جست‌وجوی استاد و پژوهشگر

Fuda van Diggelenمشاهده پروفایل

پژوهشگر

• Swarm Robotics
• Robot Learning
• Machine Learning
• +۴ مورد دیگر

Fuda van Diggelen is a Postdoctoral Researcher at the École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the School of Engineering (STI) and the Institute of Microengineering (IGM). Their primary research focuses on the intersection of robotics and artificial intelligence, particularly in robot learning and emergent behaviors in swarms. They are part of the Laboratory of Intelligent Systems (LIS), where they investigate adaptive neural networks for distributed learning in robot swarms. Van Diggelen holds a PhD in Evolutionary Robotics from Vrije Universiteit Amsterdam (2024), supervised by Guszti Eiben and Eliseo Ferrante. Their doctoral work explored robot learning algorithms in evolving populations. They also earned two Master’s degrees: Human Movement Science (cum laude) from VU Amsterdam and Mechanical Engineering (Bio-Robotics) from TU Delft. Research interests include embodied intelligence, complex systems, control theory, and applications in healthcare such as ICU data analysis during the COVID-19 pandemic. Notable achievements include a nomination for the Best Master’s Thesis Award at VU Amsterdam and 3rd place in the IEEE RAS Multi Robot Systems (MRS) competition. They have contributed to projects like the Revolve software framework for robot evolution and the Dutch ICU Data Warehouse collaboration. Their work bridges robotics, AI, and healthcare, with a focus on developing adaptive systems for real-world challenges.

• Secure Software Systems
• Cyber Security
• Cloud Computing
• +۵ مورد دیگر

Professor Ali Babar is a faculty member in the School of Computer and Mathematical Sciences at the University of Adelaide, part of the Faculty of Sciences, Engineering and Technology. He holds the academic rank of Professor and leads research in secure software systems, cyber security, and emerging technologies like cloud computing and IoT. Research focuses include engineering secure software systems, applying AI/ML for security, and empirical methods in software engineering. His work has resulted in over 320 peer-reviewed publications (h-index 66) and contributions to high-impact projects like the Cyber Security Cooperative Research Centre (CSCRC), a A$140M initiative. Collaborations span industry/government partners such as DST Group, ActewAGL, and Cisco. Awards include the 2014 Most Influential Paper Award at the Australasian Software Engineering Conference. His research addresses critical areas like secure microservices, ML model decay mitigation, and privacy engineering practices. Current themes include cyber security as a service and platform architectures for distributed systems. Active in supervising PhD and Master's students and participates in interdisciplinary initiatives like the Oceania Cyber Security Centre and Australian Cyber Collaboration Centre.

• Biometry
• Agricultural Statistics
• Computational Plant Breeding
• +۳ مورد دیگر

Dr Julian Taylor is an Associate Professor and Node Leader of the Analytics for the Australian Grains Industry (AAGI-UA) at the University of Adelaide's Waite Agricultural Precinct. He holds an Ext-Funded Research Fellowship and leads a multidisciplinary team within the School of Agriculture, Food and Wine (Faculty of Sciences, Engineering and Technology). His research focuses on biometry, machine learning, and computational tools for agricultural analytics. Taylor is a key figure in the $36M GRDC-funded AAGI initiative, fostering collaboration across institutions to address big data challenges in grains research. His expertise spans statistical methodologies, plant breeding analytics, and software development (e.g., R packages wgaim and ASMap ). Taylor collaborates extensively with plant scientists and industry partners to enhance crop resilience, yield prediction, and genomic analysis. His work emphasizes integrating advanced analytics into agricultural practices, including genomic prediction, drought tolerance, and pest/disease resistance. Key projects include: Strategic leadership of AAGI-UA’s analytics network Development of tools like Coredetector for genome alignment Genetic mapping of traits in wheat, barley, and chickpea Climate resilience studies under varying CO₂ and nitrogen regimes He actively supervises postgraduate students and contributes to national and international breeding programs. Taylor’s publications highlight advancements in statistical modeling, crop physiology, and precision agriculture.

