جستجوی استاد راهنمای دانشگاهی

Akshi Kumarمشاهده پروفایل

مدرس ارشد

• Artificial Intelligence
• Natural Language Processing
• Explainable AI
• +۸ مورد دیگر

Dr. Akshi Kumar is a Senior Lecturer (Associate Professor) in Computing at Goldsmiths, University of London, serving as Director of Postgraduate Research and Chair of Research Ethics in Computing. Her expertise spans AI, NLP, and their applications in healthcare, finance, and education. With over 15 years of academic experience, she has authored influential books like Language Intelligence: Expanding Frontiers in NLP (IEEE-Wiley, 2025) and contributed to UK parliamentary inquiries on AI ethics and mental healthcare. Education: PhD (Web Mining), University of Delhi, India (2011) MTech (CSE), GGSIPU, Delhi (2005) BE (CSE), MDU, Rohtak (2003) Research Interests: Her work focuses on AI-driven decision-making in high-stakes domains, explainable AI, and cybersecurity. Notable areas include NLP for healthcare diagnostics, fraud detection, and ethical AI policy. Professional Activities: Steering Group Member, Mayor of London’s Violence Reduction Unit (VRU) on Online Harms Contributor to UK Parliament POSTnotes on AI in mental healthcare and media literacy Consultant for NLP-powered job matching systems and educational feedback tools Awards: Top 2% Highly Cited Scientist, 2021–2024 13 Research Excellence Awards Royal Academy of Engineering Exceptional Talent Recognition (2022) Labs & Projects: Leads initiatives like ExplainED (NLP for education feedback) and collaborates on AI ethics frameworks for digital safety. Her work integrates computational linguistics with societal impact, addressing challenges in misinformation, healthcare, and policy.

Agnese Pintoمشاهده پروفایل

استادیار

• Artificial Intelligence
• Internet of Things
• Semantic Web
• +۲ مورد دیگر

Agnese Pinto is an Assistant Professor at Polytechnic of Bari, teaching courses including Operating Systems and Operating Systems for Management Engineering. Her research focuses on Artificial Intelligence, Internet of Things, Semantic Web, and Cloud-Edge Computing, with applications in logistics, sensor networks, and smart city technologies. She is affiliated with SisinfLab, contributing to projects in cloud-edge intelligence and IoT systems. Her publications demonstrate a strong emphasis on integrating semantic technologies with distributed systems, particularly in IoT and edge computing environments. Recent work explores AI-driven logistics optimization, serverless architectures for sensor networks, and knowledge representation for autonomous systems. The consistent themes include semantic reasoning, distributed intelligence, and real-time system efficiency across transportation, UAV operations, and urban computing domains. She maintains active participation in academic events such as the International Conference on Web Engineering (ICWE) and Cyber Security Challenge initiatives.

Malik Hafiz Abid Mahmoodمشاهده پروفایل

استاد آموزشی

• Complex Networks
• Network Sciences
• Network Modeling of Diseases
• +۴ مورد دیگر

Dr. Malik Hafiz Abid Mahmood is an Assistant Teaching Professor at the Knight Foundation School of Computing and Information Sciences, Florida International University (FIU). He holds a Ph.D. in Computer Science from Universiti Islam Antarabangsa Malaysia (IIUM) and has over 12 years of teaching experience across international institutions. His roles include serving as Editor-in-Chief of academic journals and editorial board member of several others. He is a Senior Fellow of the Higher Education Academy (SFHEA), UK, and a member of IEEE, where he has held leadership positions in the IEEE Bahrain chapter. Education Background : Ph.D., Computer Science, Universiti Islam Antarabangsa Malaysia (2016) M.S., Information Technology, Preston University, Pakistan (2009) MBA in Human Resource Management, Preston University, Pakistan (2007) Research Interests : Dr. Mahmood focuses on complex network analysis, including dengue epidemic modeling, social media system dynamics, and data science applications. His work bridges computer science with healthcare, economics, and environmental sustainability. Notable contributions include AI-driven solutions for poverty reduction, renewable energy policy analysis, and cybersecurity in IoT systems. Publications & Awards : With 35+ publications and 590+ citations (Google Scholar, h-index 15), he has received gold and silver medals in research poster competitions and best paper awards. His research spans interdisciplinary domains such as smart agriculture, disease network modeling, and e-learning ethics. Service & Outreach : He has chaired international conferences, volunteered as a reviewer, and served as an external examiner for universities. His outreach includes contributions to IEEE initiatives and advocacy for student activities in technical education.

