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Mohammad ZandiView profile

Professor

• Engineering Education
• Energy Engineering & Management
• Smart Manufacturing
• +3 more

Professor Mohammad Zandi serves as Professor of Chemical Engineering Education and Deputy Faculty Director of Education at the University of Sheffield's School of Chemical, Materials and Biological Engineering. With a career bridging academia and industry—including strategic research leadership at Tata Steel on biomass iron-making and algae-based CO 2 sequestration—he drives innovation in sustainable engineering education and industrial digitalization. Educational Background: BSc in Chemical Engineering MSc with Distinction in Advanced Chemical Engineering, University of Bradford PhD in Coal Combustion and Environmental Impacts, University of Sheffield His research centers on three interconnected pillars: Engineering Education (developing inclusive pedagogies and curricula for global student engagement), Energy Engineering & Management (optimizing renewable integration and sustainable systems), and Smart Manufacturing (implementing IoT, AI, and digital twins for industrial efficiency). This triad addresses 21st-century challenges from classroom innovation to heavy industry decarbonization, emphasizing practical solutions for resource-constrained environments. Publications reveal a strategic shift from foundational environmental work (coal ash leaching, biomass characterization) toward educational technology and Industry 4.0 applications. Recent outputs highlight data visualization tools like Wiz for manufacturing analytics and evidence-based approaches to international student success, reflecting his commitment to translating research into scalable educational and industrial practices. Scientific Awards: Award for Excellence in Learning & Teaching, Faculty of Engineering, University of Sheffield (2014) Foxwell Memorial Prize in Fuel Technology, Energy Institute (2005) Professor Zandi's advisory and grant leadership includes: Industrial Projects: Directed Tata Steel initiatives on biomass iron-making (with European steel consortiums) and algae-based CO 2 capture. Educational Innovation: Developed award-winning curricula for grand challenge engineering, supported by IChemE and Energy Institute partnerships. Professional Networks: Leverages AIChE and ASEE memberships for cross-sector collaboration on sustainable engineering education. His current work integrates Sheffield's engineering facilities with industrial partners through platforms like ChemEng Academy and LearniX, advancing digital twin applications for sustainable manufacturing while mentoring next-generation engineers in systems thinking and circular economy principles.

Ranjitha KumarView profile

Associate Professor

• Machine Learning
• Human-Computer Interaction
• Data-Driven Design
• +6 more

Ranjitha Kumar is an Associate Professor at the Siebel School of Computing and Data Science and Department of Electrical and Computer Engineering at the University of Illinois at Urbana-Champaign . She leads the Data Driven Design Group and serves as Director of the Innovation Leadership and Engineering Entrepreneurship (ILEE) Program in the Grainger College of Engineering. Her research bridges machine learning, user experience, and design, with a focus on data-driven tools for UX practitioners, designers, and programmers. BS and PhD in Computer Science, Stanford University Her work explores machine learning for effective user experiences , including interaction mining for mobile apps, custom experience ontologies , and emoji-first communication . She also investigates fashion compatibility prediction using embeddings and human-AI co-creation in design. The 15 most recent articles highlight her leadership in Human-Computer Interaction (e.g., mobile interaction frameworks, UX testing tools) and fashion technology (e.g., outfit compatibility models, social media influencer analysis). Notable trends include AI-driven user experience optimization , embedding-based feedback loops , and large-scale datasets like Rico and ZIPT. 2019 Dean's Award for Excellence in Research (UIUC College of Engineering) 2018 C.W. Gear Outstanding Junior Faculty Award Google Faculty Research Award for 'Design Mining Android Apps at Scale' AWS Machine Learning Research Award NSF CAREER proposal recommended for funding Her group has advised 30+ students, including Jinda Han (Apple) , Deniz Arsan (UserTesting) , and Ali Zaidi (UIUC PhD) . She has taught courses like CS 409: The Art of Web Programming and CS 568: User-Centered Machine Learning . Lab projects include the Rico dataset and Opico social media app .