Jacob Sorberمشاهده پروفایل

استاد

• Batteryless Computing
• Embedded Systems
• Wearable Computing
• +۵ مورد دیگر

Jacob Sorber is a Professor in the School of Computing at Clemson University where he teaches Computer Science courses and leads the PERSIST Research Lab. His research focuses on developing smaller, more efficient, and maintenance-free embedded systems and wearables that operate through energy harvesting and intermittent computing techniques. Dr. Sorber earned his Ph.D. in Computer Science from the University of Massachusetts Amherst under Mark Corner, continuing an academic genealogy tracing back to Sir Isaac Newton. His research interests prominently feature Batteryless Computing , Embedded Systems , and Wearable Security , with applications in health monitoring and sustainable infrastructure. He develops hardware and software technologies enabling devices to adapt to changing conditions, recover from power failures, and operate for decades without maintenance. Recent publications demonstrate a clear trajectory toward batteryless wireless networking and user-centered wearable design , with significant contributions to energy storage for intermittent sensors and eating behavior monitoring systems. His work bridges theoretical advances in intermittent computing with practical health applications like the Auracle ear-mounted eating detection system. Scientific Awards: Fulbright Scholar to Botswana (2019-20) Dean's Professor of Computer Science (2016) NSF CAREER Award (2015) SenSys Best Paper (2014) Multiple conference best paper/poster awards Dr. Sorber has secured substantial NSF funding including CAREER and project grants for Auracle and Amulet, and successfully mentored students like Josiah Hester who joined Northwestern University as an Assistant Professor. His Fulbright award enabled impactful work in Botswana advancing sustainable computing applications. He directs the PERSIST Research Lab which develops foundational technologies including Ekho (energy harvesting simulation), Mementos (checkpointing for batteryless devices), and Turducken (hierarchical power management), with active collaborations in health informatics and environmental engineering for real-world deployments.

• Information Security Management
• Data Center Optimization
• Software Architecture
• +۴ مورد دیگر

Prof. Rabih Bashroush is a Professor of Digital Infrastructure at the University of East London (UEL), affiliated with the Architecture, Computing & Engineering research institute. His expertise spans information security management, data center optimization, and energy-aware software architectures. He leads research on sustainable computing practices, server lifecycle management, and cybersecurity frameworks. His work often addresses practical challenges in IT infrastructure, including hardware refresh strategies, cloud resource allocation, and predictive security modeling. Notable contributions include developing the ALI Architecture Description Language and frameworks for variability management in software product lines. Research interests integrate technical and economic dimensions, focusing on cost-effective solutions for organizations. His publications emphasize real-world applications, such as ROI analysis for data center upgrades and ISO 27001 compliance strategies.

• Cybersecurity
• Quantum Computing
• Energy Efficiency in Computing
• +۴ مورد دیگر

Haider Ali is a Lecturer in Computer Science at the College of Science and Engineering. His research focuses on cybersecurity, quantum computing, energy-efficient computing, and optimization algorithms, particularly in IoT and real-time systems. Research interests include quantum encryption protocols, zero-day exploit detection in web platforms like WordPress, energy-aware scheduling in embedded systems, and metaheuristic algorithms for wireless sensor networks. His work bridges theoretical advancements with practical applications in edge computing, cyber-physical systems, and healthcare IoT. Notable contributions include developing novel scheduling techniques for MPSoCs, energy-optimized data aggregation in IoT, and frameworks for detecting cyber threats. Articles span reputable journals like IEEE Access and Future Internet, highlighting interdisciplinary approaches to modern computing challenges. No awards or grants are explicitly documented. Advising activity details are not provided in the text.