Vladimir Boginskiمشاهده پروفایل

استاد

• Network Science
• Optimization
• Data Mining
• +۵ مورد دیگر

Vladimir Boginski is a Professor in the Department of Industrial Engineering and Management Systems at the University of Central Florida (UCF), affiliated with the College of Engineering and Computer Science. He holds a Ph.D. in Industrial and Systems Engineering from the University of Florida (2005), alongside earlier degrees from Moscow Institute of Physics and Technology (B.S., 2000). His research focuses on network science, optimization, and data mining, with applications in social networks, financial systems, and complex infrastructure. Education: Ph.D. (UF, 2005), M.S. (UF, 2003), B.S. (Moscow Institute, 2000) Boginski's work emphasizes mathematical modeling of network structures, including robust optimization for interdependent systems, influence maximization in social media, and spectral graph theory applications. His recent studies explore small-world networks, financial market dynamics, and materials science through network-based approaches. Publications span over two decades, with recent trends in reinforcement learning for dynamic user behavior analysis, resilience optimization in critical infrastructure, and cryptocurrency price dynamics modeling. He has contributed to foundational research on quasi-clique detection, risk-constrained routing, and robust network cluster identification.

Qipeng Phil Zhengمشاهده پروفایل

استاد

• Operations Research
• Network Optimization
• Stochastic Optimization
• +۶ مورد دیگر

Qipeng Phil Zheng is a Professor at the University of Central Florida specializing in Operations Research, Stochastic Optimization, and Energy Systems optimization. His research bridges Network Optimization, Integer Programming, and Supply Chain Management with practical applications in Transportation Planning, Logistics, and Dynamic Traffic Assignment. Ph.D. Industrial & Systems Engineering, University of Florida (2010) M.S. Automation, Tsinghua University (2005) B.S. Industrial Automation, North China University of Technology (2001) His recent research focuses on stochastic energy systems modeling, social network influence dynamics, and multi-agent sustainability frameworks. Key methodologies include decomposition algorithms, machine learning integration, and risk-constrained optimization. Publications from 2020-2025 demonstrate consistent contributions to power grid resilience, blockchain-enabled energy trading, and social media cascading behavior analysis. Active in interdisciplinary applications, Zheng’s work spans from technical energy optimization to social network modeling, emphasizing practical implementation and algorithm development. His 2025 article introduces bounded rationality frameworks for demand response systems, while 2024 research addresses risk-aware energy maintenance scheduling.

Murat Yukselمشاهده پروفایل

استاد

• Wireless Communication
• Optics and Photonics
• Signal Processing
• +۳ مورد دیگر

Murat Yuksel is a Professor in the Department of Electrical and Computer Engineering at CREOL, The College of Optics and Photonics , University of Central Florida. His research focuses on advanced wireless communication systems, including millimeter-wave (mm-Wave) technologies, free-space optical (FSO) communication, and machine learning applications in signal processing and network protocols. He leads projects involving software-defined radio (SDR) testbeds, resilient emergency communication networks, and automated peering strategies for internet service providers (ISPs). His work bridges theoretical research with practical implementations, such as developing steerable antenna arrays for mm-Wave systems and optimizing FSO transceivers for aerial platforms. Yuksel also explores socio-technical aspects of communication networks, including disaster response communication on social media and economic models for ISP peering agreements. His contributions span interdisciplinary areas like visible light communication (VLC) networks, UAV-assisted optical links, and blockchain-based routing security. Key research themes include: Directional antenna design and beamforming Machine learning for radio propagation modeling Resilient disaster communication systems ISP peering automation and network economics Multi-element FSO and VLC testbed development Yuksel has contributed to over 50 peer-reviewed articles and actively collaborates with industry and government entities on projects like the CNS Core: Small: Directional Software-Defined Radio initiative.

