Associate Professor Naseem Ahmadpour is a leading researcher in Human-Computer Interaction (HCI) and Design at the University of Sydney 's School of Architecture, Design and Planning. She directs the Affective Interactions Lab and serves as Associate Dean (Research) and Chair of the EDI Committee . PhD, University of Montreal MSc, Chalmers University of Technology BSc, Bahonar University Her research critically examines the ethical implications of sociotechnical systems in care and work futures, focusing on participatory design with vulnerable populations. She explores immersive technologies like VR for mental health, pain management, and clinical training, while advocating for equity in design practices. Recent work includes 15+ publications (2023-2026) on VR applications, ethical design tools, and sociotechnical critiques. She has received the SOAR Prize (2022-2023) and led grants on VR in clinical education, digital volunteering, and aging technologies. Dr. Ahmadpour supervises PhD students in projects like Collaborative Reflection in Mental Health and Cultural Bias in Digital Design . She contributes to the Design. Think. Make. Break. Repeat methodology handbook and co-leads the VirtX Community of Practice for immersive realities.
Hannu Toivonen is a Full Professor of Computer Science at the University of Helsinki, affiliated with the Faculty of Science and the Department of Computer Science. He leads the Discovery Research Group and is part of the Helsinki Institute for Information Technology (HIIT) and the Finnish Center for Artificial Intelligence (FCAI). He obtained his PhD in Computer Science from the University of Helsinki in 1996 and has held his professorship since 2002. His research spans Artificial Intelligence , Data Science , Computational Creativity , and Data Mining , with applications in generative art, automated journalism, and bioinformatics. His research focuses on: Developing AI systems for creative tasks (e.g., poetry, music, and art generation) Cross-lingual natural language processing and unsupervised learning Ethical and societal implications of AI in media and labor Analysis of his 15 most recent publications (2021–2025) reveals a strong emphasis on computational creativity and AI-driven content generation , with interdisciplinary applications in digital humanities, journalism, and biology. Trends include ethical AI frameworks, human-AI collaboration, and innovative evaluation methods for generative systems. Scientific Awards & Honors: Knight, First Class, Order of the White Rose of Finland (2019) Best Applied Research Award, IEEE ICDM (1998) Honorary Member of TKO-äly (2010) Member of Finnish Academy of Science and Letters He has supervised over 20 doctoral theses and secured ~7 MEUR in grants (e.g., EU projects: Embeddia , Newseye ). He leads the Discovery Research Group and collaborates with institutions like VUB (Belgium) as a Francqui International Professor (2025).
Cesla Amarelle serves as Full Professor and Chairholder of Public Law and Migration Law at the University of Neuchâtel's Faculty of Law. Her academic leadership extends to co-directing the Swiss Center for Migration Law (CDM) and contributing to national research initiatives including the National Center of Competence in Research (NCCR) 'On the Move'. She concurrently holds significant public appointments as Chair of the Institute of European Law at the University of Fribourg and Federal Commissioner for Women's Issues, with recent expert designation to the Federal Round Table on signature collection integrity for 2024. Her academic foundation includes a law degree from the University of Lausanne (1996), LL.M. in European and International Economic Law from the University of Fribourg, and doctoral thesis from the University of Lausanne (2004). Her career progression at the University of Neuchâtel spans assistant professor (2009-2014), extraordinary professor (2015-2016), and full professor positions since 2016, complemented by earlier research roles at Swiss National Science Foundation and University of Fribourg. Professor Amarelle's research centers on migration law frameworks, human rights protections in asylum systems, and constitutional dimensions of European integration. Her work critically examines the intersection of migration governance with digital technologies, climate change impacts, and gender equality. Current projects analyze temporary protection regimes, non-refoulement principles in technological contexts, and the evolving relationship between Swiss migration law and European legal frameworks. Her scholarship consistently bridges theoretical legal analysis with practical policy implementation challenges. Her extensive publication record demonstrates evolving focus from foundational migration law codification toward contemporary challenges including digital discrimination, child rights in emergency contexts, and sustainable finance frameworks. Recent scholarship reflects increasing engagement with technological impacts on migration governance and the humanitarian dimensions of temporary protection systems, while maintaining rigorous analysis of constitutional and European law interfaces. Professor Amarelle actively contributes to academic and public discourse through leadership in the Swiss Center for Migration Law and participation in the NCCR 'On the Move' consortium. Her public service includes significant political roles as Vaud State Councilor for Education (2017-2022) and National Councilor (2011-2017), where she chaired key committees on political institutions and finance while representing Swiss higher education interests nationally. She maintains active engagement with professional associations including the Swiss Conference of Higher Education Institutions and Conference of Directors of Public Education.
