جست‌وجوی استاد و پژوهشگر

A. Erdem Sariyuceمشاهده پروفایل

دانشیار

• Graph Mining
• Social Network Analysis
• Network Science
• +۴ مورد دیگر

A. Erdem Sariyuce is an Associate Professor in the Department of Computer Science and Engineering at the University at Buffalo, part of the School of Engineering and Applied Sciences. His research focuses on graph mining, network science, and distributed computing. He holds a PhD from Ohio State University (2015) and a BS from Middle East Technical University (2010). His work explores temporal network analysis, social network dynamics, and algorithm design for large-scale systems. Notable contributions include methods for motif detection, core decomposition, and stream processing in bipartite networks. Sariyuce has received prestigious awards such as the NSF CAREER Award (2023) and the UB Exceptional Scholar—Young Investigator Award (2023). His research is supported by grants including the LDRD Project at Sandia National Laboratories (2016-2017). Education: PhD, Computer Science and Engineering, Ohio State University, 2015 BS, Computer Engineering, Middle East Technical University, 2010 Research interests emphasize graph algorithms, network resilience, and parallel computing. His recent projects include analyzing financial networks, identifying cohesive communities, and developing efficient algorithms for temporal data. His work bridges theoretical foundations with practical applications in social media, cybersecurity, and bioinformatics. Awards: UB Exceptional Scholar—Young Investigator Award (2023) NSF CAREER Award (2023) SEAS Early Career Researcher of the Year (2020) Advising and grants highlight his leadership in collaborative projects, including the NSF-funded Collaborative Research: OAC Core: Fast Tools for Complex Event Detection over Bipartite Graph Streams (2021). His research often involves industry partnerships and government labs, such as Sandia National Laboratories.

NAOFAL AL-DHAHIRمشاهده پروفایل

استاد

• Broadband Wireless Communication
• Machine Learning
• Signal Processing
• +۶ مورد دیگر

Dr. Naofal Al-Dhahir is the Erik Jonsson Distinguished Professor of Electrical and Computer Engineering at University of Texas at Dallas , affiliated with the Erik Jonsson School of Engineering and Computer Science . He serves as Associate Department Head for Undergraduate Education and leads the Broadband Information Transmission & Signal Processing (BITS) Laboratory . His research focuses on 6G communications, intelligent reflecting surfaces (IRS), federated learning, integrated sensing and communication (ISAC) , and wireless security. With over 600 publications and 43 US patents, he is an IEEE Fellow (2008), NAI Fellow (2020), and recipient of numerous awards including the 2022 IEEE RCC Technical Recognition Award and 2021 Qualcomm Faculty Award. Educations: PhD (Stanford University, 1994), MSc (Stanford University, 1990) Professional Roles: Editor-in-Chief of IEEE Transactions on Communications (2016-2019), Technical Staff at GE Global Research and AT&T Labs (1994-2003) Research Interests His work spans IRS-based 6G systems, machine learning for communications, vehicular networks, and smart-grid technologies . Recent contributions include secure ISAC designs and low-complexity signal processing algorithms. Collaborations with industry leaders like Qualcomm and Apple highlight his impact on practical applications. Students & Labs Alumni include professionals at Qualcomm, Apple, and NASA. The BITS Lab has hosted researchers from global institutions like KAUST and Xidian University. Current projects explore covert communications, Movable Antenna Systems (MAS), and AI-driven spectrum management .

• Reinforcement Learning
• Stochastic Dynamic Optimization
• Operations Research
• +۷ مورد دیگر

Somayeh Moazeni is an Associate Professor at the School of Business, Stevens Institute of Technology. She holds a PhD in Computer Science from the University of Waterloo and has held academic appointments including Visiting Associate Professor at Northwestern University and Postdoctoral Research Associate at Princeton University. Her research focuses on Reinforcement Learning, Stochastic Dynamic Optimization, and applications in Energy Markets, Inventory Management, and Algorithmic Trading. She has authored over 30 peer-reviewed articles and serves as an associate editor for INFOR and PLOS One . Education: PhD (Computer Science, 2012), University of Waterloo; Postdoc (Operations Research, 2012-2014), Princeton University Industry Experience: Senior Risk Analyst at RBC (2011-2012), Risk Analyst at BMO (2010) Awards: IEEE Senior Member (2019), Anita Borg Institute GHC Faculty Scholar (2017), MITACS Poster Competition First Place (2009) Her research spans Bayesian Optimization , Resilient Network Design , and Energy Efficiency . Current funded projects include PSEG Foundation grants for energy resilience and NSF funding for distributed energy resource controls. She advises PhD students in Operations Research and Energy Systems and teaches graduate courses in Reinforcement Learning and Financial Engineering. Key Contributions: Developed stochastic optimization frameworks for energy storage, contact center reliability modeling, and risk-aware trading strategies. Her work on sequential learning for consumer-driven demand response programs has advanced smart grid applications.