Aparna Guptaمشاهده پروفایل

استاد

• Quantitative Finance
• Risk Management
• Financial Decision Support
• +۵ مورد دیگر

Aparna Gupta is a Professor of Quantitative Finance at the Lally School of Management, Rensselaer Polytechnic Institute (RPI). She previously co-founded and co-directed the NSF IUCRC Center for Research toward Advancing Financial Technologies (CRAFT) and served as Associate Dean for Academic Affairs at Lally School. Her research focuses on financial decision support systems, risk management, and applying machine learning/mathematical modeling to financial engineering and renewable energy sectors. She has held a visiting researcher position at the U.S. Securities and Exchange Commission (SEC) and contributed to over 80 indexed publications across Computer Science, Decision Sciences, and Mathematics. Education: PhD (2000) and MS (1997) in Operations Research from Stanford University; B.Sc. and M.Sc. in Mathematics from Indian Institute of Technology (IIT) Kanpur. Research interests include blockchain technology applications, climate change impact analysis, renewable energy risk mitigation, and financial regulatory frameworks. Notable work includes developing frameworks for assessing risk culture in banks/insurance firms and creating algorithms for predicting financial performance from SEC filings. Her book Risk Management and Simulation remains a key reference in the field. Awards include the 2018 Financial Management Association Best Paper Award and 2019 FRAP Conference Best Paper Award. She serves on the editorial boards of quantitative finance journals and the GARP FRM Advisory Board. Her interdisciplinary projects involve collaborations with federal agencies (SEC), industry partners, and international academic networks. Current focus areas include AI-driven fraud detection, cross-border payment innovations, and systemic risk management in interconnected financial systems.

Lei Yuمشاهده پروفایل

استادیار

• Data Privacy
• AI Security
• Machine Learning Systems
• +۳ مورد دیگر

Lei Yu is a Tenure-Track Assistant Professor in the Department of Computer Science at Rensselaer Polytechnic Institute (RPI). Previously, he was a Research Staff Member at IBM Research's Thomas J. Watson Research Center. He holds a Ph.D. in Computer Science from Georgia Institute of Technology and earlier studied at Harbin Institute of Technology. His research focuses on data privacy, AI security, machine learning systems, and cloud/mobile computing, with notable contributions to federated learning, adversarial attacks, and blockchain security. Yu has been awarded multiple IBM accolades, including the 2022 IBM Research Outstanding Accomplishment and the IBM Outstanding Innovation Award. He has authored numerous patents and serves on technical program committees for top conferences like ACM ASIACCS and IEEE ICDCS. Education: Ph.D. in Computer Science (Georgia Tech), M.S. and B.S. from Harbin Institute of Technology (China). His work spans theoretical and applied research, including privacy-preserving techniques, secure AI systems, and distributed computing. He leads the RPI lab focused on trustworthy AI and has advised over 15 students across Ph.D., Master’s, and undergraduate programs. Research interests emphasize threats in data lifecycle, machine learning robustness, and system security. His lab’s projects include membership inference attacks, model deduplication, and blockchain-based solutions for data integrity. He has secured grants such as the RPI-IBM AIRC research award and maintains active collaborations with industry and academia. Awards: IBM Research Awards (2020–2022), NSF Travel Grants, Best Paper Awards. Professional Activities: Guest Editor for Wireless Communications and Mobile Computing , TPC roles in ICDCS, AsiaCCS, and ICDE. Teaching: Courses on database systems, network programming, and machine learning security at RPI.

• Financial Mathematics
• Stochastic Processes
• Cryptocurrencies
• +۳ مورد دیگر

Sveinn Olafsson is an Assistant Professor at the School of Business of Stevens Institute of Technology . His academic focus lies in financial mathematics, stochastic processes, and blockchain technologies. PhD in Statistics from Purdue University (2015) MS in Financial Mathematics from Stanford University (2011) His research explores mathematical modeling in finance, including Cournot games, blockchain governance, and Lévy processes for volatility analysis. Recent publications address decentralization in cryptocurrencies, robo-advising, and supply chain sustainability. He is a member of the Bachelier Finance Society (BFS) and Institute for Operations Research and Management Sciences (INFORMS). No explicit awards or student advising details are provided in the available data.