Mehrdad Nojoumian is an Associate Professor at Florida Atlantic University's College of Engineering and Computer Science, specializing in Security, Privacy, Trust, and Human-Autonomy Interaction. His research bridges computer science with FinTech and autonomous systems, focusing on cryptographic protocols, blockchain, and IoT security. PhD, University of Waterloo (Computer Science, 2012) MSc, University of Ottawa (Computer Science, 2007) BSc, Islamic Azad University (Computer Engineering, 2002) His research explores privacy-preserving mechanisms in autonomous systems, trust modeling in blockchain, and cross-disciplinary applications of cryptography. Recent work includes patents on adaptive driving modes and ongoing studies on IoT vulnerabilities and autonomous coordination. Notable awards include the Excellence and Innovation in Undergraduate Teaching Award (2023), NAI Induction (2022), and multiple Best Paper Awards . His publications span journals like Information and Computation and conferences such as GameSec and IEEE Blockchain . He mentors graduate students in cybersecurity bootcamps, high school outreach programs, and collaborative research projects funded by NSF , ARO-AFOSR , and AFRL . His lab emphasizes diversity and inclusion, particularly supporting underrepresented groups in STEM.
Ryan Calo is the Lane Powell & D. Wayne Gittinger Professor of Law at the University of Washington School of Law, with joint appointments at the Information School and adjunct roles at the Paul G. Allen School of Computer Science and Engineering. He co-founded the UW Tech Policy Lab and Center for an Informed Public, focusing on technology policy, data privacy, and AI ethics. His research explores the intersection of law and technology, emphasizing AI regulation, surveillance law, and privacy harms. Key themes include legal indeterminacy in tech policy, ethical challenges of autonomous systems, and market manipulation in digital economies. His work spans law reviews, technical journals, and policy reports. Ryan Calo's articles highlight critical gaps in AI governance, surveillance frameworks, and robotics law. His publications address algorithmic bias, cultural responsiveness in AI, and legal implications of autonomous vehicles, with recurring focus on consumer protection, constitutional challenges, and cross-disciplinary policy solutions. Phillip A. Trautman 1L Professor of the Year Award (2014, 2017) Washington Law Review Faculty Award (2019) As a public intellectual, Calo has testified before the U.S. Senate multiple times, including on AI-driven privacy risks. He serves on advisory boards for major tech policy organizations and frequently appears in media discussing AI ethics, data breaches, and constitutional tech regulation.
