جست‌وجوی استاد و پژوهشگر

Huong Haمشاهده پروفایل

مدرس ارشد

• Machine Learning
• Software Engineering
• Automated Machine Learning
• +۵ مورد دیگر

Dr. Huong Ha is a tenured Senior Lecturer in Computer Science and Program Manager of the Bachelor of Computer Science at the School of Computing Technologies, RMIT University, Australia. Previously, she worked at the Applied Artificial Intelligence Institute (A2I2), Deakin University, Australia. She received her PhD from the University of Newcastle, Australia in May 2017. Her educational background includes: PhD in Computer Science from the University of Newcastle, Australia (2017) Dr. Ha's research focuses on the intersection of Machine Learning and Software Engineering, specializing in Automated Machine Learning (particularly Bayesian Optimization), Trustworthy Machine Learning, and Data-driven Software Engineering. Her work addresses critical challenges in intelligent incident management of software systems and quality prediction and optimization for software systems. She has made significant contributions to root cause analysis for microservice systems using causal inference and Bayesian optimization techniques. Her publication record shows a strong trend in applying advanced machine learning techniques to software engineering problems, particularly in microservices architecture. Her recent work demonstrates expertise in developing benchmarking frameworks (RCAEval) and optimization methods (MOCA-HESP) that bridge theoretical advancements with practical applications in software systems. Dr. Ha has received numerous awards and recognitions: Top High-volume Course at RMIT (Semester 1, 2025) Outstanding Reviewer of KDD 2025 Research Track Special Commendation for 2024 RMIT STEM College Learning and Teaching Award ACM SIGSOFT Best Artifact Award at FSE 2024 Top Reviewer of NeurIPS 2022-2023 As Program Manager of the Bachelor of Computer Science, Dr. Ha plays a key role in curriculum development and academic leadership. She actively supervises PhD students including Thuan (Solving Mathematical Problems with LLMs) and Thanh (Fraud Detection for Blockchain Networks), and has secured multiple research grants including the OpenAI Researcher Access Grant (10,000 USD) and several RMIT RACE Merit Allocation Scheme grants. Her academic service includes serving on program committees for major conferences in both machine learning (NeurIPS, ICML) and software engineering (ASE, ICSE).

• Automation and Control Systems
• Cyber-Physical Systems
• Networked Control Systems
• +۳ مورد دیگر

Professor Peng Shi is a faculty member in the School of Electrical and Mechanical Engineering at the University of Adelaide, specifically within the Department of Electrical and Electronic Engineering. He holds a Professor rank and is actively involved in research and academic leadership. Academic Rank: Professor Affiliations: University of Adelaide, School of Electrical and Mechanical Engineering Research Interests: Automation and control systems, cyber-physical systems, networked control systems, autonomous robotics, artificial intelligence, and control theory. Professor Shi has an extensive track record in research, with over 30 years of contributions to advanced control theory and interdisciplinary applications. He has authored 25 monographs, 800+ journal articles, and numerous conference papers, generating over 90,000 citations with an h-index of 164. His work emphasizes cyber-physical systems, human-machine collaboration, and resilient control under cyber attacks. His recent publications (2023–2025) focus on advanced control methodologies for robotics, power systems, and cybersecurity, addressing challenges such as fault diagnosis, consensus control, and secure estimation in networked environments. Scientific Awards: Fellowships from IEEE, IET, IMA, IEAust, and IETI Highly Cited Researcher (2014–present) Professor Shi advises students in advanced control systems and collaborates on grants related to smart grids, robotics, and cybersecurity. He leads research groups focused on resilient control systems and has developed methodologies for distributed control and fault-tolerant designs.

• Optimization
• Operational Research
• Heuristics
• +۳ مورد دیگر

Andrew J. Parkes is an Assistant Professor (Lecturer) in Operational Research and Computer Science at the University of Nottingham , affiliated with the School of Computer Science and the COL research group (formerly ASAP). He has been a member of the LANCS Initiative's executive committee and co-organized multiple streams at international conferences like OR61, EURO 2019, and OR60. His research spans optimization techniques, heuristic methods, and applications in timetabling and financial modeling.

