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Paul DaltonView profile

Associate Professor

• Biofabrication
• Biomaterials
• 3D Printing
• +3 more

Paul Dalton is an Associate Professor at the University of Oregon's Knight Campus, holding the Bradshaw and Holzapfel Research Professor chair in Transformational Science and Mathematics. With a materials science background, he has pioneered melt electrowriting (MEW) technology for biomedical applications over 25 years across Australia, Canada, Germany, and the USA. Education: PhD from Curtin University (Perth, Australia) Key Positions: First Biofabrication Professor in Germany; Knight Campus faculty since 2011 His research integrates advanced manufacturing principles with biomaterials to create clinical solutions. The Dalton Lab's open-source MEWron platform has democratized access to high-resolution 3D bioprinting, enabling applications in nerve regeneration , artificial blood vessels , and skin tissue engineering . The technology has been adopted by over 25 European labs and 5 commercial bioprinter manufacturers. Selected publications in journals like Advanced Materials , Nature Materials , and Biomaterials demonstrate his work's impact. His lab actively trains students and researchers while collaborating with international institutions and industry partners. Scientific Awards: Bradshaw and Holzapfel Research Professorship Advising: Mentors PhD candidates, postdocs, and visiting scholars in biofabrication and biomaterials research

Filippo BergamascoView profile

Associate Professor

• Computer Vision
• Oceanography
• Image Processing
• +3 more

Filippo Bergamasco is an Associate Professor at Ca' Foscari University of Venice, affiliated with the Department of Environmental Sciences, Computer Science and Statistics. He is a member of the Scientific Committee of the Center for Studies on Port Economics and Management (DAIS). His work bridges computer vision, environmental monitoring, and oceanography, with a focus on developing advanced imaging techniques for ocean wave analysis and stereo reconstruction. He leads projects like the WASS pipeline, an open-source tool for 3D stereo reconstruction of ocean waves, and collaborates on studies involving rogue wave dynamics, low-cost sensors, and Arctic sea-state analysis. His research leverages machine learning, deep learning, and real-time systems to address challenges in environmental and marine sciences. Research interests include computer vision applications in oceanography, stereo imaging systems, wave dynamics modeling, and environmental monitoring technologies. He has contributed to over 80 peer-reviewed publications, with recent works focusing on real-time wave tracking, 3D reconstruction, and the integration of physics-driven models with neural networks. His expertise spans interdisciplinary collaborations, including projects on fish oil's impact on wind waves and the development of robust camera calibration methods. He actively publishes in top journals like IEEE Transactions on Image Processing, Ocean Modelling, and Physical Review Letters, and engages in international conferences such as ECCV and ICPRAM.

Juan Carlos FarahView profile

Researcher

• Educational Technology
• Artificial Intelligence in Education
• Learning Analytics
• +4 more

Juan Carlos Farah is a Researcher at the École Polytechnique Fédérale de Lausanne (EPFL), holding dual appointments in the Fondation Bertarelli Chair in Neuroprosthétique Cognitive (School of Life Sciences/SV) and the SCI-STI-DG group (School of Engineering/STI). His work bridges neuroscience, artificial intelligence, and educational technology, focusing on innovative applications of AI in learning environments and neuroprosthetics research. Research Interests: Farah’s research spans educational chatbot design, AI-enhanced learning analytics, neuroprosthetic systems, and the ethical integration of technology in education. He has pioneered frameworks for task-oriented conversational agents, blockchain-based learning trace repositories, and gamified computational thinking tools. Key Projects: He contributed to the Graasp Desktop initiative for underconnected African schools and developed the TRACE model for educational chatbots. His work on code review notebooks and bot-mediated software engineering education has influenced pedagogical practices globally. Awards & Recognition: No specific awards listed, but his publications reflect high-impact contributions to IEEE, ACM, and Elsevier journals/conferences. Active in global initiatives like UNESCO’s Unequal World Conference on education equity. Technical Expertise: Proficient in Python, JavaScript, and AI toolkits. Specializes in building scalable educational platforms, learning analytics pipelines, and neuroimaging analysis for cognitive studies.

