Farnoush Banaei-Kashani is an Associate Professor (Tenured) in the Department of Computer Science and Engineering at the University of Colorado Denver. She also holds an Adjunct Associate Professor position in the Department of Mathematical and Statistical Sciences. As the founder and director of the Big Data Management and Mining Lab (BDLab), she leads multiple GAANN Fellowship Programs, including BDSE (Big Data Science and Engineering), DDC (Data-Driven Cybersecurity), and II (Infrastructure Informatics). She directs the 'Data Science in Biomedicine' MS Track and focuses on data-driven decision systems (DDSs), integrating machine learning and big data analytics into healthcare, energy, transportation, and environmental applications. Education: Details not explicitly provided in the text. Her research spans data management cycles for DDSs, addressing challenges like big data volume, velocity, and variety. Key projects include iWatch (crime surveillance), POCM (mobility monitoring), and GeoSIM (urban texture documentation). She teaches courses such as Machine Learning Systems, Big Data Science, and Data Mining. Publications highlight advancements in sea ice classification, federated learning, proteomic networks, and privacy-preserving AI. Her work is funded by NSF, NIH, DOT, and industry partners like Google and IBM. She has advised numerous students and contributes to academic leadership as editor, conference chair (ACM SIGSPATIAL 2018/2019), and program committee member for venues like SIGMOD and KDD.
Professor Michael C.L. CHAU serves as Professor and Deputy Area Head of Innovation and Information Management at The University of Hong Kong's Faculty of Business and Economics. He also holds the position of Associate Director at the HKU HKJC Centre for Suicide Research and Prevention, and serves on the HKU Senate and Court. His academic journey includes a Ph.D. in Management Information Systems from the University of Arizona and a B.Sc. in Computer Science (Information Systems) from the University of Hong Kong. Dr. Chau's research spans business analytics, artificial intelligence, web mining, fintech, smart health, and security informatics. His work focuses on applying data/text/web mining techniques to business, education, and social domains. He leads the Artificial Intelligence Research Group at HKU Business School, which has secured significant funding from the Hong Kong Research Grants Council, Food and Health Bureau, and other agencies for projects including 'The Invisible Hand in Crowdfunding' and 'Factors Moderating the Predictive Power of Social Media Sentiment on Stock Returns'. His publication portfolio includes over 150 articles in premier journals like MIS Quarterly, JMIS, and IEEE Transactions, with recent work exploring large language models, hate speech detection, and disaster-related social media analysis. His research demonstrates strong interdisciplinary connections across computer science, information systems, and business applications. INFORMS ISS Design Science Award (2020) IEEE ITSS Leadership Award in Intelligence and Security Informatics (2020) AIS Sandra Slaughter Service Award (2016) HKU Outstanding Young Researcher Award (2014) Faculty Research Postgraduate Supervision Award (2020 & 2025) Cited over 9,400 times (h-index = 47) Dr. Chau actively mentors doctoral students and has supervised numerous PhD graduates who now hold academic positions at institutions including Fudan University, Xi'an Jiaotong-Liverpool University, and the University of Maryland. His research grants portfolio demonstrates sustained funding success across diverse areas including blockchain, mental health applications, and social media analytics. The Artificial Intelligence Research Group he leads maintains strong industry connections through projects with Hong Kong Red Cross and the Hospital Authority.
Jaan Masso is an Associate Professor at the University of Tartu, Estonia, where he has been affiliated with the Faculty of Economics and Business Administration since at least 2001. He currently serves as Chair of the department, Head of the Chair of Economic Modelling, and Programme Manager of the Master's programme in Quantitative Economics. His research focuses on applied econometrics, economic development, foreign direct investment, and labor economics, with particular emphasis on Estonia and the Baltic region as catching-up economies. He has published 146 scholarly works with over 23,000 reads and 1,745 citations, demonstrating significant scholarly impact in his field. Masso's research interests span multiple interconnected areas including foreign direct investment effects , productivity analysis , gender wage gap studies , innovation economics , and labor market dynamics . His work often employs rigorous econometric methods to analyze firm-level and regional economic data, particularly from Estonia and other Baltic states. His recent publications (2023-2025) show consistent scholarly productivity across multiple journals, with particular focus on foreign ownership effects, gender pay gaps in academia, FinTech sector development, and innovative methods for measuring firm innovativeness through web data analysis. His scientific contributions demonstrate expertise in analyzing economic transitions in small open economies, with methodological strengths in econometric analysis of firm-level data and innovative approaches to measuring economic phenomena.