Prof. Dr. Frank T. Piller is a University Professor and Co-Leader of the Institute for Technology and Innovation Management (TIM) at RWTH Aachen University, where he also serves as Academic Director of the Executive MBA program at RWTH Business School. He leads a research team of approximately 30 doctoral students, 5 postdocs, and over 20 student researchers within the TIME Research Area of the School of Business and Economics. His educational background includes a doctoral degree in Operations Management from the University of Würzburg (1999) and a Habilitation degree from TUM Business School (2004) on "Innovation and Value Co-Creation." Prior to joining RWTH Aachen in 2007, he was a Research Fellow at MIT Sloan School of Management and faculty at TUM Business School. Prof. Piller is recognized as one of the world's leading experts in customer-centered value creation, specializing in mass customization, personalization, and customer co-creation. His current research focuses on how established companies can transform in response to disruptive business model innovations, with particular emphasis on digital transformation (Industry 4.0), AI-augmented innovation, and sustainable business models. He is particularly known for his work on innovation ecosystems, platform-based business models, and stakeholder-oriented technology development. His recent publications demonstrate a clear trajectory toward integrating artificial intelligence with traditional innovation management frameworks, exploring how AI transforms manufacturing systems, innovation processes, and business models. His work increasingly addresses the challenges of digital transformation in established industries while maintaining focus on customer co-creation and mass customization principles. His scientific achievements have been recognized with numerous awards: Co-Creation Award of the PDMA Nomination for "Innovating Innovation" Prize by Harvard Business Review and McKinsey "Lecturer of the Year" by Executive MBA students at TU Munich RWTH Aachen Rector's Prize for Excellent Teaching (since 2010) Grant for innovative "Flipping the Classroom" teaching concept ERC Synergy Grant for SAFER Grid project (2025-2031) Prof. Piller maintains an extensive research network spanning academia and industry. He collaborates with numerous corporations including 3M, Adidas, BASF, EON, J&J, P&G, Siemens, and Vodafone, as well as many technology startups across Europe and North America. As a co-founder, supervisory board member, and investor in innovative startups, he actively transfers research into practice. His research has received significant funding, most notably the prestigious ERC Synergy Grant for the SAFER Grid project. He leads the Technology and Innovation Management Group (TIM) within the TIME Research Area at RWTH Aachen, which comprises over 100 senior and junior researchers working at the intersection of innovation, technology management, marketing, and entrepreneurship. The institute is a leading European research institution for strategic, behavioral, and computer-supported technology and innovation management.
Dr. Chien-Ming Huang is the John C. Malone Assistant Professor in the Department of Computer Science at Johns Hopkins University. He leads the Intuitive Computing Laboratory and is affiliated with the Malone Center for Engineering in Healthcare, Laboratory for Computational Sensing and Robotics, Institute for Assured Autonomy, and Data Science and AI Institute. His research focuses on human-robot interaction, human-computer interaction, and artificial intelligence applications in healthcare and education. BS in Computer Science, National Chiao Tung University (2006) MS in Computer Science, Georgia Institute of Technology (2010) PhD in Computer Science, University of Wisconsin–Madison (2015) Postdoctoral Research, Yale University (2015-2017) Dr. Huang's work bridges human-robot interaction, robotics, and AI to develop technologies that enhance social, physical, and behavioral support for diverse populations. His research includes adaptive robot systems for autism intervention, aging care technologies, and explainable AI frameworks for medical decision support. Current projects focus on end-user robot programming, socially aware navigation, and conversational agents for health management. His publications span major venues like Science Robotics , HRI, CHI, and ICRA, with recent emphasis on robot error awareness, small talk in collaboration, and AI explanation design for healthcare. Dr. Huang has received numerous accolades including the NSF CAREER Award and John C. Malone Endowed Chair. 2022 NSF CAREER Award John C. Malone Endowed Chair 2013 RSS Best Paper Runner-Up 2012 Human-Robot Interaction Pioneer Dr. Huang mentors PhD, postdoctoral, and undergraduate researchers, emphasizing interdisciplinary collaboration and technical rigor. He serves as Associate Editor for ACM Transactions on Human-Robot Interaction and has organized key conferences including HRI and ICMI. His lab develops systems for robotic assistance in surgical training, home healthcare, and educational contexts.