Karuna Pande Joshiمشاهده پروفایل

استاد

• AI/Data Science
• Legal Text Analytics
• Cloud Computing
• +۵ مورد دیگر

Karuna Pande Joshi is a Professor of Information Systems at the University of Maryland, Baltimore County (UMBC), and the Director of the Center for Accelerated Real-time Analytics (CARTA). She also leads the Knowledge, Analytics, Cognitive and Cloud Lab. Her research focuses on AI/Data Science, Legal Text Analytics, Cloud Computing, and Healthcare IT, with notable work on oblivious cloud systems and automating legal documents. Dr. Joshi holds a PhD and MS from UMBC, supported by IBM PhD Fellowships, and a BEng from the University of Mumbai. Her industry experience includes over 15 years as an IT manager at organizations like the International Monetary Fund, managing projects in databases, web content management, and network applications. She has secured grants from NSF, ONR, DoD, Cisco, and GE Research, including an NSF I-Corps award and TEDCO MII grant for commercializing research through a startup. Research interests span cloud usability standards (collaborating with NIST), medical device regulatory compliance, and cybersecurity frameworks. Notable projects include the ALDA cognitive assistant for legal documents and frameworks for secure cloud EHR systems using attribute-based encryption. She advises over 14 graduate students and leads interdisciplinary teams addressing challenges in healthcare IT, cybersecurity, and cloud services. Awards include IBM PhD Fellowship (twice), TEDCO MII grant, and NSF I-Corps award. Her work emphasizes practical solutions for transitioning organizations to cloud systems while addressing compliance, privacy, and security challenges.

• Cyber Security
• Blockchain Technology
• Distributed Systems Security
• +۷ مورد دیگر

Dr. Muntadher Sallal is a Senior Lecturer in Cyber Security at Bournemouth University, affiliated with the Bournemouth University Cyber Security Research group (BUCSR). His expertise spans security, privacy, and trust in distributed systems including blockchain, IoT, e-voting, and darknet analysis. Previously, he held roles as a Lecturer at Nottingham Trent University, Research Fellow at Surrey Centre for Cyber Security, and part-time Lecturer at the University of Portsmouth's School of Computing. Dr. Sallal holds a PhD in Computer Science from the University of Portsmouth (2018), focusing on Bitcoin network security and blockchain consistency. His research integrates machine learning with blockchain technologies to enhance smart city security and e-voting systems. Key areas include privacy-preserving e-voting protocols, cryptocurrency security implications, and distributed ledger topology optimization. He leads the S4AllCities (Smart Spaces Safety and Security for All Cities) grant (2023), funded by the European Commission's Horizon 2020. His work emphasizes practical applications of AI and blockchain in cyber defense, urban security, and voting infrastructure. Collaborations include projects on 6G network security, autonomous robotics risk frameworks, and crowd behavior analysis using digital twins. Over 20 peer-reviewed publications demonstrate his contributions to blockchain performance evaluation, cryptocurrency crime analysis, and AI-driven cyber threat detection. His research bridges theoretical advancements with real-world implementations in critical infrastructure systems.

Olugbenga Oluwagbemiمشاهده پروفایل

مدرس ارشد

• Climate Change Modelling
• Computational Modelling in Health
• Artificial Intelligence in Health
• +۷ مورد دیگر

Dr. Olugbenga Oluwagbemi is a Senior Lecturer in Computing Science at Middlesex University, UK, with a C2 NRF rating in South Africa. He holds a PhD in Computer Science from Covenant University (defended at Johns Hopkins University as a Fulbright Scholar) and advanced certificates from the Rochester Institute of Technology, USA, and Stellenbosch University, South Africa. His roles include teaching courses like Legal/Security Aspects of Data Science, Individual Data Science Projects, Blockchain Development, and supervising postdoctoral, PhD, MSc, and BSc students. He has over 17 years of teaching experience across Nigeria, South Africa, and the UK. Education: PhD (Covenant University/Johns Hopkins University), MSc (University of Ibadan), BSc (University of Ilorin), Advanced Certificate (Rochester Institute of Technology). Research Focus: Climate change modeling, AI in health, computational genomics, malaria control, and health informatics software development. His research spans computational models for disease control, including HIV diagnostics, malaria eradication, and mRNA vaccine design. He has secured grants from DAAD, NRF, Oppenheimer Memorial Trust, and UK African Research Excellence Fellowship (AREF). Notable awards include the C2 NRF rating, DAAD Climate Research Grant, and Fulbright Fellowship awards. Recent articles highlight AI-driven health solutions (e.g., facial emotion recognition, Monkeypox forecasting) and climate resilience strategies. He actively collaborates with institutions globally, including Oxford, Stellenbosch, and TUM. His work emphasizes practical software tools for healthcare and environmental challenges in Africa.