Prof. Dr. Mathias Christmann is a faculty member at the Institute of Chemistry and Biochemistry, Freie Universität Berlin , leading the research group in Organic Chemistry . His work focuses on strategic and methodological challenges in synthetic chemistry, particularly in total synthesis, organocatalysis, and renewable resource transformations. Position: Professor Contact: mathias.christmann@fu-berlin.de Location: Takustr. 3, Room 24.16, 14195 Berlin Research Interests include: Natural product-inspired small molecule synthesis for biological pathway modulation Minimizing C-C bond formations through selective functionalization of terpene building blocks Organocatalytic and metal-catalyzed reactions in multistep sequences Flow chemistry applications for scalable and sustainable synthesis Biological evaluation of TRPC channel agonists/antagonists for cancer therapy Publication Trends highlight expertise in total synthesis of complex terpenoids, organocatalysis for stereocontrolled reactions, flow chemistry for late-stage transformations, and TRPC4/5 channel modulation in renal cancer studies. His group pioneers asymmetric desymmetrization , photo-oxidation protocols , and electrosynthesis methods with minimal reagent waste. Advisees include PhD candidates Jan-Hendrik Dickoff , Mayar Elbendary , Nadine Kreidt , Tobias Olbrisch , Kamar Shakeri , and Zhen Wang , focusing on terpene-based drug discovery and catalytic reaction design.
Clark Olson is a Professor in the Division of Computing & Software Systems at the University of Washington Bothell, part of the School of Science, Technology, Engineering & Mathematics. He earned his Ph.D. in Computer Science from UC Berkeley (1994), M.S. in Electrical Engineering (1990), and B.S. in Computer Engineering (1989) from the University of Washington, Seattle. Education: Ph.D. in Computer Science (2017) from University of California, Berkeley M.S. in Electrical Engineering (1990) from University of Washington, Seattle B.S. in Computer Engineering (1989) from University of Washington, Seattle His research focuses on computer vision, robot navigation, and clustering algorithms. He has developed techniques for Mars rover terrain mapping, subspace clustering, and geometric feature matching. His work bridges theory and application in autonomous systems and image analysis. Analysis of his publications reveals expertise in computer vision (8 papers), clustering algorithms (4 papers), and robotics (5 papers). Key subtopics include Mars exploration (3 papers), Hough transforms (3 papers), and probabilistic methods (3 papers). Professor Olson teaches courses ranging from introductory programming (CSS 161-162) to advanced topics in computer vision (CSS 487-587) and algorithm design (CSS 549). He also advises on the CSSE Capstone (CSS 497) projects requiring rigorous prerequisites and structured evaluation criteria.
Prof. Bryan Ford leads the Decentralized/Distributed Systems (DEDIS) lab at EPFL. He focuses on secure decentralized systems, including blockchain technology, privacy, and systems security. He earned his Ph.D. from MIT and held faculty positions at Yale University and EPFL. His work spans distributed consensus protocols, peer-to-peer networking, and privacy-preserving systems. Key projects include QuePaxa (timeout-free consensus), UIA (global connectivity for mobile devices), and MedCo (secure healthcare data sharing). He advises numerous PhD students and contributes to open-source projects like Bitcoin collective signing and privacy networks like Riffle. Education: Ph.D., MIT; Postdoctoral work at Yale Research interests include blockchain scalability, consensus algorithms, and cryptographic privacy. His lab develops systems like TRIP for coercion-resistant voting and F3B to mitigate blockchain front-running. His work on NAT traversal and peer-to-peer protocols (e.g., STUN/ICE) remains foundational in network architecture. He emphasizes practical, auditable security solutions such as CertiKOS and atomic cross-chain transactions (Atom). Notable contributions: CoSi (collective signing), OmniLedger (sharded blockchain), and privacy-preserving protocols like PURBs (Protected Unsealable Recursive Boxes). His lab collaborates with Swiss Post to audit e-voting systems and designs democratic cryptocurrencies like PoPCoin.