Federica Sarroمشاهده پروفایل

استاد

• Predictive Analytics for Software Engineering
• Search-Based Software Engineering
• Empirical Software Engineering
• +۴ مورد دیگر

Federica Sarro is a Professor of Software Engineering at the Department of Computer Science, University College London (UCL). She leads the SOLAR group, focusing on Predictive Analytics, Search-Based Software Engineering, and Empirical Software Engineering. Her research emphasizes software testing, effort estimation, and app store analysis, with over 70 peer-reviewed publications and collaborations with 20+ institutions worldwide. Her research has been supported by grants including the €2.1M ERC EPIC grant and a £6.8M EPSRC Programme Grant (DAASE). She has supervised numerous PhD students and postdoctoral researchers, including graduated scholars like Afnan Al-Subaihin and William Martin. She is actively involved in program committees and editorial roles, including Associate Editor for ACM TOSEM and IEEE Transactions on Evolutionary Computation. Key achievements include the ACM Distinguished Paper Award (2019), the GECCO-HUMIES Medal (2016), and leadership roles in conferences like ICSE, FSE, and SSBSE. Her work bridges software engineering with machine learning and data analytics, addressing challenges in testing, defect prediction, and agile practices.

Raúl Ordóñezمشاهده پروفایل

استاد

• Nonlinear Control
• Adaptive Control
• Extremum-Seeking Control
• +۴ مورد دیگر

Raúl Ordóñez is a full professor and Director of Graduate Programs in the Department of Electrical and Computer Engineering at the University of Dayton’s School of Engineering. He holds a Ph.D. and M.S. in Electrical Engineering from The Ohio State University (2001 and 1996) and a B.E. from Monterrey Institute of Technology. His research focuses on nonlinear control, adaptive systems, extremum-seeking control, and applications in aerospace, robotics, and power systems. Professional highlights include serving as Associate Editor for Automatica since 2006, co-authoring textbooks on adaptive control and extremum-seeking techniques, and holding editorial roles for IEEE conferences. Awards include the Boeing Welliver Faculty Fellowship (2008) and AFRL Summer Faculty Fellowship (2014). He has conducted research collaborations at institutions like Université de Picardie Jules Verne (France) and TU Wien (Austria). Key research areas include control of hypersonic vehicles, industrial robots, scramjets, and power generators. His work integrates advanced control methodologies with practical systems, emphasizing real-time optimization and robustness. Courses taught span control systems, nonlinear dynamics, and adaptive control. Education: Ph.D./M.S. (Ohio State), B.E. (Monterrey Tech) Professional Activities: IEEE Control Systems Society, CCCS Collaborative Center Recent Awards: AFRL (2014), Boeing (2008) Labs/Teams: Collaborates with robotics and aerospace teams at UD and international institutions

Bern Jordanمشاهده پروفایل

پژوهشگر

• Accessibility and Inclusive Design
• Human-Computer Interaction
• Assistive Technology
• +۳ مورد دیگر

Bern Jordan is an Assistant Research Scientist at the University of Maryland’s College of Information Studies (INFO). With a Ph.D. in biomedical engineering, his work focuses on accessibility of information and communications technology (ICT), emphasizing cross-disability access to public systems, standards development, and inclusive design. He leads projects like the Maryland Initiative for Digital Accessibility (MIDA) and the Rehabilitation Engineering Research Center on Inclusive ICT (Trace RERC). His expertise includes kiosk accessibility, auto-personalization software, and accessibility training. He collaborates with federal agencies (e.g., FCC, NIH, NIST) and organizations like the Smithsonian and FDIC to advance accessibility policies and technologies. Recent work includes improving at-home test accessibility for the NIH’s RADx Tech initiative and developing tools like FormA11y for PDF remediation. Dr. Jordan has 10 patents in kiosk and touchscreen accessibility, and his research spans 50 years of Trace Center innovations. His articles emphasize user-centric design, inclusive technologies, and bridging gaps between accessibility standards and real-world practices. He advocates for auto-hyper-personalization systems to democratize technology access globally.