Paola Domínguez FernándezView profile

Research Fellow

• Computational Astrophysics
• Galaxy Clusters
• Magnetic Fields in the Universe
• +5 more

Dr. Paola Domínguez Fernández is a Future Faculty Leaders (FFL) Fellow at the Institute for Theory and Computation (ITC) within the Center for Astrophysics | Harvard & Smithsonian. She specializes in large-scale magnetic fields, cosmic rays, and non-thermal phenomena in galaxy clusters using cosmological magneto-hydrodynamics (MHD) simulations. Education: Ph.D. in Astrophysics (Universität Hamburg, 2021), M.Sc. in Astrophysics (University of Bonn, 2017), B.Sc. in Physics (UNAM, 2015) Her research focuses on magnetic field evolution, shock dynamics, and synchrotron emission in galaxy clusters, employing tools like ENZO, PLUTO, and FLASH codes. Recent publications analyze AGN jet interactions, radio relic substructures, and turbulence effects in the intracluster medium (ICM). She is a committed mentor, co-directing the Science and Research Mentoring Program (SRMP) and serving as Deputy Co-Chair of the Postdoc Council at CfA. Her awards include the Future Faculty Leaders Fellowship and HmbNFG doctoral funding.

• Biodiversity Informatics
• Scientific Name Parsing
• Biodiversity Heritage Library
• +3 more

Dmitriy Yuryevich Mozzherin serves as an Assistant Research Scientist in Biodiversity Informatics at the Illinois Natural History Survey, which is part of the University of Illinois Urbana-Champaign. His work focuses on developing computational tools and methodologies for processing, integrating, and accessing biodiversity data across multiple platforms and resources. Dr. Mozzherin's research spans several critical areas in biodiversity informatics: Scientific name recognition and parsing systems Integration of biodiversity data resources Development of tools for biodiversity heritage libraries Phylogenetic tree accessibility and delivery systems Big data approaches to biodiversity information management DNA sequence analysis and related bioinformatics His publication history reveals a consistent focus on solving practical challenges in biodiversity data management. Recent work has centered on improving taxonomic information systems through integration with resources like the Catalogue of Life and developing innovative platforms such as Phylotastic for dynamic phylogenetic tree delivery. His research frequently addresses the complexities of scientific nomenclature and the challenges of working with large-scale biodiversity datasets. Dr. Mozzherin has established significant collaborations across the biodiversity informatics community, contributing to projects that enhance how researchers access and utilize evolutionary and taxonomic knowledge. His work on "gnparser" represents a major contribution to scientific name processing infrastructure used by biodiversity initiatives worldwide.

Olivier FercoqView profile

Professor

• First-order optimization algorithms
• Primal-dual methods
• Coordinate descent methods
• +7 more

Olivier Fercoq is a Professor at Télécom Paris in the Information Processing and Communication Laboratory (LTCI) . He holds a PhD in Applied Mathematics from École Polytechnique (2012) and a Master's degree from Paris 6 and ENSTA Paris. His research focuses on first-order optimization algorithms , primal-dual methods , coordinate descent , and applications in web ranking , chronotherapy for cancer , and statistical learning . Education : PhD in Applied Mathematics (École Polytechnique), Master's (Paris 6), Engineering degree (ENSTA Paris) Research Themes : Optimization for machine learning, primal-dual algorithms, web ranking, chemotherapy scheduling His recent work spans stochastic optimization , nonconvex-nonconcave minimax problems , and scalable semidefinite programming . Articles highlight advancements in primal-dual coordinate descent , power-aware signal processing , and duality gap analysis . Awards include the IMA Leslie Fox Prize (2015) and the Gaspard Monge PhD Thesis Award (2013) . Olivier has supervised numerous PhD students including Eyal Vayness (2024-), Iyad Walwil (2022-), and Eugène Ndiaye (2016-2018). He organized the Paris-Saclay Junior Conference on Data Science and Engineering (2018) and co-led the workshop Optimization, Distributed Computation, and Machine Learning (2016) . His software contributions include APPROX for parallel coordinate descent and tools for scikit-learn .

• Clothing Technology
• Functional Clothing Design
• Apparel Fit and Customization
• +5 more

Dr. Arzu Vuruşkan is an Associate Professor at the Department of Fashion and Textile Design, Faculty of Fine Arts and Design, Izmir University of Economics. She holds a PhD in Textile Engineering (2010) and has completed academic training at Dokuz Eylul University (Turkey) and Niederrhein University (Germany), supported by a DAAD award. Education: Bachelor & Master in Textile Engineering (2002, 2005) - Dokuz Eylul University Second Master in Textile and Clothing Management (2009) - Niederrhein University Her research focuses on clothing technology, functional apparel design, 3D body scanning applications, and mass customization systems. She has developed an AI-based fashion recommendation platform (Tübitak project) and conducted groundbreaking work on pressure distribution in athletic clothing through collaborations with Cornell University (2015-2017) as a Fulbright Visiting Scholar. Recent publications address dynamic body modeling, light-integrated fashion, and blockchain applications in textiles. Her work combines technical innovation with practical industry applications, including projects with Adidas and Hugo Boss. Administrative roles include Vice-Dean of Faculty (2011-2015) and Senate Member since 2019. Scientific Awards DAAD Award for Master's Studies in Germany Fulbright Visiting Scholar (2016)