Sebastian U. Stich is a tenured faculty member at the CISPA Helmholtz Center for Information Security , where he has been since December 2021. He is also a member of the European Lab for Learning and Intelligent Systems (ELLIS) since June 2020. His research focuses on optimization methods for machine learning, collaborative learning algorithms, privacy and security in distributed systems, and theoretical foundations of deep learning. Stich received his PhD in Theoretical Computer Science from ETH Zurich (2014), following a Master's in Mathematics at the same institution (2010-2014). Prior to CISPA, he worked as a research scientist at EPFL (2016-2021) and held positions at ETH Zurich and ICTEAM/CORE. He has been awarded the ERC Consolidator Grant 2024 , Google Research Scholar Award (2023), and Meta Privacy-Enhancing Technologies Research Award (2022). His team includes Dr. Anton Rodomanov (since 2023), Dr. Rotem Mulayoff (since 2024), Xiaowen Jiang (2023), Yuan Gao (2023), and notable alumni like Anastasia Koloskova (defended 2023). Stich actively organizes workshops (e.g., NeurIPS OPT 2024) and serves on editorial boards ( Journal of Optimization Theory and Applications , Transactions on Machine Learning Research ). He teaches advanced courses in optimization at Saarland University and has held visiting positions at MIT. Key scientific contributions include: Developing ProgFed for progressive federated learning (2021) Creating ProxSkip to accelerate communication in federated settings (2022) Formalizing SCAFFOLD with control variates for FL (2020) Introducing RelaySum mechanism for decentralized learning (2021) Proposing Lookahead-Minmax for GAN training (2021) His work addresses fundamental challenges in: Decentralized optimization theory Communication-efficient algorithms Privacy-preserving model training Handling heterogeneous data distributions Stochastic gradient dynamics Second-order optimization methods
Fabio Miranda is an Assistant Professor at the Department of Computer Science, University of Illinois at Chicago (UIC) . His research bridges visualization , machine learning , data management , and computer graphics to enable interactive visual analysis of large-scale urban datasets . He has developed systems like UrbanRama (for VR navigation) and The Urban Toolkit (a grammar-based framework), which have been deployed in academia, industry, and government agencies. Education: Ph.D., Computer Science , New York University (2018) M.S., Computer Science , Pontifical Catholic University of Rio de Janeiro (2011) B.S., Computer Science , Federal University of Minas Gerais (2009) Research Interests center on urban visual analytics , 3D analytics , and machine learning for accessibility . His work addresses challenges like sunlight access , sidewalk quality assessment , and commuting flow modeling , often collaborating with urban planners, climate scientists, and occupational therapists. Scientific Recognition includes awards at IEEE VIS , SIBGRAPI , and SIGMOD . His research is funded by NSF , NIH , DOT , and DPI , with media coverage in The New York Times , The Economist , and Architectural Digest . Teaching includes courses like CS 524: Big Data Visualization and Analytics and CS 424: Visualization and Visual Analytics . He emphasizes web-based systems, dataflow frameworks, and interdisciplinary collaboration, with open positions for PhD , MSc , and undergraduate researchers .
Professor John W. Edmunds is a leading academic in Infectious Disease Modelling at the London School of Hygiene and Tropical Medicine (LSHTM). Holding a Professor position since 2013 and serving as Dean of the Faculty of Epidemiology and Population Health (2013-2019), he combines mathematical, statistical, and economic models to inform public health policy. His part-time role at the Health Protection Agency (HPA) since 2008 underscores his policy advisory contributions. PhD in Infectious Disease Modelling (Imperial College, 1994) MSc in Health Economics (University of York, 1995) BSc in Biology (Imperial College, 1989) His research focuses on understanding disease transmission and optimizing control strategies. He has pioneered methods integrating social contact surveys , participatory surveillance (e.g., Influenzanet), and economic analysis to evaluate vaccines and interventions. Recent work includes SARS-CoV-2 dynamics , Ebola spatial forecasting , and typhoid vaccine prioritization . His 15 most recent publications highlight social contact patterns (Reconnect, CoMix studies), vaccine impact (HPV, typhoid), and real-time outbreak analytics (Ebola, cholera). Key trends include digital epidemiology , behavioral surveillance , and cross-country modeling for global health. Knighthood (2024) for services to epidemiology Weldon Memorial Prize (2022) for biostatistics contributions FMedSci (2018) for medical science excellence OBE (2016) for public service As an educator, he teaches "Modelling and the Dynamics of Infectious Diseases" and co-organizes "Pandemics: Emergence, Spread and Response" . Current grants include National Institute for Health and Care Research projects on post-pandemic surveillance and Bill & Melinda Gates Foundation funding for polio eradication. He leads collaborations with the Centre for Mathematical Modelling of Infectious Diseases , Vaccine Centre , and Health in Humanitarian Crises Centre , while advising UK and WHO committees on zoonotic influenza , variants , and testing programs .