Patrick McCormickمشاهده پروفایل

استادیار

• Radar Systems
• Signal Processing
• RF Engineering
• +۳ مورد دیگر

Patrick McCormick is an Assistant Professor and Assistant Scientist in the Department of Electrical Engineering and Computer Science (EECS) and the Institute for Information Sciences (I2S) at the University of Kansas. He joined the university in 2021 after working at the Air Force Research Laboratory - Sensors Directorate (2018-2021). His research focuses on RF systems, signal processing, and waveform design for radar and communication systems. B.S. Mechanical Engineering, University of Kansas (2008) B.S. Electrical Engineering, University of Kansas (2013) Ph.D. Electrical Engineering, University of Kansas (2018) McCormick’s research areas include optimal emission design, multifunction transmissions, hardware characterization/compensation, and adaptive model-based parameter estimation. He leads the Radar Systems and Remote Sensing Laboratory (RSL) and has published extensively in radar waveform diversity, spectrum sharing, and adaptive signal processing. Recent work trends emphasize dual-function radar-communications co-design, low-cost systems, nonlinear hardware characterization, and digital array optimization. His publications span topics like waveform optimization, mutual coupling compensation, and power-efficient joint systems. IEEE Aerospace and Electronic Systems Society 2018 Robert T. Hill Best Dissertation Award He advises graduate students and collaborates with researchers at institutions like the Air Force Research Laboratory (AFRL), University of Oklahoma (OU), and international conferences. His service includes conference chairs, special session organization, and journal reviewing for IEEE Transactions on Signal Processing and Aerospace Systems. McCormick holds memberships in IEEE, Signal Processing Society, and Young Professionals. His lab seeks motivated graduate students for research in radar waveform design and RF systems.

Xiao Liمشاهده پروفایل

استادیار

• Blockchain Technology
• Distributed Systems
• Machine Learning
• +۷ مورد دیگر

Dr. Xiao Li is an Assistant Professor in the Department of Computer Science and Engineering at Santa Clara University, School of Engineering. His research focuses on blockchain technology applications in distributed systems (Edge Computing, IoT, Federated Learning), machine learning, and privacy-preserving frameworks. He has a Ph.D. in Computer Science from The University of Texas at Dallas (2024) and was awarded the Jan P. Van der Ziel Engineering Fellowship there. Education: Ph.D. in Computer Science, The University of Texas at Dallas, 2024 Research interests include: Blockchain architecture optimization in resource-constrained environments Machine learning model development for cryptocurrency analysis Cybersecurity disclosure sentiment analysis using unsupervised techniques Low-resource data challenges in psychiatric clinics Professional activities: Program Committee Member, IEEE International Workshop on Blockchain and Smart Contracts (IEEE BSC 2024) Recruitment of PhD/Master’s students specializing in blockchain, distributed machine learning, and edge computing Office Location: Bergin 206 Office Hours: Mon/Wed 4pm-5pm (Winter 2025)

Amirali Abariمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Machine Learning
• Computational Decision Making
• +۷ مورد دیگر

Dr. Amirali Abari is an Associate Professor in the Faculty of Business and Information Technology at Ontario Tech University, specializing in Artificial Intelligence, Machine Learning, and Computational Decision Making. His research focuses on decision-making under uncertainty, including preference learning, group recommendation systems, and probabilistic inference. He holds a PhD in Computer Science from the University of Toronto (2016) and was an NSERC Postdoctoral Fellow at the University of Toronto and University of Waterloo. Dr. Abari's research has been recognized with awards including the NSERC Postdoctoral Fellowship and a U.S. patent. He serves on program committees for top AI conferences (e.g., AAAI, IJCAI) and reviews for journals like IEEE Transactions and ACM Transactions. His work bridges computational methods with real-world applications in supply chain optimization, risk management, and sustainable infrastructure planning. Key contributions include integrating machine learning with queueing theory for EV charging stations, stochastic optimization for resilient supply chains, and decision support systems for industrial processes. His research group collaborates with industry partners to apply AI-driven solutions to business analytics and operations challenges. Education: PhD in Computer Science, University of Toronto (2016) Awards: NSERC Postdoctoral Fellowship, Bell Scholarship, Student Best Paper Award Service: Program committees for AAAI, IJCAI; reviewer for IEEE, ACM, and Algorithmica

