in Classical Studies at Tufts University. Crane leads the Perseus Digital Library research program, which has evolved through multiple generations of technology to become a leading resource for classical studies. His work has established critical infrastructure for digital classics, including named entity identification systems and morphological analysis tools that have shaped the field of digital humanities.
Kwok Pui-lan is the Dean’s Professor of Systematic Theology at the Candler School of Theology, Emory University. Her work bridges postcolonial and feminist theological frameworks with contemporary social justice issues. She is a prominent author of works including Postcolonial Politics and Theology , Occupy Religion , and Introducing Asian Feminist Theology . Her research focuses on globalization, gender, peacebuilding, and the intersection of theology with race, power, and pedagogy. Dr. Kwok actively contributes to academic discourse through her blog (http://kwokpuilan.blogspot.com) and writings for the Wabash Center, addressing themes such as embodied teaching in digital spaces, anti-racism in academia, and theology’s role in responding to societal crises. Her scholarship emphasizes critical reflection on religious education and the ethical implications of emerging technologies. Her teaching philosophy integrates collaborative learning, arts-based methods, and embodied practices to foster transformative education. She has explored topics like machine learning’s impact on religious imagination and the role of spirituality in pandemic-era learning environments. Dr. Kwok’s work consistently interrogates systems of power and oppression, advocating for marginalized voices in theological discourse. Her contributions to the field include reimagining pedagogical approaches to address contemporary challenges in religious education and social justice advocacy.