Tove Stjern FrønesView profile

Researcher

• Reading Comprehension
• Literacy
• Critical Reading
• +4 more

Tove Stjern Frønes serves as a Researcher at the Department of Teacher Education and School Research within the Faculty of Educational Sciences at the University of Oslo. She functions as the Reading Expert for PISA Norway and the National Assessment of Reading Literacy since 2018, with prior advisory roles in these programs dating back to 2015. Her educational foundation includes a 2017 PhD dissertation from the University of Oslo titled Reading and navigating the web. A study of students' navigation strategies , which established her expertise in digital reading comprehension. Earlier professional milestones include serving on Norway's reading expert group (2007-2009) and conducting doctoral research on online reading strategies (2009-2015). Frønes' research centers on critical reading comprehension across physical and digital environments, with particular emphasis on students' navigation strategies in complex online texts, assessment methodologies for reading literacy, and equity issues in educational outcomes. Her work bridges cognitive psychology and educational practice through innovative methodologies including eye-tracking and logfile analysis to examine metacognitive processes during reading tasks. Her publication trajectory from 2020-2025 reveals evolving focus areas: initial concentration on PISA assessment frameworks has expanded into critical digital literacy, multilingual reading contexts, and Nordic educational equity models. Recent works demonstrate growing attention to practical classroom applications, particularly in developing assessment frameworks for critical reading and analyzing how socioeconomic factors influence reading comprehension trajectories across international contexts. No scientific awards were documented in the source materials. Her professional activities indicate no formal student advising roles but significant contributions to national testing frameworks and international large-scale assessments. Frønes operates within the Large-scale Educational Assessment (LEA) research group, where she contributes to Norway's participation in PISA and TIMSS surveys. Her current projects focus on strengthening reading culture in schools through evidence-based interventions that address both traditional literacy and emerging digital competencies required for critical engagement with online information.

• Machine Learning
• Computer Science
• Natural Language Processing
• +3 more

Mikolaj Tymon Mazurczyk is a Research Fellow at the Department of Computer Science, University of Copenhagen. His research intersects with machine learning and computer science, focusing on areas such as natural language processing, medical image analysis, and biological data modeling. The Machine Learning Section at DIKU explores both theoretical and applied aspects, including information retrieval, medical data analysis, remote sensing, and sustainability. They participate in the SCIENCE AI Centre and collaborate with various research groups. Dr. Mazurczyk's recent publications highlight advancements in optical neural networks, sustainable AI, and quantum computing applications. His work also addresses fairness in recommender systems and interpretability in large language models, as well as clinical informatics and biomedical data analysis.

Akshitha SriramanView profile

Assistant Professor

• Computer Architecture
• Software Systems
• Sustainable Computing
• +4 more

Akshitha Sriraman is an Assistant Professor at Carnegie Mellon University with joint appointments in Electrical and Computer Engineering and Computer Science. Her research bridges computer architecture and software systems to enable sustainable, equitable, and efficient hyperscale web infrastructures. She holds a PhD in Computer Science from the University of Michigan (2021) and an M.S. in Embedded Systems from the University of Pennsylvania (2015). Research Focus: Dr. Sriraman redesigns computing stacks to achieve high-performance web systems while addressing critical ethical implications like sustainability (e.g., reducing hardware carbon footprint) and equity (e.g., eliminating demographic bias in web scheduling). Her solutions span from analytical models to production deployments at hyperscale, influencing industry hardware designs including Intel's CPUs and Infrastructure Processing Units. Publications: Her 15 most recent publications demonstrate consistent focus on optimizing data center systems through architectural innovations. Key themes include carbon-efficient cloud servers, hardware-accelerated metadata management, and profile-guided microarchitectural optimizations. Work appears in premier venues like ISCA, MICRO, ASPLOS, and IEEE Micro, with two papers receiving IEEE Micro Top Picks distinctions. Awards & Honors: Google ML and Systems Junior Faculty Award (2025) NSF CAREER Award (2023) Intel Rising Star Award (2023) George Tallman Ladd Research Award (2024) IEEE Micro Top Picks (2020, 2024) ACM SIGARCH/TCCA Outstanding Dissertation Award HM (2022) Meta Systems Research Award Facebook Fellowship Students & Funding: Advises 10+ PhD/Master's students working on sustainable systems, equitable computing, and hyperscale architectures. Student achievements include NSF Graduate Fellowships and K&L Gates Presidential Fellowships. Research supported by NSF, Google, Meta, Intel, VMWare, and AWS grants. Lab & Service: Leads the Ethical Computer Systems Lab focusing on hardware/software co-design for societal impact. Founded workshops like HotEthics and initiated DEI activities recognized by CMU's Service Award. Regularly serves on program committees for OSDI, ISCA, and ASPLOS.