Vinod M. Vokkarane is a Professor in the Department of Electrical and Computer Engineering at the University of Massachusetts Lowell, where he serves as Director of the Center for Smart Cyber-Physical Systems (SCyPS) and Director of Advanced Computer Network Labs. Previously, he was an Associate Professor at University of Massachusetts Dartmouth from 2004 to 2013 and a Visiting Scientist at MIT's Research Laboratory of Electronics from 2011 to 2014. His extensive research portfolio spans multiple domains of advanced networking and cyber-physical systems. Dr. Vokkarane earned his educational foundation with a B.S. from University of Mysore, India (1999), followed by an M.S. (2001) and Ph.D. (2004) in Computer Science from the University of Texas at Dallas. His dissertation focused on optical burst-switched networks, establishing the foundation for his future research trajectory. His research interests center on Cyber-Physical Systems, Network Optimization, Reliability, Smart Grids, and Cyber-Security, with particular expertise in the design, analysis, and modeling of architectures, protocols, and algorithms for ultra-high speed networks including Optical networks, Grid/Cloud networks, and Big-data networks. His work bridges theoretical foundations with practical implementations, often addressing critical challenges in network reliability, security, and efficiency. His research has received significant recognition through numerous best paper awards and substantial external funding. Analysis of his recent publications reveals a clear evolution toward increasingly sophisticated integration of cyber-physical systems with power infrastructure, particularly in the areas of grid resilience and observability. His work has expanded from fundamental optical networking research to address critical infrastructure challenges, with a growing emphasis on machine learning applications for network optimization and power system monitoring. The recent focus on PMU networks, disaster resilience, and cyber restoration demonstrates his strategic pivot toward addressing national security and critical infrastructure protection challenges. UMass Dartmouth Scholar of the Year Award (2011) UMass Dartmouth Chancellor's Innovation in Teaching Award (2010-11) University of Texas at Dallas Computer Science Dissertation of the Year Award (2003-04) Multiple Best Paper Awards including IEEE GLOBECOM 2005, IEEE ANTS 2010, ONDM 2015, ONDM 2016, and IEEE ANTS 2016 Texas Telecommunications Engineering Consortium Fellowship (2002-03) Dr. Vokkarane has successfully mentored numerous graduate students who have contributed significantly to his research projects, with several going on to successful careers in academia and industry. His research has been consistently supported by major funding agencies including NSF, DOE, and USMC, with recent projects totaling over $5 million in funding. Current projects include Unified Post-Disaster Restoration Planning for Cyber-Physical Power Distribution Systems (ONR, $550K), CyberCARE: Northeast University Cybersecurity Center (DOE, $3.5M), and Flexible Spectrum Allocation in Next-Generation Optical Networks (NSF, $350K). He leads the Center for Smart Cyber-Physical Systems (SCyPS) and Advanced Computer Network Labs at UMass Lowell, where his research teams work on cutting-edge problems in network architecture, cyber-physical security, and infrastructure resilience. His labs collaborate extensively with national laboratories and industry partners to translate theoretical advances into practical solutions for real-world infrastructure challenges.
Dongwook Yoon is an Associate Professor at the Department of Computer Science , University of British Columbia , and serves as Director of the SOCIUS Lab . He actively contributes to research in Human-Computer Interaction, Human-AI Interaction, and Virtual/Augmented Reality as a member of the Designing for People (DFP) and CAIDA research clusters. Education : PhD in Computer Science from Cornell University (2017), MS (2009) and BS (2007) in Computer Science from Seoul National University Research Focus : Designing socio-technical systems that bridge the gap between technology and human social processes, with innovations in AR/VR, multimodal interaction, and inclusive design Article Trends show his work spans: Temporal and bichronous learning environments AI self-clones and ethical implications Income inequality in virtual platforms Enhanced multimodal collaboration in VR Eyes-reduced interfaces for situational impairments Speculative participatory design for gig economy challenges Scientific Awards include: Google Academic Research Award (2024) Best Paper Award at CHI 2024 High Impact Award in Educational Technology (2024) CHCCS/SCDHM Graphics Interface Early Career Award (2023) Multiple Honorable Mentions at CHI, DIS, and CSCW Students & Collaborators range from active PhD candidates (Anika Sayara, Yuri Kim) to notable alumni (Thitaree Tanprasert, Ashish Chopra) across his SOCIUS Lab projects. His research receives funding from NSERC , KIST , Adobe , Microsoft , and Google grants.