Professor Petri Kuosmanen is affiliated with Aalto University as a faculty member of the School of Engineering and holds a position in the Department of Energy and Mechanical Engineering and the Mechatronics unit. Doctoral Degree in Engineering and Technology, Helsinki University of Technology (2004) Licentiate Degree in Engineering and Technology, Helsinki University of Technology (1992) Master's Degree in Engineering and Technology, Helsinki University of Technology (1988) His research focuses on Industrial Internet and Rotor Dynamics , with significant contributions to elevator systems , hydraulics , and wastewater treatment plant design . Recent work includes optimizing natural frequencies in rotor systems and developing digital twins for engineering education . Key trends in his 2024 publications include: Rotor dynamics and vibration analysis Smart data validation in industrial IoT networks Cold-climate adaptations for wastewater treatment Automated fiber optics coating mechanisms Energy efficiency in aeration systems As Principal Investigator, he leads projects like DRIVE FORWARD (2024–2027) and GOOD (2021–2024), focusing on electrified mobile machinery. He actively collaborates with networks such as DAAAM International (Chair) and European CLUSTER-university network (Member).
Yuchen Liu is an Assistant Professor in the Department of Computer Science and Department of Electrical & Computer Engineering (by courtesy) at North Carolina State University. He earned his Ph.D. in Electrical and Computer Engineering from Georgia Institute of Technology. His research spans networking, machine learning, and cybersecurity, focusing on wireless systems, digital twins, and networked agentic systems. Research areas: Networking (3D UAV networks, mmWave/THz communication, cybersecurity), Machine Learning (generative AI, LLMs, reinforcement learning), Digital Twins (synchronization optimization, edge caching), Software Development (differentiable simulators, open-source testbeds) His recent publications emphasize neurosymbolic AI, diffusion models for wireless systems, and multi-agent approaches to spectrum sensing. Articles highlight applications in UAV networks, vehicular security, satellite localization, and federated learning defenses. Honors include NSF CAREER (2025), NVIDIA Academic Grant (2025), NCSU Carla Savage Award (2025), and multiple IEEE/ACM Best Paper Awards. Current projects are supported by NSF CNS (#2312138), NSF SaTC (#2350075), and NSF NAIRR Pilot Demonstration (#2506757) grants.
Sushmita Ruj is an Associate Professor in the School of Computer Science and Engineering at the University of New South Wales (UNSW), Sydney. She serves as the Faculty of Engineering Lead for the UNSW Institute for Cybersecurity (IfCyber) and as the Taste of Research (ToR) Coordinator within the School of Computer Science and Engineering. Her academic journey includes previous positions as a Senior Research Scientist at CSIRO's Data61 (2019-2022), Associate Professor at the Indian Statistical Institute, Kolkata, and Assistant Professor at the Indian Institute of Technology (IIT), Indore. Dr. Ruj's primary research interests focus on applied cryptography, post-quantum cryptography, cybersecurity, blockchains, and data privacy. She designs practical, efficient, and provably secure protocols for real-life applications, with particular emphasis on critical infrastructure including smart grids, cloud computing, ad hoc networks, and data sharing frameworks. As quantum technology advances, her work increasingly focuses on developing quantum-safe algorithms to ensure a more secure Internet infrastructure. Her research spans multiple domains including cryptographic key management, proofs of storage, verifiable computation, vector commitments, and privacy-enhancing technologies for cloud and IoT environments. Her recent publications demonstrate a strong trend toward post-quantum cryptography solutions, with particular emphasis on blockchain applications, DNS security, and privacy-preserving protocols for industrial IoT. The research shows increasing focus on practical implementations of theoretical cryptographic concepts, with applications across multiple sectors including finance, healthcare, and critical infrastructure. Her work bridges the gap between theoretical cryptography and real-world security challenges, with growing emphasis on the transition from classical to quantum-resistant systems. Best Paper Award at ACISP 2024 JNCA Best Survey Award (2023) NSW Innovation Award (iAward) Merit Winner (2022) Women in Science Award from CSIRO (2020) ACM Senior Member (2016) IEEE Senior Member (2015) Samsung GRO award (2014) Dr. Ruj has successfully mentored numerous PhD and Master's students, with many of her former students now holding academic positions at institutions like IIT Indore, TU Wien, and CISPA Helmholtz Center. She has secured significant competitive funding including multiple Australian Research Council (ARC) grants, Samsung GRO Award, NetApp Faculty Fellowship, Cisco Academic Grant, and IBM Research grant. Her current research portfolio includes projects on blockchain-based quantum-safe digital medical passports, embedding trust in digital IDs, and resilience of supply chain unstructured data. As Faculty of Engineering Lead for IfCyber, Dr. Ruj plays a key role in UNSW's cybersecurity research initiatives. She has served on editorial boards for prestigious journals including IEEE Transactions on Information Forensics and Security and has held leadership positions in major conferences such as ACISP 2021 and Indocrypt 2020. She was also a member of the working group on "Blockchain For Cybersecurity" for the National Blockchain Roadmap of Australia and the first Blockchain Working group set up by the Reserve Bank of India.