• Machine Learning
• Computer Vision
• Data Analytics
• +۱۲ مورد دیگر

Michael Dittenbach is a researcher at TU Wien's Institute of Software Technology and Interactive Systems (E188). He contributes to interdisciplinary work combining machine learning, computer vision, and tourism informatics. His career spans over 15 years of publications in semantic web technologies, data analytics, and 3D virtual environments. Current research focuses on computer vision applications for cultural heritage, tourism recommender systems, and self-organizing map visualization Key projects include Media Square, SOIRE, and Web 3D environments Collaborates extensively with Helmut Berger, Andreas Rauber, and Robert Sablatnig His recent work (2022) explores computer vision techniques for digital library preservation, while earlier studies (2005-2015) focused on tourism informatics, data analytics frameworks, and semantic web applications. Publications demonstrate a consistent trajectory toward integrating machine learning with user-centric digital systems. As part of TU Wien's research infrastructure, he contributes to technical reports, conference proceedings, and multimedia system development without explicit mentions of scientific awards in available records.

• Information Systems
• NoSQL Databases
• Formal Modeling of Organizations
• +۷ مورد دیگر

Pedro Ramos is a Full Professor and Director at the Department of Information Science and Technology (ISTA), ISCTE-IUL University Institute of Lisbon. He is also an Integrated Researcher at ISTAR-Iscte, a leading research center in Information Sciences, Technologies, and Architecture. His academic leadership includes directing various degree programs and serving on institutional governance bodies such as the Scientific Committee and General Council. PhD in Information Sciences and Technologies (ISCTE-IUL, 1999) Master's in Business Sciences (ISCTE-IUL, 1992) Bachelor's in Business Organization and Management (ISCTE-IUL, 1988) His research focuses on Information Systems , NoSQL databases , formal modeling of organizations , and big data management . He explores applications in distributed systems, semantic web, and data mining for business intelligence and public policy. His work bridges theoretical modeling and practical implementation in enterprise IT environments. His recent publications span high-impact journals in transportation, tourism, education, and information systems. Key themes include semantic interoperability in bibliographic data , passenger rail disruption management , data mining for guest satisfaction , and social media engagement in sports and fashion . His research consistently applies computational and analytical methods to real-world organizational challenges. Pedro Ramos has played a central role in developing and coordinating master's programs in Information Systems and related fields. He actively supervises both Master’s and PhD students, with ongoing projects in formal ontologies, public policy, business performance, and decision support systems. He has also contributed to institutional research projects funded by European programs. He leads research at ISTAR-Iscte and has held key administrative roles, including Director of the Department of Information Science and Technology and leadership in academic councils. His work integrates research, teaching, and institutional development.

Sam Conrad Joyceمشاهده پروفایل

دانشیار

• Architectural Design
• Design Computation
• Generative AI
• +۷ مورد دیگر

Sam Conrad Joyce is an Associate Professor at Singapore University of Technology and Design (SUTD), holding a joint appointment in the Architecture and Sustainable Design pillar. He serves as the PhD Programme Coordinator and leads the Spatial AI Studio under the Design and Artificial Intelligence (DAI ASD) initiative. Joyce heads the Meta Design Lab, focusing on the integration of computation, design, and urban systems to enhance collaborative human-machine workflows in architecture and master planning. His research emphasizes generative design, big data analytics, machine learning, and web-based visualization to augment design processes. Before joining SUTD, Joyce worked at Foster + Partners (2008–2015) and Buro Happold (2009–2011), contributing to high-profile projects such as the Apple Campus and the Louvre Abu Dhabi. His doctoral work at the Universities of Bath and Bristol explored data-rich systems for design space exploration and decision-making, integrating distributed computing, optimization, and visualization. Key research interests include design optimization, spatial big data analytics, AI-driven design collaboration, and web-based tools. Joyce has led projects funded by entities like URA-SUTD, Singapore Aviation, and Changi General Hospital. His work bridges academia and practice, emphasizing practical applications of computational methods in architecture and urban design. He has taught globally, including at the Architectural Association (London) and Chalmers University (Sweden), and collaborates on initiatives like the Venice Biennale and Smart Geometry conferences. His research outputs span design computation, AI integration, and urban analytics, reflecting a commitment to advancing innovative, data-informed design practices.