Walid Morsi Ibrahimمشاهده پروفایل

استاد

• Smart Grid
• Power Systems
• Signal Processing
• +۴ مورد دیگر

Dr. Walid Morsi Ibrahim is a Professor in the Department of Electrical, Computer and Software Engineering at Ontario Tech University, Faculty of Engineering and Applied Science. His expertise includes Smart Grid design, power systems analysis, and signal processing. He holds a PhD from Dalhousie University (2009), with prior academic positions including Adjunct Professor at the University of Waterloo and Assistant Professor roles at Ontario Tech University and the University of New Brunswick. Education: PhD (2009, Dalhousie), MSc (2002, Suez Canal University), BSc (1998, Suez Canal University) His research focuses on Smart Grid technologies, including signal processing for power systems, automation, and distributed energy resources. Notable contributions include work on electric vehicle integration, transformer aging analysis, and nonintrusive load monitoring using wavelet transforms and machine learning. He has authored over 50 publications in top-tier IEEE conferences and journals. Recent articles highlight his work on electric vehicle load forecasting during the pandemic, fault detection in photovoltaic systems, and transactive energy frameworks for prosumers. Awards include the IEEE PEDG 2010 Best Paper Award and multiple poster awards at Ontario Tech University. Dr. Ibrahim teaches courses on smart grid fundamentals, power systems operation, and information technology for engineers. He has secured grants for research on smart grid monitoring systems and holds patents related to energy management solutions. His work bridges theoretical advancements with practical grid applications, emphasizing resilience and sustainability.

• Programming Languages
• Software Engineering
• Compilers
• +۵ مورد دیگر

Manuel Rigger is an Assistant Professor at the National University of Singapore in the School of Computing and leads the Trustworthy Engineering of Software Technologies (TEST) Lab . His research focuses on improving data-centric systems , particularly their reliability, having found over 1,000 unique bugs in database systems. Education : PhD in Computer Science (2019) and MSc in Software Engineering (2015) from Johannes Kepler University Linz; MPhil in Chinese Philosophy (2015) from Xiamen University Research Highlights : Developed SQLancer – an automated testing framework that found 500+ bugs in DBMSs; created Query Plan Guidance (QPG) for efficient logic bug detection; received best paper awards at ICSE '23 and EuroSys '24 Scientific Awards : Recipient of 6 distinguished artifact/reviewer awards Major industry support from Google, AWS, and Microsoft Developed tools adopted by Oracle GraalVM and SQLite Teaching : Lecturer for CS3213 Foundations of Software Engineering and CS6223 Advanced Topics in Software Testing . Supervises multiple PhD/MSc theses on database testing and compiler reliability.

Leow Wee Khengمشاهده پروفایل

دانشیار

• Medical Image Analysis
• Computer Vision
• 3D Modeling
• +۵ مورد دیگر

Associate Professor Leow Wee Kheng is affiliated with the Department of Computer Science at the School of Computing, National University of Singapore . His career spans over three decades with expertise in medical image analysis , computer vision , and surgical simulation . Ph.D. in Computer Science, University of Texas at Austin (1994) M.Sc. in Computer Science, National University of Singapore (1989) B.Sc. in Computer Science, National University of Singapore (1985) His research focuses on medical image analysis for craniofacial surgery and stroke diagnosis, 3D modeling of anatomical structures, and computer vision techniques like robust PCA and texture analysis . Recent work includes knee joint motion modeling and forearm rotation simulation for clinical applications. Key trends in his 2017-2025 publications involve skull reconstruction algorithms , multi-objective optimization for digital media, subject-specific biomechanical modeling , and low-rank decomposition techniques in visual computing. Collaborations include institutions like Singapore General Hospital and National Taiwan University Hospital . Scientific Awards : CAIP 2017 Best Paper Award 2007 Andrew P. Sage Best Transactions Paper Award Faculty Teaching Excellence Award (AY2015/16) Annual Teaching Excellence Award (AY2015/16) He has mentored numerous students in medical imaging , computer vision , and biomedical modeling . Current and former advisees include Chen Ying , Vineta Lum Lai Fun , and Long Huizhong (Ph.D.).