Petar JovanovicView profile

Researcher

• Big Data Management
• Data Governance
• Data Integration
• +3 more

Petar Jovanovic is a researcher at the Department of Service and Information Systems Engineering within the Barcelona School of Computer Science at Polytechnic University of Catalonia (UPC). His work focuses on Big Data management , data governance , and user-centered data integration platforms . PhD (2016) from UPC and Université Libre de Bruxelles Software Engineering degree from University of Belgrade Jovanovic created the Quarry platform, enabling non-technical users to perform data analysis for global health initiatives like WHO disease eradication programs. His 2017 SCIE/BBVA award recognized innovations in applying Big Data to combat diseases such as Chagas in underprivileged countries. Recent research emphasizes: Knowledge graph-based data governance frameworks (2024) Web API evolution prediction models (2024) Automated FAIR data lifecycle systems (2023-2024) He has co-authored 15+ high-impact publications and holds one patent as primary innovator. His work spans European Union research programs and WHO collaborations.

Dustin RichmondView profile

Assistant Professor

• Computer Architecture
• FPGA
• RISC-V
• +4 more

Dustin Richmond is an Assistant Professor in the Department of Computer Science and Engineering at the Baskin School of Engineering, University of California, Santa Cruz. His work focuses on secure, usable hardware systems with applications in FPGA acceleration, RISC-V architectures, and side-channel analysis. Email: drichmond@ucsc Office: Engineering 2, Room 221 Research Interests: Secure hardware systems FPGA-based computing Manycore processors High-level synthesis Side-channel vulnerabilities Notable Article Trends: Recent publications emphasize cloud FPGA security, manycore design optimization, and hardware security. Earlier works focus on RISC-V acceleration, OpenCL compiler enhancements, and heterogeneous computing systems. GitHub Contributions: Maintains open-source projects like RISC-V-On-PYNQ and PYNQ-HLS, addressing FPGA programming challenges and RISC-V integration. Active in resolving community issues related to toolchain compatibility and hardware-software interfaces.

Jelena PlašićView profile

Assistant Professor

• Information Technologies and Systems
• Data Science
• Business Intelligence
• +7 more

Jelena Plašić is an Assistant Professor at the Department of Information Technologies , Faculty of Technical Sciences in Čačak , University of Kragujevac. She holds a Master of Information Technology Engineering and is pursuing her Ph.D. in Information Technology. Her work focuses on Information Technologies and Systems , with expertise in cloud computing, business intelligence, data science , and software engineering . Education: B.Sc. in Informatics (University of Kragujevac), M.Sc. in Information Technology Engineering (FTS Čačak) Current Role: Assistant Professor (2021–present) and Teaching Associate (2019–2021) Her research bridges data analytics and enterprise systems , emphasizing cloud-based solutions and predictive modeling . Her 15 most recent publications span CRM transformation , IoT standards , and regression analysis in education and demographics. She contributes to academic conferences like EBM and TIE , and participates in the Promotion Team at FTS Čačak. Her technological interests include machine learning , business intelligence , and sustainable supply chain analytics . She teaches Introduction to Programming, Software Engineering , and E-Business , and has served on organizational committees for international conferences such as TIE 2022 and TIE 2024 . Contact: jelena.plasic@ftn.kg.ac.rs .

Gianmarco CherchiView profile

Assistant Professor

• Computer Graphics
• Geometry Processing
• Surface Mesh Generation
• +12 more

Gianmarco Cherchi is a Tenure-Track Assistant Professor and Computer Science Researcher in the Department of Mathematics and Computer Science at the University of Cagliari, Italy, where he also completed his PhD. He teaches courses in Data Visualization and Web Programming at the undergraduate level. His research lies at the intersection of Computer Graphics and Geometry Processing, with a strong focus on surface and volumetric mesh generation, optimization, digital fabrication, and polycube-based modeling. His work combines algorithmic innovation with practical applications in fabrication, visualization, and interactive systems. The recent publications highlight a consistent trend in advanced hexahedral meshing techniques (e.g., HexBox, VOLMAP), robust geometric computation (e.g., mesh booleans), and interactive tools (e.g., ProtoSketchAR, Py3DViewer). His research spans theoretical algorithm development, benchmark creation, and applied systems for VR/AR and simulation. His scientific accolades include the Young Investigator Award 2024 from the Shape Modeling International Organization, and prior Best Thesis Awards from the Eurographics Italy Association for both his M.Sc. and Ph.D. work. Cherchi actively collaborates with researchers such as Marco Livesu, Riccardo Scateni, and others, contributing to major surveys and state-of-the-art methods in hexahedral meshing. His work is supported by publications in top venues like ACM Transactions on Graphics (SIGGRAPH), Computer Graphics Forum (Eurographics), and IEEE VR. He has also developed practical software tools like Py3DViewer for geometry processing prototyping. He leads research in digital fabrication pipelines, as evidenced by publications on polycube decomposition for manufacturing and automated flat pattern generation. His lab work involves developing interactive and robust systems for 3D modeling and analysis.