N. Katherine Haylesمشاهده پروفایل

استاد

• Critical Theory
• Science Fiction
• Electronic Textuality
• +۲ مورد دیگر

N. Katherine Hayles is a Professor of Literature at Duke University, Durham, NC, USA, with a career spanning institutions such as the University of California, Los Angeles (UCLA) and Rochester Institute of Technology. Her work bridges literature, science, and technology, establishing foundational contributions to posthuman studies and digital humanities. She is a member of the American Academy of Arts and Sciences (2015) and has held prestigious fellowships at the National Humanities Center, Princeton University, and the Rockefeller Foundation's Bellagio Center. Research Interests : Interdisciplinary studies connecting literature, science fiction, electronic textuality, and the intersections of literature, science, and technology in the 20th and 21st centuries. Publications : Her influential works include How We Became Posthuman (1999), Writing Machines (2002), and How We Think (2012), alongside articles analyzing experimental fiction, cognitive shifts, and digital media. Scientific Awards : 2015 : American Academy of Arts and Sciences, Institute for Advanced Study Fellowship (Durham University) 2010 : Honorary Doctorate (Art College of Design), Innovation Hall of Fame Inductee (Rochester Institute of Technology) 2007 : Honorary Doctorate (Umea University, Sweden) 2002 : Susanne E. Langer Award ( Writing Machines ), René Wellek Prize, Eaton Award. Grants : Digital Publishing Grant ($10,000) from Duke University's Franklin Humanities Institute and co-directorship of a $225,000 grant for the GreaterThanGames Humanities Laboratory (2011-2014). Current Projects : Collaborating with Durham University's Emergence group on Cognition Everywhere , exploring automated finance algorithms as forms of cognition.

• Organic Computing
• Evolutionary Algorithms
• Learning Classifier Systems
• +۶ مورد دیگر

Professor Jörg Hähner holds the Chair of Organic Computing at the University of Augsburg's Faculty of Applied Computer Science within the Institute of Computer Science. He leads a research team focused on evolutionary computation, self-organizing systems, and intelligent computing approaches. His educational background includes computer science studies at TU Darmstadt. His academic career progression shows steady advancement in the field of organic and self-organizing computing systems. Prof. Hähner's research spans multiple interconnected domains in computational intelligence. His primary focus is on Organic Computing, which involves developing systems that can adapt and self-organize in complex environments. Within this framework, he has made significant contributions to Evolutionary Algorithms, particularly Cartesian Genetic Programming and Learning Classifier Systems. His work explores how these techniques can be applied to real-world problems such as predictive maintenance, energy systems optimization, and industrial automation. The research demonstrates a strong emphasis on both theoretical foundations and practical applications of self-adaptive systems. An analysis of his recent publications reveals a strong concentration on evolutionary computation techniques, particularly Cartesian Genetic Programming variants and Learning Classifier Systems. His research group has been actively developing frameworks like CRust_GP and GRAHF to advance modular construction of evolutionary algorithms. There's a clear trend toward applying these techniques to industrial problems including predictive maintenance, resource allocation in networks, and energy management systems. The publications show consistent exploration of fundamental questions about algorithm behavior while maintaining strong connections to practical applications. Prof. Hähner leads an active research group with numerous PhD students and collaborators, including Karen Poloczek, Henning Cui, Victor Gerling, Dr. Michael Heider, Marco Hüller, Neele Kemper, Helena Stegherr, Jonathan Wurth, and Roman Sraj. His team regularly publishes in top-tier conferences and journals in evolutionary computation, intelligent systems, and industrial applications. The Organic Computing research group maintains a strong presence in both theoretical and applied research, with projects spanning from foundational algorithm development to industrial applications in manufacturing, energy systems, and network optimization. The group's work demonstrates a cohesive research vision centered on creating adaptive, self-organizing computational systems that can operate effectively in complex real-world environments.

Seyed Ziae Mousavi Mojabمشاهده پروفایل

استادیار

• Data Mining
• Machine Learning
• Evolutionary Algorithms
• +۶ مورد دیگر

Seyed Ziae Mousavi Mojab is an Assistant Professor (Teaching) in Computer Science at Wayne State University's James and Patricia Anderson College of Engineering. He holds a B.S.E. in Computer Science from the University of Michigan Ann Arbor, and both M.S. and Ph.D. degrees in Computer Science from Wayne State University. His research focuses on evolutionary computation, optimization methods, workflow scheduling, medical image processing, data analytics, and business intelligence. Key investigations include cultural algorithms for big data workflows, deep learning ensembles for medical diagnostics, and neural architecture synthesis techniques. Recent publications demonstrate applications in robotic surgical segmentation (2023), COVID-19 detection via chest X-ray analysis (2020-2021), and optimization frameworks for cloud-based big data systems (2019-2022). Research consistently integrates evolutionary computation with deep learning architectures across medical and data-intensive domains.