Dimitar Stefanov DimitrovView profile

Professor

• Evolutionary Biology
• Arthropod Systematics
• Spider Evolution
• +6 more

Dimitar Stefanov Dimitrov is a Professor at the Department of Natural History, University Museum of Bergen, University of Bergen. His research focuses on evolutionary biology with a background in arthropod systematics and evolution, particularly specializing in spiders, while also expanding to vascular plants and vertebrates. He teaches BIO332 Phylogenetic Methods and maintains active scholarly profiles on Google Scholar, ResearchGate, ORCID, and Web of Science. Dr. Dimitrov's research program aims to understand how evolutionary and ecological processes generate and maintain biodiversity through time and space. He combines species evolutionary histories, contemporary distributional data, historical distributions, and environmental factors to investigate the mechanisms underlying life's distribution on Earth. His work specifically examines factors governing biodiversity patterns at different spatial scales and species responses to climate change. This integrative approach assembles multiple pieces of a complex puzzle from species description to understanding gene-environment interactions. His recent publications (2023-2025) reveal a dual research focus: spider evolution/systematics and plant macroecology/macroevolution. In spider research, he investigates phylogenomics, diversification dynamics, adaptive radiations (particularly Hawaiian Tetragnatha), and orb-weaving spider evolution. In plant research, his work examines global angiosperm diversity patterns, floristic mapping, flowering plant evolution, and species richness-climate relationships. He has also developed bioinformatics tools like NCBIminer and PyNCBIminer for phylogenetic data assembly. Dr. Dimitrov is actively involved in research projects within two broad fields: systematics, macroecology and macroevolution of spiders (with focus on orb weavers and pholcids), and macroecology and macroevolution of seed plants. He participates in the BiGTREE project, a HKdir funded NORPART training network connecting Norway, Colombia, and Peru. His international collaborations span institutions worldwide including Peking University, University of Copenhagen, and Harvard University, supporting his global biodiversity research.

Kari Anne BraathenView profile

Professor

• Arctic Ecology
• Plant-Herbivore Interactions
• Climate Change Impact on Ecosystems
• +5 more

Kari Anne Braathen is a Professor at the Institute of Urbanism and Landscape Architecture , Oslo School of Architecture and Design, specializing in Arctic and boreal ecosystems. Her work integrates ecology, climate change impacts, and vegetation dynamics. Current Affiliation : Oslo School of Architecture and Design Research Focus : Herbivory effects, climate change, tundra ecosystems, soil-plant interactions Methods : Ancient DNA analysis, NIRS (near-infrared spectroscopy), experimental ecology Her research explores how herbivores (reindeer, geese, rodents) and climate drivers shape Arctic vegetation composition and ecosystem functions. Key themes include niche construction , biotic homogenization , and allelopathic plant interactions . She contributes to global soil fungal diversity understanding through the Global Soil Mycobiome consortium . Recent article trends highlight interdisciplinary approaches combining sedaDNA for Holocene vegetation reconstruction, NIRS for rapid chemical analysis, and large-scale herbivore exclusion experiments . These studies span topics from Empetrum nigrum allelopathy to climate-driven shifts in reindeer pasture quality. She collaborates extensively with researchers like Maria Wilhelmina Tuomi, Claire Armstrong, and Peter Heintzman, contributing to journals such as Ecography , Nature Communications , and Science Advances .

• Natural language processing
• Speech recognition
• Statistical graph recognition
• +2 more

HW Hon is a full-time Visiting Professor in the Department of Information Engineering. He maintains an active research affiliation with Microsoft, evidenced by his institutional email address and personal research website. His role indicates ongoing academic engagement without indications of part-time status or retirement. His research expertise spans computational linguistics and intelligent systems development, with primary focus areas including: Natural language processing algorithms Speech recognition systems Statistical pattern recognition Web search technologies Large-scale data mining