• Robotics
• Computer Vision
• Industrial Automation
• +4 more

Oleksandr Semeniuta is an active researcher specializing in robotics, computer vision, and industrial automation systems. His work demonstrates consistent contributions to the field with publications spanning from 2015 to 2022, indicating ongoing academic or research activity. His collaborations with researchers like Petter Falkman across multiple publications suggest established research partnerships in the robotics domain. Dr. Semeniuta's research interests center around practical applications of robotics and computer vision in industrial settings. His work encompasses event-driven architectures for data processing and robot control, stereo calibration methods for 3D reconstruction, and resource-aware machine learning for IoT security. His research shows a strong focus on developing practical frameworks and systems that address real-world challenges in manufacturing and industrial automation. The publication trends reveal a consistent focus on robotics systems engineering, with particular emphasis on vision-based solutions and event-driven architectures. His work bridges theoretical computer vision concepts with practical industrial applications, especially in automotive manufacturing and robotic deburring systems. The research demonstrates progression from foundational work on dataflow programming for vision systems to more complex implementations of machine learning on edge devices for security applications. While specific awards are not documented in the available publication records, the consistent output in reputable venues including IEEE conferences and PeerJ Computer Science indicates recognition within the academic community. His work appears in both journal and conference publications, suggesting a balanced approach to disseminating research findings through different academic channels. Dr. Semeniuta's collaborative network includes researchers from various institutions, with Petter Falkman appearing as a frequent co-author across multiple projects. This suggests participation in research teams focused on industrial robotics and computer vision applications. His work on frameworks like EPypes indicates contributions to software infrastructure that enables more efficient development of robotic systems and data processing pipelines.

Isaac Samuel KohaneView profile

Professor

• Artificial Intelligence
• Biomedical Informatics
• Genomics
• +4 more

Isaac Samuel Kohane, MD, PhD, is the inaugural Chair and Marion V. Nelson Professor of Biomedical Informatics at Harvard Medical School, with additional appointments as Professor of Pediatrics at Boston Children's Hospital and Associate Professor of Medicine at Brigham and Women's Hospital. He directs the Kohane Lab ('Zaklab'), pioneering AI integration in clinical medicine, patient data control, and human values in AI systems. His research spans 30+ years of re-engineering healthcare through computational techniques, linking EHR and genomic data to study complex diseases like autism, cancers, and rare disorders. He co-authored the Institute of Medicine's Precision Medicine Report and authored influential books including The AI Revolution in Medicine . Recent work focuses on causal machine learning for treatment outcomes, GPT-4 applications in diabetes monitoring, and patient-centric data systems like PING and Guardian Angel. He leads NIH-funded initiatives on trans-omics integration (TOPMED) and patient-centered information commons. Scientific Honors: Institute of Medicine (National Academy of Medicine) member American Society for Clinical Investigation member Current Research: Multi-institutional real-world data pipelines AI ethics and value alignment Genomic risk scores in cancer Neurodevelopmental disorder genetics The lab fosters a collaborative environment with graduate students and postdocs working on large language models, precision oncology, and disease classification. He balances leadership in NEJM AI as Editor-in-Chief with hands-on research and mentorship.

Furkan KıraçView profile

Assistant Professor

• Artificial Intelligence
• Computer Vision
• Machine Learning
• +3 more

Furkan Kıraç is an Assistant Professor in the Computer Science Department at Özyeğin University, specializing in Computer Vision and Machine Learning . He previously served as a Part-Time Instructor at the same university (2012-2013) and as a Research Assistant at Boğaziçi University (2009-2013). Education: PhD in Computer Engineering, Boğaziçi University (2013) MS in Systems and Control Engineering, Boğaziçi University (2002) BS in Mechanical Engineering, Boğaziçi University (2000) His research focuses on real-time hand pose estimation , deep learning , and computer vision applications in industrial automation. Recent publications highlight his work on pedestrian tracking, spatio-temporal mapping, and image processing pipelines for test oracle automation. Notable achievements include founding two computer vision companies ( Proksima and Fortibase ) and receiving awards at SIU conferences (2004, 2005, 2012). He has contributed to projects funded by TÜBİTAK and the Scientific and Technical Research Council of Turkey. Scientific Awards: 3rd place in best demo award (SIU 2012) Best application paper award (SIU 2012) 3rd degree in Turkish National Science Competition (1994, 1995) Gold/Silver/Bronze medals in National Computer Science Olympiads