Professor Jean Burgess is a leading scholar in digital media studies, holding positions as Distinguished Professor of Digital Media at Queensland University of Technology (QUT) and Associate Director of the ARC Centre of Excellence for Automated Decision-Making and Society (ADM+S). She is affiliated with the Digital Media Research Centre (DMRC) and School of Communication at QUT. Her work focuses on the social implications of digital platforms, algorithmic culture, and innovative digital methods. Education: PhD (Queensland University of Technology) M.Phil (University of Queensland) B. Arts (Hons) and B. Mus (Hons) (University of Queensland) Research Interests: Burgess explores digital media technologies' societal impacts, platform governance, and algorithmic systems. Her recent work includes studies on GenAI, Instagram's visual culture, and automated decision-making. She co-authored Everyday Data Cultures (2022) and contributes to platforms like The Conversation. Awards: Fellow, Australian Academy of the Humanities Member, ARC College of Experts Recipient of the Vice-Chancellor’s Award for Excellence Grants & Projects: Key projects include the ARC-funded ADM+S Centre, research on Instagram’s machine vision, and studies on algorithmic transparency in advertising. She collaborates with industries like Australia Post and the Australian Centre for the Moving Image. Labs/Teams: Leads the DMRC and ADM+S QUT node, fostering interdisciplinary research on digital media's role in society.
Dr. Jianguo Wang is a Professor in the Department of Earth and Space Science Engineering at York University's Lassonde School of Engineering. He has been a faculty member since 2006 and is a founding member of the Lassonde School. With over 35 years of academic and industrial experience, he specializes in multisensor integration, GNSS technology, and precision engineering surveying. He holds a Dr.-Ing. in Geomatics Engineering from Universität der Bundeswehr München, Germany, alongside Bachelor’s and Master’s degrees from Wuhan Technical University of Surveying and Mapping (WTUSM). His research focuses on advanced data processing methodologies, including Kalman filtering, error analysis, and LiDAR systems. He has authored/co-authored over 60 publications, including textbooks like Error Theory and Foundation of Surveying Adjustment and Foundation of Geodesy . He is a Fellow of Engineers Canada and licensed as a Professional Engineer in Ontario. Education: Dr.-Ing., Geomatics Engineering, Universität der Bundeswehr München (Germany) M.Sc., Surveying Engineering, Wuhan Technical University of Surveying and Mapping B.Sc., Surveying Engineering, Wuhan Technical University of Surveying and Mapping Dr. Wang teaches courses such as Advanced Optimization and Applications , GNSS , and Global Geophysics and Geodesy . He leads the Earth Observation Laboratory (PSE 432), focusing on multisensor integration for navigation and positioning. His work explores innovative solutions for sensor calibration, data fusion, and geospatial applications. Grants & Labs: Active in lab-based research with collaborators like Baoxin Hu, his laboratory integrates GNSS, IMUs, LiDAR, and cameras for precision navigation. His recent work addresses challenges in sensor error calibration, LiDAR point cloud accuracy, and Kalman filter enhancements.
Professor Ruth Holliday holds the position of Professor of Gender and Culture at the University of Leeds since 2006, where she has also served as Director of Studies for the Centre for Interdisciplinary Gender Studies, Director of Research and Innovation, and Director of Recruitment and Admissions for the School of Sociology and Social Policy. Previously, she worked at Staffordshire University and Birmingham City University, and served as a Visiting Professor at the University of Technology Sydney (UTS). Her research expertise spans cultural sociology, body studies, material culture, medical tourism, and gender relations, with a focus on low fertility and East Asian cultural contexts. Her academic qualifications include a PhD in Sociology and a BA in Electronics and Management Science. She has contributed to over 50 articles and 7 books, including the award-winning Beautyscapes (2019), which explored global cosmetic surgery tourism and won the Foundation for the Sociology of Health and Illness Book Prize in 2020. Her work on kitsch aesthetics and visual methodologies has also been influential, particularly in understanding class, gender, and race through taste politics. Ruth’s current research projects include studying low fertility cultures’ impacts on gender identities and a project on the cultural meaning of the penis in gender construction. She teaches modules such as Theorizing Gender and Contested Bodies at the MA level, emphasizing critical approaches to gender and embodiment. Key Projects: ESRC-funded 'Building Capacity in Visual Research' and collaborative work on medical tourism in East Asia and Europe. Awards: 2020 Foundation for the Sociology of Health and Illness Book Prize. Supervision: Active in mentoring PhD students researching the body, intimacy, and low fertility in China and Korea. Her interdisciplinary approach bridges sociology, cultural studies, and visual methodologies, with a commitment to ethnographic fieldwork and global comparative analysis.