Laurie Williams serves as a Goodnight Distinguished University Professor in the Computer Science Department within the College of Engineering at North Carolina State University. She co-directs both the NCSU Secure Computing Institute and the NC State Science of Security Lablet, demonstrating deep institutional leadership in cybersecurity research. With over 260 refereed publications, her work establishes her as a prominent figure in software security academia. Her research spans critical areas including software security, agile development practices (particularly continuous deployment), software reliability, and software supply chain security. Williams focuses on practical security solutions addressing modern challenges like malicious dependencies in open-source ecosystems, AI-generated code vulnerabilities, and runtime protection mechanisms. Her work bridges theoretical security principles with industry-relevant applications. Recent publications reveal strong trends toward software supply chain security, with multiple 2024-2025 papers addressing vulnerability exploitability, malicious commit detection, and metrics-driven security control selection. Her research increasingly incorporates machine learning for threat detection while maintaining focus on human factors in secure development practices. IEEE Fellow (2018) National Science Foundation CAREER Award (2004) ACM SIGSOFT Influential Educator Award (2009) Multiple IBM Faculty Awards (2002-2012) NCSU Alumni Association Outstanding Research Award (2015-2016) Williams leads multiple major NSF-funded projects including the $5.7M SaTC Frontiers grant on secure software supply chains and the Science of Security Lablet with $3.6M in DoD funding. Her research emphasizes practical industry impact through collaborations with Cisco and Laboratory for Analytic Sciences. She actively mentors through the NCSU Research Leadership Academy and maintains significant educational outreach in software security. Her laboratory work centers on the Secure Computing Institute and Science of Security Lablet, where her team develops frameworks for vulnerability prediction, supply chain risk assessment, and secure development methodologies. Current projects focus on machine learning integrity, cognitive modeling for security decisions, and empirical analysis of build/deployment logs for anomaly detection.
Esa Ollila serves as Associate Professor in the Department of Signal Processing and Acoustics at Aalto University, Finland, and holds an adjunct professorship in Statistics at the University of Oulu. His academic appointments include Academy of Finland Research Fellow (2010-2015) and prior senior research/lecturing roles at both institutions. His educational background features: M.Sc. in Mathematics, University of Oulu (1998) Ph.D. in Statistics (with honors), University of Jyväskylä (2002) D.Sc.(Tech) in Signal Processing (with honors), Aalto University (2010) Professor Ollila's research centers on statistical signal processing and robust statistical methodologies , with significant contributions to array processing, high-dimensional data analysis, and covariance matrix estimation. His work bridges theoretical statistics with practical applications in radar systems, wireless communications, and big data analytics, emphasizing robustness against outliers and computational efficiency in modern data-intensive environments. Current focus areas include compressed sensing, sparse approximation, and blind source separation techniques. Analysis of his 15 most recent publications (2024-2025) reveals three dominant trends: (1) robust covariance learning for massive random access systems, (2) integrated sensing and communications (ISAC) for 6G networks using advanced beamforming, and (3) geometric approaches to elliptical distributions in statistical inference. His work increasingly incorporates deep learning (GANs, graph neural networks) while maintaining strong foundations in classical signal processing theory. Key recognitions include: Academy of Finland Postdoctoral Fellowship (2004-2007) Academy of Finland Research Fellowship (2010-2015) His research has been supported through prestigious Academy of Finland grants totaling over a decade of continuous funding. Professor Ollila currently leads an active research group at Aalto University, supervising doctoral candidates and collaborating internationally with institutions including Princeton University (where he served as Visiting Post-doctoral Research Associate during 2010-2011). He maintains strong ties with the University of Oulu through his adjunct professorship and has contributed to EURASIP's Special Area Team on Theoretical and Methodological Trends in Signal Processing. The Esa Ollila Research Group focuses on cutting-edge challenges in statistical signal processing, with current projects spanning robust DOA estimation under non-Gaussian noise, covariance matrix learning for massive MIMO systems, and machine learning-enhanced radar-communication integration. The group actively develops open-source tools like the fitHeavyTail R package for heavy-tailed distribution modeling and maintains collaborations with industry partners in wireless communications.