Neerja Mhaskarمشاهده پروفایل

استادیار

• String Algorithms
• Algorithms and Data Structures
• Network Security
• +۴ مورد دیگر

Neerja Mhaskar is an Assistant Professor in the Department of Computing and Software at McMaster University's Faculty of Engineering. She is currently accepting graduate students and maintains an active research group. Her office is located in ITB 220, and she can be reached at pophlin@mcmaster.ca. Her educational background includes a PhD in Computer Science from McMaster University (2016), a Master's degree in Engineering Science from Louisiana State University, and a Bachelor's degree in Mechanical Engineering from Jawaharlal Nehru Technological University Hyderabad, India. Dr. Mhaskar's research focuses on the design and analysis of efficient algorithms and data structures, with particular emphasis on string processing for applications in bioinformatics, network security, and data compression. She develops algorithms for pattern matching, secure network design, and big data analysis. Her work bridges theoretical computer science with practical applications in privacy and security, as well as computational biology. Her recent publications demonstrate a strong trend in string algorithms, especially in covering problems and indeterminate strings, with growing applications in network security and bioinformatics. Over the past decade, she has contributed to foundational stringology and expanded into network segmentation and protein sequence analysis. Dr. Mhaskar has not been mentioned to have received any scientific awards in the provided text. Dr. Mhaskar has successfully supervised multiple graduate students. Her current advisees include PhD candidates Shafigh Ashrafi, Hamed Hasibi, Nivetha Raj Pappuraj, and Amin Kashef, as well as Master's students Samkith Kishore Kumar Jain and Shutong Wu. Among her graduated students are Tieyun Zhang, Meng Wang, Chenge Liu, Zehong Wang, Hossein Dehghani, and Holly Koponen, who have gone on to work at companies such as Siemens Canada, Robinhood, and Robotic Assistance Devices, or pursued further studies.

James G Boothمشاهده پروفایل

استاد

• Statistics
• Computational Biology
• Bioinformatics
• +۵ مورد دیگر

James G Booth is a Professor in the Department of Biological Statistics and Computational Biology at Cornell University , a position he has held since 2004. He also holds an appointment in the Department of Statistical Science within the Computing and Information Science school. His academic career spans prior faculty roles at the University of Florida (1987-2003) and research fellowships at the Australian National University and Colorado State University. Ph.D. in Statistics, University of Kentucky (1987) B.S. in Mathematics, University of Leeds (1981) Booth's research focuses on statistical methodology for biological data, including bootstrap/Monte Carlo methods, mixed models, generalized linear models, and variable selection. His work bridges computational statistics with applications in bioinformatics, epidemiology, and social science, particularly in disease surveillance, antimicrobial resistance analysis, and religion-climate change dynamics. Recent publications emphasize Bayesian modeling , high-dimensional classification , wildlife disease prediction , and social determinants of climate policy indifference . He has contributed to software tools like MAGMa for proteomic analysis and RRmix for metabolomics batch correction.

• XML Database Systems
• Cloud Computing Security
• Data Stream Mining
• +۵ مورد دیگر

Eric Pardede is a professor at the School of Computing and Mathematics of Western Sydney University . He has an extensive publication record in data management, cybersecurity, and technology-enhanced learning, often collaborating with researchers like Wenny Rahayu, David Taniar, and A. S. M. Kayes. Research Focus: XML database systems, cloud computing security, data stream mining, and educational technology Award-Winning Contributions: Notable work on IoT security frameworks, blockchain risk assessment, and adaptive learning systems Recent Publications: 15 articles from 2021-2025 address topics like concept drift adaptation, cybersecurity in multi-cloud environments, and smart education tools Key Collaborations: Frequent partnerships with researchers in Australia, Indonesia, and Austria

Carsten Trinitisمشاهده پروفایل

استاد

• High Performance Computer Architectures
• Microprocessor Architectures
• Co-design
• +۵ مورد دیگر