• Image processing
• 3D visualization
• Virtual Reality
• +7 more

Prof. PhD Miroslav Nikolov Galabov is a Professor at the Faculty of Mathematics and Informatics, St. Cyril and St. Methodius University of Veliko Turnovo in Bulgaria. His academic career spans several decades with significant contributions to computer science, particularly in the areas of 3D visualization, virtual and augmented reality, and image processing. He maintains active research collaborations and participates in multiple funded projects at the university. Professor Galabov's research interests focus on cutting-edge technologies including: Image processing and computer vision 3D visualization and modeling Virtual and Augmented Reality systems Microprocessor systems and embedded computing System programming and software architecture Multimedia systems and publishing technologies E-business applications and social network technologies His scholarly output demonstrates a clear evolution from foundational work in digital signal processing and image compression toward contemporary research in cloud infrastructure, semantic web technologies, and digital twin applications. Recent publications show a strong emphasis on practical implementations of AWS infrastructure, microservices architecture, and blockchain solutions for IoT systems. His work consistently bridges theoretical computer science with real-world applications across multiple domains including education, business, and cultural heritage preservation. Professor Galabov actively participates in significant research projects including: "Изследване и анализ на приложението на технологични инструменти и инфраструктура като креативна среда за трансфер на знания" (2025-2025) "Изследване, анализ и популяризиране на мобилни технологии и софтуерни приложения в полза на студенти със специални потребности" (2025-2025) "Изследване възможностите на технологиите за виртуална и добавена реалност за атрактивно представяне и популяризиране на българското фолклорно наследство" (2023-2023) Multiple projects related to 3D visualization, e-learning, and digital infrastructure development

Andrew LumsdaineView profile

Academic

• High Performance Computing
• Scalable Graph Algorithms
• Computational Photography
• +5 more

Andrew Lumsdaine is the Chief Scientist at the Northwest Institute for Advanced Computing , a dual appointee between the University of Washington and the Pacific Northwest National Laboratory (PNNL). He holds the title of Affiliate Professor in the Paul G. Allen School of Computer Science and Engineering at UW and serves as a Laboratory Fellow in PNNL's Applied Mathematics, Computing, and Data Division. His research spans foundational and applied aspects of High Performance Computing , focusing on scalable graph algorithms, computational photography, and runtime systems for distributed-memory architectures. Education : Not explicitly stated in the provided text. Lumsdaine's work addresses critical challenges in parallel and distributed computing , including synchronization avoidance, communication optimization, and domain-specific language design for graph analytics. He has led projects like GraphPack (NSF-sponsored) and contributed to DARPA's HIVE program through the HAGGLE software development kit. His publications highlight innovations in light field imaging , GPU programming models , and graph algorithm abstractions . Notable collaborations include the GraphBLAS standardization effort and development of tools for checkpoint/restart fault tolerance. His research has been presented at leading conferences like SC , IPDPS , and Eurographics . Lumsdaine actively seeks collaborators and advises students/postdocs through projects listed on his research page.

Olga LevinaView profile

Professor

• Ethical Issues of Digitalization
• Business Process Management
• Low-Code Development
• +2 more

Prof. Dr. Olga Levina serves as Professor of Business Informatics at Brandenburg University of Technology (BTU), Department of Economics, where she bridges technical systems design with ethical governance in digital transformation. Her institutional leadership includes contributions to DIN working groups on Responsible AI and UNESCO's "Artificial Intelligence for more gender equality and against discrimination" guideline. Her educational background includes: Industrial Engineering with technical specialization in Information and Communication Systems (Technical University of Berlin and LUISS Rome) Doctorate in Network Analysis (TU Berlin) Levina's research critically examines ethical digitalization , business process management , and low-code development through participatory frameworks. She investigates how socially-aware information systems can mitigate digital inequality while advancing sustainability. Current projects analyze dark patterns in consent interfaces and AI's impact on journalistic values, emphasizing transparency and stakeholder inclusion as foundational principles. Her 15 most recent publications (2021-2025) reveal three dominant trajectories: (1) operationalizing ethics in software design through assessment tools and pipelines, (2) analyzing low-code platforms' organizational impact, and (3) exposing biases in algorithmic systems via empirical studies of dark patterns and recommender systems. This work consistently connects technical implementation with societal consequences. Levina actively supervises Master's theses through structured processes requiring English proficiency and research proposals. Her Ethical and Legal Aspects of Digitalization course generates publishable student research on topics like cookie consent dark patterns and AI sentiment analysis. She leads the InnoWest project on sustainable IT development while maintaining roles as journal/conference reviewer and DIN working group contributor. Her research group produces empirical studies through student projects examining digital ethics in real-world contexts, including cross-national analyses of cookie banners and values in messenger apps. Current work explores "naming as framing" in sustainability discourse and machine learning system auditing.