Gary M. Shaw is the Rosemarie Hess Professor and Professor (Research) at Stanford University , with courtesy appointments in the Department of Epidemiology and Population Health and Department of Obstetrics & Gynecology - Maternal Fetal Medicine . He serves as Co-PI of the March of Dimes Prematurity Research Center at Stanford and PI of the California Center for Finding Causes and Preventives of Birth Defects . His research focuses on the Epidemiology of birth defects Gene-environment interactions in perinatal outcomes Nutritional factors in reproductive health . He has developed machine learning approaches for precision parenteral nutrition and predictive models for preterm birth, while investigating persistent metabolomic signatures following hypertensive pregnancy disorders. Shaw's recent work explores Climate change impacts on reproductive health Maternal-fetal immune interactions Epigenetic mechanisms in perinatal disease with applications of multiomics to neonatal intensive care units. As a member of Bio-X and the Maternal & Child Health Research Institute , he contributes to translational research networks while serving as Associate Editor for Birth Defects Research and American Journal of Medical Genetics . He supervises Med Scholar Project student Richard Liang Doctoral co-advisor for Saskia Comess and Richard Liang Master's advisor for Lenae Joe while leading the Division of Neonatology as Associate Chair for Clinical Research (2012-2025). His laboratory work integrates Metabolomic profiling Proteomic analysis Computational modeling Machine learning for biomedical data to advance neonatal care through precision medicine approaches.
Mohit Singh is the Coca-Cola Foundation Professor at the H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology. He previously held positions at Microsoft Research (2011-2016) and as an Assistant Professor at McGill University (2010-2012). PhD in Algorithms, Combinatorics, and Optimization (ACO) at Carnegie Mellon University His research focuses on discrete optimization , approximation algorithms , and convex optimization , with applications to combinatorial optimization, submodular functions, and network design. He has contributed to topics like Sticky Brownian Rounding, integrality gaps, and online adaptive algorithms. His recent work includes theoretical advancements in matroid constraints, dimensionality reduction, and submodular maximization. He has published extensively in top conferences such as FOCS, SODA, ICML, and NeurIPS. He has been recognized with the Coca-Cola Foundation Professorship and served as Director of the Algorithms and Randomness Center at Georgia Tech (2019-2023). He has also held editorial roles and organized key academic workshops like the Bellairs Workshop on Approximation Algorithms (2011). His teaching includes advanced courses on approximation algorithms, combinatorial optimization, and linear inequalities. He has collaborated with institutions such as Microsoft Research and McGill University.
Joshua J. Coon is a Professor at the University of Wisconsin-Madison with appointments in the Department of Biomolecular Chemistry and the Department of Chemistry. He leads the Coon Group, focusing on advancing mass spectrometry technologies for proteomics, metabolomics, and lipidomics. His research addresses fundamental questions in cell biology, including stem cell differentiation, epigenetic regulation, and cancer biomarker discovery. Affiliations : Director of the NIGMS National Center for Quantitative Biology of Complex Systems. Research Emphasis : Instrumentation development, data analysis software, ion chemistry, and biological applications of proteomics. Laboratory : Located in the Genome Center of Wisconsin with a dozen hybrid mass spectrometers, including Orbitrap systems. Collaborations : Long-term partnership with Thermo Fisher Scientific and the Wisconsin Alumni Research Foundation (WARF) for technology commercialization. Training : Mentored 27 Ph.D. students since 2009, emphasizing interdisciplinary research and professional development.
Alexander Russell is a Professor of Computer Science and Mathematics at the University of Connecticut, serving as Director of Graduate Affairs in the School of Computing and Director of the UConn Voting Technology Research Lab. He holds a Ph.D. in Mathematics and an S.M. in Computer Science from MIT, alongside dual B.A. degrees in Mathematics and Computer Science from Cornell University. His research focuses on cryptographic protocols, blockchain security, quantum computing, algorithms, and election auditing. Key areas include consensus algorithms, complexity-theoretic cryptography, and applied cryptography in voting systems. Recent work emphasizes low-variance risk-limiting audits and adaptive security mechanisms for blockchains. Notable contributions span provably secure blockchain protocols (e.g., Ouroboros), election integrity methods, and smartphone-based depression prediction models. His articles address topics like settlement bounds in longest-chain consensus, Byzantine-resilient gossip protocols, and energy-efficient neighbor discovery in mobile networks. Russell advises on interdisciplinary projects at the Voting Technology Research Center and collaborates on grants involving quantum-resistant cryptography and healthcare analytics. His work bridges theoretical computer science with practical applications in secure systems and public infrastructure.