Tyler Derrمشاهده پروفایل

استادیار

• Data Mining
• Social Network Analysis
• Graph Representation Learning
• +۵ مورد دیگر

Dr. Tyler Derr is an Assistant Professor in the Department of Computer Science at Vanderbilt University, with affiliate roles in the Data Science Institute and the Frist Center for Autism and Innovation. He holds a PhD from Michigan State University (2020) and focuses on data mining, machine learning, and graph neural networks with applications in drug discovery, ethical AI, and neurodiversity research. Education: PhD in Computer Science, Michigan State University (2020) M.S. in Computer Science, Pennsylvania State University B.S. in Computer Science and Mathematics, Pennsylvania State University His research emphasizes interdisciplinary social good, including drug discovery, education equity, and autism innovation. He directs the Network and Data Science (NDS) Lab, mentoring students who have won 50+ awards. Notable contributions include tools like FairNNV for fairness certification and datasets like WelQrate for drug discovery benchmarking. Awards include the NSF CAREER Award (2023), NVIDIA Academic Grant (2024), and Vanderbilt’s Career Catalyst Impact Award (2025). He co-founded the MLoG workshop series and serves on editorial boards for ACM TKDD and IEEE Transactions on Big Data . Grants & Leadership: NSF Grant for student travel to KDD2024 NVIDIA BioNeMo Platform grant for peptide design DOE Computational Science Fellowship advising His work bridges theory and practice, with tutorials on graph ML at AAAI/KDD and keynotes on ethical AI. The NDS Lab hosts interdisciplinary collaborations in computational biology, transportation, and neurodiversity advocacy.

Geerten van de Kaaمشاهده پروفایل

دانشیار

• Standardization
• Strategic Management
• Responsible Innovation
• +۳ مورد دیگر

Dr. Geerten van de Kaa is an Associate Professor of Standardization and Business Strategy at Delft University of Technology (TU Delft), affiliated with the Faculty of Technology, Policy and Management. He holds a PhD from Rotterdam School of Management, Erasmus University. His research focuses on understanding standardization processes to enable complex innovations and address societal challenges, emphasizing collaboration, market mechanisms, and strategic firm behaviors. He teaches courses on strategic management, technology strategies, and standards battles. His work has been published in high-impact journals like Organization Studies and IEEE Transactions on Engineering Management . Research Interests: Design for values, responsible innovation management, sustainable energy systems, and strategic management. He leads the Journal of Standardisation as Editor-in-Chief and collaborates on EU and NWO-funded projects. Teaching: Courses include 'Strategic Management', 'Technology and Strategy', and 'Standards Battles', emphasizing practical applications in business and policy. His research explores factors influencing standard dominance, ethical considerations in innovation, and geopolitical aspects of technology standards. Grants: Active in EU-funded initiatives and Dutch National Science Foundation (NWO) projects. Research spans semiconductor industry standards, maritime energy transitions, and blockchain standardization geopolitics. Labs/Teams: Engaged with TU Delft's Values, Technology and Innovation department and Economics of Technology and Innovation section. Collaborates with industry and policy stakeholders globally.

Jacquelien Scherpenمشاهده پروفایل

استاد

• Automation & Control Systems
• Nonlinear Control Systems
• Smart Energy Systems
• +۳ مورد دیگر

Jacquelien Scherpen is a Professor at the University of Groningen, currently serving as Rector Magnificus. She holds a position in the Engineering and Technology institute Groningen (ENTEG) within the Faculty of Science and Engineering. Her academic journey includes a PhD in Applied Mathematics from the University of Twente (1994) and post-doctoral roles at Delft University of Technology before joining Groningen in 2006. She has been a leader in systems and control research, with roles as Scientific Director of ENTEG (2013–2019) and Director of the Groningen Engineering Center (2016–2023). Her research focuses on model reduction, nonlinear control, smart energy systems, and distributed control applications in smart grids. Key achievements include the Automatica Best Paper Prize (2020), Knight of the Order of the Netherlands Lion (2019), and the Prince Friso Engineer of the Year Award (2023). She has held leadership roles in organizations like the European Control Association (EUCA) and is a Fellow of IEEE. Her professional activities include editorial roles in journals like the IEEE Transactions on Automatic Control and the International Journal of Robust and Nonlinear Control. She has organized major conferences, including the European Control Conference (ECC) 2021 and 2023. Her work bridges theoretical advancements with practical applications, emphasizing sustainability and engineering innovation.