Yubao WuView profile

Assistant Professor

• Big Data Analytics
• Data Mining
• Bioinformatics
• +3 more

Dr. Yubao (Robert) Wu is an Assistant Professor in the Department of Computer Science at Georgia State University. He holds a Ph.D. from Case Western Reserve University, and B.Eng. and M.Eng. degrees from Dalian University of Technology, China. His research focuses on big data analytics, data mining, and bioinformatics, with emphasis on analyzing large-scale networks in biomedical and social domains. Key areas include graph theory, random walk-based proximity measures, and community detection algorithms. Education: B.Eng. in Electronic and Information Engineering, Dalian University of Technology (2007) M.Eng. in Signal and Information Processing, Dalian University of Technology (2009) Ph.D. in Computer Science, Case Western Reserve University (2016) Dr. Wu’s research emphasizes scalable algorithms for large graphs, including Monte Carlo methods for random-walk-based similarity measures and distributed computing techniques. His work addresses challenges in network analysis such as detecting communities, measuring node similarity, and optimizing search processes in complex networks. He also explores applications in cybercrime analysis (e.g., dark web markets), public health (opioid epidemic prediction via social media), and bioinformatics. His publications span prestigious venues like VLDB, SIGMOD, and ICDE, addressing topics like illicit drug ad detection, dark web certification analysis, and efficient k-vertex connected component discovery. He is based at 1 Park Place, room 638.

Dimitris PoursanidisView profile

Research Fellow

• Environmental Mapping
• Environmental Monitoring
• Earth Observation
• +6 more

Dimitris Poursanidis serves as a Research Fellow at the Remote Sensing Lab (rslab.gr) within the Institute of Applied and Computational Mathematics at the Foundation for Research and Technology - Hellas (FORTH). His work focuses on environmental mapping and monitoring through innovative technological approaches. His educational background includes a Ph.D. in Marine Ecology (2016), an M.Sc. in Integrated Coastal Zone Management (2008), and a B.Sc. in Ecosystem Management (2004). His academic journey has been complemented by extensive field experience across multiple sectors. Poursanidis specializes in Environmental Mapping and Monitoring using Earth Observation, UAV technology, Non-Destructive Sampling, Photogrammetry, and Scientific Diving. His research particularly emphasizes Satellite Remote Sensing applications in coastal environments and Biodiversity exploitation through Species Distribution Modeling in both terrestrial and aquatic ecosystems. His work bridges the gap between technological innovation and ecological conservation, with a strong focus on Mediterranean environments. Analysis of his recent publications reveals a strong emphasis on Mediterranean marine ecosystems, particularly seagrass habitats like Posidonia oceanica. His work integrates satellite remote sensing with field validation methods to address conservation challenges, invasive species monitoring, and habitat mapping. A notable trend is his increasing use of cloud computing platforms like Google Earth Engine for large-scale environmental analysis, demonstrating technical innovation in processing satellite data for ecological applications. Throughout his career, Poursanidis has collaborated across diverse institutional contexts, working with academic institutions (NHMC, UNEP/MAP, HCMR, University of Athens, University of the Aegean), private sector companies (Marathon Data Systems, NCC ltd, NatureBureau ltd), and NGOs (WWF, IUCN, iSea). His projects have been funded by major European and national programs including LIFE+, INTERREG, EraNET, H2020, MAVA Foundation, THALASSA Foundation, and MEDPAN. At FORTH's Remote Sensing Lab, Poursanidis contributes to cutting-edge research that combines satellite technology with ecological field studies. His work on satellite-derived bathymetry, marine habitat mapping, and invasive species monitoring represents significant contributions to the understanding and conservation of Mediterranean coastal ecosystems.

Hannes MühleisenView profile

Professor

• Data Engineering
• Database Systems
• Query Processing
• +2 more

Hannes Mühleisen is Professor of Data Engineering at Radboud University's Faculty of Science, Institute for Computing and Information Sciences. He maintains a joint appointment as Senior Researcher at Centrum Wiskunde & Informatica (CWI) and serves as CEO of DuckDB Labs. His research focuses on analytical data management systems architecture, with applications in modern data-driven applications. Mühleisen's research interests center on data engineering challenges, particularly the architecture and design of analytical data management systems. He develops universally-useful software artifacts that transform how data systems operate in real-world applications, with emphasis on CPU-efficient processing and embedded analytics. His recent publications demonstrate a consistent focus on database system optimization, particularly in the areas of query processing, sorting algorithms, and web-based analytical processing. This research direction aims to improve the efficiency and scalability of data systems handling large-scale analytical workloads. Dutch Prize for ICT Research 2025 Best paper runner up award at SSDBM 2017 Mühleisen leads DuckDB Labs and collaborates with research teams at Radboud University on data engineering challenges. His work includes developing frameworks for responsible decentralized data architectures and teaching courses on Big Data Infrastructures & Technology.