• Artificial Intelligence
• Machine Learning
• Educational Technology
• +۳ مورد دیگر

Dr. Giacomo Nalli is a Lecturer in the Department of Computer Science at Middlesex University. His research focuses on integrating Artificial Intelligence (AI) and Machine Learning (ML) into educational systems, with a particular emphasis on IoT applications, cybersecurity in educational platforms, and data-driven student performance analysis. He leads modules in computer science and contributes to innovative projects in hybrid learning environments, blockchain-based credential systems, and emotion detection through IoT devices. His work addresses both the technical and pedagogical challenges of modern education systems. Research interests include AI in education, IoT security, e-learning systems, and the ethical implications of technological integration in schools and universities. Notable contributions explore predictive models for student retention, AI-driven peer assessment tools, and blockchain solutions for digital credentials. Dr. Nalli’s publications span topics such as signature-based IoT threat detection, clustering algorithms for biometric data in VR experiences, and the use of chatbots in Moodle platforms. His work often bridges theoretical computer science with practical educational applications, aiming to enhance learning outcomes through technology. Contact details: Office T120 Town Hall Building, Hendon Campus; Email: g.nalli@mdx.ac.uk .

Omair Shafiqمشاهده پروفایل

دانشیار

• Natural Language Processing
• Machine Learning
• Deep Learning
• +۴ مورد دیگر

Omair Shafiq is an Associate Professor at the School of Computer Science, Carleton University. His research focuses on advanced topics in natural language processing (NLP), machine learning, and their applications in knowledge graphs, blockchain, and network security. He leads projects that integrate large language models (LLMs) with structured data to enhance information retrieval and decision-making systems. His work spans areas like explainable AI, adversarial robustness, and real-time traffic prediction. Shafiq is affiliated with Herzberg Laboratories and contributes to interdisciplinary research, including smart contracts, encrypted traffic classification, and IoT security. Education details are not explicitly listed in the provided text. His research interests emphasize practical solutions for challenges in AI ethics, data privacy (e.g., GDPR compliance), and scalable analytics for big data applications. He has developed frameworks like ECSGen/iZen for NLP tasks and CARD-B for encrypted traffic classification. His recent publications (2022–2025) highlight innovations in ensemble learning, adversarial attacks defense, and blockchain-based solutions for secure transactions. Shafiq’s work often bridges theory and practice, addressing real-world problems such as cybersecurity in vehicular networks, stock market prediction using deep learning, and user behavior analysis on social platforms. His contributions include tools like RevDet for event detection in news feeds and HybLoc for indoor localization. Though no specific awards are mentioned, his prolific publication record reflects sustained academic impact.

• Business Analytics
• Space Industry
• Cybersecurity
• +۵ مورد دیگر

Professor Stefania Paladini holds the position of Professor of Business Analytics at Queen Margaret University's Business School. A professional statistician and former Italian government trade commissioner, her work bridges academia and policy, focusing on space sustainability, cybersecurity, fintech, and blockchain applications. Her research explores geopolitical implications of space exploration, orbital debris management, and sustainable practices across industries. Her research interests span the space industry, cybersecurity, and blockchain for social innovation. Notable works include The New Frontiers of Space (2019), analyzing economic and security dimensions of space exploration. Recent publications address issues such as NHS healthcare waste reduction, social bot detection frameworks, and Alzheimer’s-periodontal disease correlations. Publications from 2023–2025 highlight trends in space governance, cybersecurity threats, and sustainable supply chain redesign. Her work emphasizes interdisciplinary approaches, blending economics, policy, and technology to address global challenges. No specific awards or grants are listed, though her contributions to space policy and data analytics are internationally recognized.