Seffetullah Kuldasمشاهده پروفایل

پژوهشگر

• Parental Mediation
• Educational Resilience
• Self-Construal
• +۳ مورد دیگر

Seffetullah Kuldas is currently a Postdoctoral Fellow at the University of Oslo's Department of Media and Communication, funded by a Marie Skłodowska-Curie Actions – Individual Fellowship (MSCA–IF). His research focuses on ethnicity-based parenting for children’s online safety, educational resilience against bullying and socioeconomic challenges, and unconscious cognitive processes. He previously held a postdoctoral position at Dublin City University’s Anti-Bullying Centre, studying Roma children’s experiences with ethnicity-based bullying. His work integrates empirical research with policy recommendations, often using EU Kids Online datasets and peer-reviewed publications. Key research interests include parental mediation strategies, transactional resiliency frameworks, and the intersection of unconscious mind theories with educational practices. He has contributed to developing validated scales for anti-bullying self-efficacy and has explored digital divides in online safety awareness. Teaching roles: Guest Lecturer at Dublin City University and the University of Science Malaysia, covering topics like ethnicity-based bullying, metacognition, and research methodologies. Awards: MSCA–IF Fellowship, Best Research Award, and multiple Best Publication accolades. Publications span 20+ peer-reviewed articles in journals like International Journal of Communication and Youth & Society , focusing on bullying prevention, digital parenting, and cognitive resilience. His projects emphasize marginalized communities, including Roma children and ethnic minorities in Europe, addressing both academic and societal impacts through collaborative research and policy engagement.

Sophie Vigneronمشاهده پروفایل

استاد

• Cultural Heritage Law
• Art Law
• International Law
• +۳ مورد دیگر

Dr. Sophie Vigneron is a Reader in Law and Director of Graduate Studies at the University of Kent's Kent Law School. Her research focuses on art and cultural heritage law, including the regulation and protection of heritage (tangible/intangible, movable/immovable) under national and international frameworks. She holds a joint PhD from the Universities of Nancy and Kent, awarded the prize for best private law thesis in 2005. Her roles include Editor-in-Chief of the International Journal of Cultural Property since 2023, and leadership in projects like the AHRC network on Cultural World Heritage Sites. She has served on review panels for the EU, ESRC, and AHRC. Research Interests: Regulation of art trade, heritage law intersections with human rights, protection during conflicts, restitution of cultural objects (e.g., WWII looting), and UNESCO conventions implementation. Publications span cultural heritage governance, Brexit impacts on heritage, repatriation of human remains, and authenticity in art law. She regularly contributes to legal encyclopedias and journals, with over 50 publications indexed in the Kent Academic Repository. Professional Memberships: Board Member of ISCHAL, co-convenor of the Socio-Legal Studies Association's Art & Heritage stream.

• Urban Computing
• Spatiotemporal Data Management
• Artificial Intelligence
• +۳ مورد دیگر

Associate Professor Ke Deng is affiliated with the School of Computing Technologies at RMIT University. His research focuses on urban computing, spatiotemporal data analysis, and social networks, with expertise in data mining and artificial intelligence. He holds a PhD in Computer Science from The University of Queensland (2007), a Master's in Information and Communication Technology (2001), and a Bachelor's in Electrical Engineering (1994). Previously, he was a postdoctoral researcher at CSIRO ICT Centre and a researcher at Huawei Noah's Ark Lab. His work emphasizes practical applications of AI, such as fairness-aware recommendation systems, traffic scenario modeling, and energy-efficient protocols for IoT. Dr. Deng's career includes roles as an acting lecturer at The University of Queensland and co-supervisor of a PhD student. He has supervised numerous research projects, including advancements in quantum annealing for recommenders, fake news mitigation via reinforcement learning, and smart human sensing using millimeter-wave radar. His research outputs span journals like ACM Transactions on Information Systems and IEEE Transactions on Knowledge and Data Engineering. Education: PhD in Computer Science, The University of Queensland (2007) MSc in Information and Communication Technology (2001) BEng in Electrical Engineering (1994) Key Research Themes: Urban computing and smart cities Mechanisms for fair AI systems Energy-efficient IoT protocols Spatiotemporal data mining Grants and Collaborations: ARC Australian Postdoctoral Fellowship (2010–2012) Research at Huawei Noah's Ark Lab (2013) His recent projects highlight interdisciplinary innovation, such as quantum computing for feature selection and self-supervised networks for traffic scenario clustering. Dr. Deng is actively involved in mentoring PhD/Masters students and contributes to RMIT’s research initiatives in AI and urban informatics.