Gary Hallمشاهده پروفایل

استاد

• Digital Culture
• Media Theory
• Open Access Publishing
• +۵ مورد دیگر

Gary Hall is a Professor of Media and Performing Arts and Executive Director of the Centre for Postdigital Cultures at Coventry University. His research explores digital culture, radical publishing, and institutional critique, emphasizing collaborative, non-profit models and hyper-political approaches to media theory. He co-founded Open Humanities Press (OHP) and led the COPIM project, advocating for community-led open access infrastructures. Key projects include the COPIM initiative (2019–2023), which developed open access book publishing systems, and the Combinatorial Books series. His work interrogates capitalism, academia, and technology through publications like Pirate Philosophy (2016) and Masked Media (2025). He blogs at garyhall.info , blending theory with activism. Research interests span media philosophy, posthumanities, open access advocacy, and institutional reform. Collaborative projects include the Living Books About Life series and the Radical Open Access Collective. His experimental methods challenge traditional academic frameworks, prioritizing collective action and non-rivalrous models.

Silun Zhangمشاهده پروفایل

استادیار

• Nonlinear Control
• Large-Scale Complex Systems
• Privacy-Preserving Algorithms
• +۳ مورد دیگر

Silun Zhang is an Assistant Professor in the Department of Mathematics at KTH Royal Institute of Technology, affiliated with WASP (Wallenberg AI, Autonomous Systems and Software Program) and the Digital Futures Faculty. He holds a Ph.D. in Optimization & Systems Theory from KTH (2019), an M.S. and B.S. in Automation from Harbin Institute of Technology, China. Prior to KTH, he was a Postdoctoral Associate at MIT's Laboratory for Information & Decision Systems (LIDS) and EECS Department (2019–2023), where he collaborated with Prof. Munther Dahleh and contributed to the MIT MicroMasters Program in Statistics and Data Science. His research focuses on nonlinear control , large-scale complex systems , privacy-preserving algorithms , and risk-averse reinforcement learning . Key areas include control on manifolds (e.g., rigid-body attitude coordination), privacy in federated learning, and moment-based modeling for collective systems. He leads projects such as 'Analysis and Synergy of Hyper-networked Autonomy' and 'Designing Interaction-Aware Multi-Robot Systems.' Current team members include Georgios Vasileiou (Ph.D.), Lantian Zhang (Postdoc), and Malintha Fernando Chakravarthige (Postdoc). His work is supported by the Wallenberg Foundations and Digital Futures. Open positions are available for motivated Ph.D. students and postdocs.

Mircea Lunguمشاهده پروفایل

دانشیار

• Software Engineering
• Virtual Reality
• Software Systems
• +۴ مورد دیگر

Mircea Lungu is an Associate Professor in Software Engineering at the IT University of Copenhagen. His research focuses on software ecosystems, software architecture, technical debt management, and immersive technologies for software development. He actively contributes to academia through publications, projects, and teaching. Affiliation: IT University of Copenhagen Academic Rank: Associate Professor Research Interests: Mircea explores the intersection of software engineering and virtual reality through projects like Immersive Software Archaeology , which leverages 3D environments for legacy system analysis. His work also addresses educational paradigms in software engineering, emphasizing live systems and experiential learning. Project Highlights: He leads the HPL-PATHS initiative (2023–2026) on hyper-personalized language education and collaborates on the ISA project (2020–2024) for virtual reality-based software exploration. Publication Trends: Recent work combines virtual reality with software engineering challenges, including collaborative exploration tools, technical debt visualization, and immersive analytics. His academic output spans conference proceedings, journal articles, and systematic reviews. Contact: Email: mlun@itu.dk

• Optical Networking
• Machine Learning in Network Automation
• Physical Layer Security
• +۳ مورد دیگر

Carlos Natalino Da Silva is a Researcher at Chalmers University of Technology's Optical Networks Unit , focusing on network automation and machine learning applications in optical network design and security. His work addresses resource efficiency (e.g., spectrum optimization), physical layer security , and 6G readiness , with involvement in EU and Brazil-funded projects. He has also contributed to computer programming education in Brazil and Sweden. Research Interests : Machine learning for optical networks Network automation and programmability Physical layer security 6G network readiness Distributed computing optimization Recent Article Trends : His 2025-2024 publications emphasize ML for QoT estimation , state-of-polarization analysis , hybrid FSO-THz for 6G , and DRL-assisted resource allocation , reflecting a focus on convergence between AI, security, and next-gen optical systems. Projects & Collaborations : Current initiatives include Resilient Remote Environment Emulation (2025-2025, ARC-funded), ECO-eNET (2024-2028, EU), and EMPOWER - 6G (2024-2027). Past projects span PHOTONIC HARDWARE (VR-funded), TeraFlow (EU), and ANIARA (VINNOVA).