• Materials Science
• Nanotechnology
• Transmission Electron Microscopy (TEM)
• +5 more

Meng Li is a Staff Scientist at the Center for Functional Nanomaterials within Brookhaven National Laboratory, specializing in in-situ environmental Transmission Electron Microscopy (E-TEM) and related applications. She holds a Ph.D. in Materials Science and Engineering from Xi'an Jiaotong University, China, and a B.E. in Mechanical Engineering from the same institution. Postdoctoral research at the University of Pittsburgh focused on in-situ ETEM studies of copper oxidation and catalytic mechanisms. Research Interests: Meng Li's work centers on advancing atomic-scale understanding of gas-solid reactions in catalysts and corrosion processes. She develops MEMS-based holders for in-situ TEM Data analysis pipelines for operando studies Hardware/software for environmental TEM (gas-cell, liquid-cell, heating, electrical biasing) targeting catalysis, corrosion, and energy materials. Scientific Contributions: Her publications span 2016–2025 and emphasize operando TEM techniques for studying oxidation dynamics, alloy stability, nanowire growth, and battery materials. Key trends include Integration of machine learning with first-principles calculations Environmental cell applications for real-time reaction monitoring Thermal and mechanical behavior of nanomaterials Metal-semiconductor interface analysis Laboratory Affiliations: Meng Li is affiliated with the Center for Functional Nanomaterials at Brookhaven National Laboratory, where she focuses on analytical (S)TEM techniques and MEMS device innovation for in-situ experiments.

• distributed and parallel computing
• blockchain technology
• decentralized platforms
• +3 more

Тетяна Сергіївна Дьячук є старшим викладачем кафедри комп'ютерних систем та мереж Факультету комп'ютерних наук і технологій Запорізької національної технічної політехніки, де працює з 2006 року після закінчення університету з відзнакою. Вона є активним членом академічної спільноти, зосереджуючись на сучасних напрямках комп'ютерних наук та технологій. Освіта: Запорізька національна технічна політехніка, 2006 рік, спеціальність "Комп'ютерні системи та мережі", кваліфікація "Магістр комп'ютерних систем та мереж" (з відзнакою) Запорізька національна технічна політехніка, 2006 рік, кваліфікація "Менеджер-економіст" Наукові інтереси Тетяни Сергіївни охоплюють ключові напрями сучасних комп'ютерних технологій, зокрема розподілені та паралельні обчислення, блокчейн-технології, децентралізовані платформи та оптимізацію обчислень. Вона також активно займається дослідженнями в галузі Android-програмування та розробки мобільних додатків. Її наукова робота характеризується практичною спрямованістю, що знаходить відображення в численних публікаціях та конференціях. Аналіз наукових публікацій Тетяни Сергіївни показує чітку еволюцію її наукових інтересів від фундаментальних досліджень розподілених систем та алгоритмів планування ресурсів до сучасних технологій блокчейну, штучного інтелекту та автоматизації процесів програмування. Особливо вражає її здатність поєднувати теоретичні дослідження з практичними застосуваннями в різних галузях, від медичної діагностики до розробки мов високого рівня. Наукові досягнення: Понад 15 наукових публікацій в провідних наукових виданнях Активна участь у міжнародних наукових конференціях Реєстрація в наукометричних базах: Scopus, Web of Science, Google Scholar, ORCID Тетяна Сергіївна активно бере участь у науково-педагогічній діяльності, викладаючи курси, що відповідають сучасним тенденціям в комп'ютерних науках. Вона також займається науковою роботою зі студентами, сприяючи їх інтеграції в наукову спільноту через участь у наукових конференціях та проєктах. Незважаючи на те, що конкретні науково-дослідні гранти не зазначені в доступних джерелах, її публікаційна активність та участь у конференціях свідчать про продуктивну наукову діяльність. Хоча конкретні лабораторії або наукові групи, якими керує Тетяна Сергіївна, не зазначені в доступних джерелах, її наукова робота тісно пов'язана з розвитком сучасних технологій розподілених систем та обчислень, що ймовірно відбувається в рамках кафедри комп'ютерних систем та мереж Запорізької політехніки.