Prof. Dr. Carsten Trinitis is a full professor at the Chair of Computer Architecture & Parallel Systems within the TUM School of Computation, Information and Technology. Specializing in high-performance computer architecture with a unique focus on spaceflight applications and informatics ethics, he leads the 'Gesellschaft für Informatik und Ethik' (Society for Informatics and Ethics). Ph.D. in Electrical Engineering from TUM (1998) Industry experience before returning to academia Former Assistant Professor in History of Science (2002-2010) at Universität der Bundeswehr München Full Professor of Distributed Computing at University of Bedfordshire (2010-2014) His research spans three major domains: High-Performance Computing: Focused on microprocessor architectures, hardware-oriented optimizations, and co-design approaches. Recent work includes GPU power capping strategies and Data Distribution Service (DDS) middleware enhancements. Space Systems: Pioneering computer architectures for nanosatellites with projects like MOVE-II mission and MicroPython-based satellite control systems. Digital Ethics: Through his 'Gewissensbits' initiative, he explores ethical decision-making frameworks for technology and contributes to the German Informatics Society's ethical guidelines. Key publication trends show interdisciplinary work connecting: HPC systems and edge AI applications FPGA-based verification and RISC-V processors Time series analysis at petascale performance Hardware-software co-design for extreme environments Continued emphasis on ethical computing frameworks Scientific Recognition: TeachInf Award for Outstanding Teaching (2023) Hans Meuer Award for Best Paper (2020) ZARM Master Thesis Awards (2016, 2017) Prof. Trinitis leads multiple research projects including: SEANERGYS (EuroHPC) - Energy-efficient computing systems PlasmaPEPS - Plasma physics simulation environments OpenCUBE - Open computing frameworks for space MUNIQC-ATOMS - Quantum computing integration

János Tóthمشاهده پروفایل

استادیار مدعو

• Ensemble Systems Optimization
• Big Data Analytics
• Machine Learning
• +۳ مورد دیگر

Dr. János Tóth is an Adjunct Assistant Professor at the Department of Data Science and Visualization within the Faculty of Informatics at the University of Debrecen. His research focuses on optimization of ensemble systems and big data analytics. Institution: University of Debrecen School: Faculty of Informatics Department: Data Science and Visualization Rank: Adjunct Assistant Professor Email: toth.janos@inf.unideb.hu Research Interests: Dr. Tóth specializes in optimizing ensemble systems for medical image analysis and big data processing. His work spans: Parameter optimization techniques for ensemble models Integration of classical image processing with deep learning Medical data visualization solutions Applications in diabetic retinopathy detection Handling unstructured Hungarian medical reports Cloud-based machine learning pipelines Publication Trends: Over the past decade, Dr. Tóth's research has shown consistent focus on medical image analysis (particularly fundus and Pap smear imaging) combined with ensemble learning approaches. His work includes algorithm optimization (2014-2022), data visualization techniques (2012-2024), and natural language processing for Hungarian medical reports (2024). Recent publications (2024) demonstrate continued innovation in machine learning applications for both healthcare and business domains.

Ron Doyleمشاهده پروفایل

استاد

• Cloud Computing
• Distributed Systems
• Artificial Intelligence
• +۳ مورد دیگر

Dr. Ron Doyle holds the Katherine and Dickerson Wright Presidential Chair of Computer Science and Entrepreneurship at Wake Forest University. He received his PhD in Computer Science from Duke University in 2003, following undergraduate and graduate studies at West Virginia University. With over 20 years at IBM and a recent tenure as Chief Technology Officer at Broadcom (2018-2023), he brings extensive industry experience to academia. His research lies at the intersection of computer science and entrepreneurship, focusing on Cloud Computing Distributed Systems Artificial Intelligence Web Application Development Automation Entrepreneurial Innovation . He bridges technical expertise with business insights to help students launch startups. Dr. Doyle holds over 50 U.S. patents and has published extensively on cloud service delivery, edge processing, web quality of service, and content optimization. As a joint appointee in Wake Forest's Center for Entrepreneurship, he mentors student ventures and develops curriculum. His industry accolades include IBM's Distinguished Engineer and Master Inventor titles. Scientific awards include: Distinguished Engineer at IBM Master Inventor at IBM Over 50 U.S. Patents His work demonstrates trends in cloud technologies (adaptive edge processing, SLA enforcement, resource optimization) and AI (offensive language detection). He also contributes to mobile cloud integration and secure device configuration.