Mohammed Abuibaidمشاهده پروفایل

استاد مدعو

• Hyper-Reliable and Low-Latency Communications
• Industrial Automation Networks
• 5G Networks and Beyond
• +۷ مورد دیگر

Dr. Mohammed Abuibaid is an Adjunct Research Professor at Carleton University's School of Information Technology and a Radio Virtual Distributed Unit (vDU) System Designer at Ericsson Canada. As a Senior IEEE Member, he contributes significantly to standards development through IEEE 802 Plenary Sessions and ITU-T Study Group 15 initiatives. His expertise lies in wireless communications with a focus on industrial applications, where he bridges academic research and industry implementation. Dr. Abuibaid earned his Ph.D. from Carleton University, Canada, where he has continued his academic contributions. His educational background has positioned him as a leading expert in next-generation wireless communication systems. Dr. Abuibaid specializes in Hyper-Reliable and Low-Latency Communications (HRLLC) for industrial automation, with research spanning 5G networks and beyond, Time-Sensitive Networking (TSN), Deterministic Networking (DetNet), Massive MIMO systems, and Edge Computing. His innovative approach integrates machine learning techniques to optimize network performance, particularly in balancing reliability with bandwidth utilization in industrial settings. His work addresses critical requirements for Industry 5.0, focusing on resilient networks that can support advanced manufacturing and automation systems. His publication record demonstrates a consistent focus on integrating wireless communication standards with industrial networking requirements. Dr. Abuibaid's research trajectory shows increasing sophistication in addressing the reliability-bandwidth tradeoff through machine learning frameworks and novel system designs that optimize resource utilization while maintaining critical performance metrics for industrial applications. Dr. Abuibaid has received notable recognition for his contributions: Best Industry Paper Award at the 2024 IEEE 10th World Forum on Internet of Things Senior Member of IEEE (since April 2024) As an academic mentor, Dr. Abuibaid supervises student research at Carleton University, focusing on next-generation wireless communication systems. His industry-academic partnership with Ericsson has resulted in significant research funding, including support from the Ericsson-Carleton Partnership Fund and MITACS Canada for the 5G-TSN for Industry 4.0 project. These collaborations have produced innovative solutions that address real-world challenges in industrial networking. Dr. Abuibaid has contributed to establishing the 6G Non-Terrestrial Networks Research Center, collaborating with global technology leaders like Keysight Technologies. His work spans both terrestrial and satellite communication systems, reflecting his comprehensive approach to next-generation network design. He actively participates in standards development through IEEE and ITU-T, ensuring his research has practical impact on emerging communication technologies.

• Artificial Intelligence
• Neural Networks
• Robotics
• +۵ مورد دیگر

Abdullatif Baba is an Assistant Professor in the Department of Computer Engineering at Turkish Aeronautical Association University. His research focuses on interdisciplinary applications of artificial intelligence, robotics, and sustainable energy systems. He develops solutions for smart infrastructure, including AI-driven energy forecasting, autonomous drones for grid maintenance, and hyperspectral imaging techniques. His research interests span: AI/ML Systems : Neural networks, probabilistic forecasting, and FPGA-accelerated deep learning Robotics : Autonomous drones with computer vision for industrial and energy applications Sustainable Energy : Solar-based systems, smart grid optimization, and consumption prediction Security : Chaos-based cryptographic systems for secure communications Recent publications (2020-2024) demonstrate strong trends in practical AI implementations. Key themes include energy forecasting using adaptive neural networks (11 papers), robotics for infrastructure maintenance (4 papers), computer vision for biometrics and imaging (3 papers), and cryptographic systems (2 papers). Methodologies frequently involve hybrid approaches combining ANN, fuzzy logic, and hardware acceleration. No awards, students, or grant details were mentioned in the source material. Research collaborations include institutions in Turkey and the Middle East.