جست‌وجوی استاد و پژوهشگر

• Hydrology
• Remote Sensing
• Artificial Intelligence
• +۳ مورد دیگر

Mathew Herrnegger is a Senior Scientist at the Institute of Hydrology and Water Resources Management (HyWa) at the University of Natural Resources and Life Sciences, Vienna (BOKU). He completed his doctorate in hydrology after studying Environmental Engineering and Water Resources Management. His research focuses on hydrological modeling, integration of remote sensing data, artificial intelligence, and machine learning in water management applications, climate change impacts on water resources, and big data analytics. Primary research areas: Hydrology, Water Resources Management, Climate Change, Artificial Intelligence, Remote Sensing, Machine Learning Dr. Herrnegger leads research groups since 2013 and has published extensively on hydrology and water management, particularly in alpine and East African contexts. His work includes flood risk assessment, groundwater recharge modeling, and soil erosion studies using advanced statistical and machine learning techniques. He actively participates in international conferences and collaborates with institutions in Kenya, Uganda, and Austria. His recent article analyses span from 2023 to 2025, covering glacier melt contributions to runoff under climate change, water quality degradation mapping, and extreme flood estimation using synthetic weather data. Key subtopics include snow-hydrology coupling, transboundary river basin management, and AI applications in stream temperature prediction. Dr. Herrnegger contributes to university teaching and supervises student theses while engaging in knowledge transfer through GIS training workshops in Uganda and Kenya. He maintains active roles in international hydrological conferences and local Austrian climate change initiatives.

• Internet of Things
• Cybersecurity
• Smart Cities
• +۴ مورد دیگر

Dr. Oluwaseun Bamgboye is a Lecturer at Edinburgh Napier University's School of Computing Engineering and the Built Environment. His research focuses on Internet of Things (IoT) , Cybersecurity , and Semantic Technologies , with applications in Smart Cities, Data Quality, and Sensor Networks. He actively publishes in IoT data validation , XAI for cyberattack detection , and real-time analytics . Academic Affiliation: School of Computing Engineering and the Built Environment, Edinburgh Napier University Research Interests: Dr. Bamgboye's work bridges semantic modeling and machine learning to address data consistency in Smart Spaces, enhance cybersecurity through explainable AI (XAI) , and develop IoT-driven decision-making systems . His projects often integrate RDF stream processing and rule-based reasoning for real-time data quality assurance. Publication Trends: His recent articles (2023-2025) emphasize IoT network security , XAI frameworks , and smart city infrastructure . Earlier works (2015-2019) focus on distributed systems fault tolerance , sensor data uncertainty , and web accessibility tools . Key methodologies include neurosymbolic learning , ensemble models , and semantic stream management . Supervision: Dr. Bamgboye supervises PhD projects such as: Enhanced deep learning and semantic-based predictive analytics for reactive IoT streaming data (Talatu Adamu, 2024–present) AI-driven and IoT-assisted explainable smart banking (Fatima Mumtaz, 2024–present) Semantic models for sensor data uncertainty in smart systems (Tawanda Nyakudya, 2022–present) Web accessibility auditing (Collins Ovie, 2023–present)

Flora Salimمشاهده پروفایل

استاد

• Ubiquitous computing
• Machine learning
• Data science
• +۶ مورد دیگر

Professor Flora Salim is a leading academic at the University of New South Wales (UNSW) Sydney, holding a full Professorship in the School of Computer Science and Engineering. She serves as Deputy Director (Engagement) of the UNSW AI Institute and contributes to multidisciplinary research at the intersection of ubiquitous computing, machine learning, and data science. Human-centred AI and ethical systems Spatio-temporal data modeling Applications for climate resilience and urban mobility Her research focuses on multimodal foundation models, continual learning, and responsible AI deployment in real-world environments. She explores: Time-series and sensor data analysis Wearable and environmental sensing AI for sustainable infrastructure Robustness and trustworthiness in models Recent publications highlight her work on: Transformer-based climate downscaling Cross-modal fairness in mobility Privacy-preserving spatio-temporal generation Patient similarity networks in healthcare She has received multiple competitive fellowships including: Humboldt Fellowship Bayer Fellowship Victoria Fellowship ARC Australian Postdoctoral Industry (APDI) Fellowship Additional accolades include: Women in AI Award Australia and New Zealand (2022) IBM Smarter Planet Industry Innovation Award As Chief Investigator in: ARC Centre of Excellence for Automated Decision Making and Society (ADM+S) ARC Training Centre for Whole Life Design for Carbon Neutral Infrastructure She maintains active collaborations through: Associate position at ELLIS Alicante Visiting Professor roles at University of Kassel (2019-2020) and University of Cambridge (2019) Editorial board memberships in ACM TIST, IEEE Pervasive Computing, and Nature Scientific Data

• Machine Learning
• Artificial Intelligence
• Cyber-Physical Systems
• +۳ مورد دیگر

Ning Xiong is a Professor at Mälardalen University, affiliated with the School of Innovation, Design and Engineering and the Division of Intelligent Future Technologies. His research focuses on advanced artificial intelligence, machine learning, optimization algorithms, and cyber-physical systems. He explores applications ranging from digital twin frameworks in distributed systems to predictive maintenance using explainable AI and anomaly detection in timeseries data. His work integrates techniques like federated learning, Bayesian classifiers, and bio-inspired computing (e.g., membrane clustering) to address challenges in smart systems and data science. Key research areas include: Machine Learning & Deep Learning Cyber-Physical Systems Optimization Algorithms Smart Systems & IoT Data Science & Big Data Recent publications highlight advancements in digital twin frameworks for resilient distributed systems, ensemble learning for imbalanced data, and lightweight object detection methods for UAV imagery. His contributions emphasize practical applications in energy grids, predictive maintenance, and industrial automation while addressing theoretical challenges in model explainability and scalability. His research is characterized by interdisciplinary collaboration, combining software engineering, systems architecture, and domain-specific expertise to develop innovative solutions for dynamic environments.

Anastasia Benekaمشاهده پروفایل

استاد

• Physical Rehabilitation
• Therapeutic Exercise
• Sports Injury Rehabilitation
• +۶ مورد دیگر

Anastasia Beneka is a Professor at the Department of Physical Education & Sport Sciences, Democritus University of Thrace (Greece), affiliated with the Laboratory of Therapeutic Exercise and Rehabilitation. She holds academic roles including teaching undergraduate and graduate courses on musculoskeletal injuries, rehabilitation counseling, and anatomy. Her research focuses on therapeutic exercise for chronic musculoskeletal pain, sports injury rehabilitation, and ergonomic interventions for occupational health. She has supervised over 30 master’s and doctoral theses and contributed to peer-reviewed journals such as the Journal of Sport Rehabilitation and Scandinavian Journal of Medicine & Science in Sports. Educations: PhD in Sports Sciences (1998), MSc in Coaching (1996), BSc in Physical Education (1994), all from Democritus University of Thrace. Professional Experience: Researcher (2005–present), Academic Advisor (2008–2010), Special Advisor to the Greek Ministry of Education (2007–2009). Research Interests: She investigates musculoskeletal injury prevention, therapeutic exercise programs for chronic pain, and the biomechanical assessment of athletic performance. Notable contributions include studies on proprioceptive training in soccer players, core stability for low back pain, and ergonomic interventions for office workers. Publications: Over 50 peer-reviewed articles (605 citations, H-index 15), with recent work on AI-driven injury rehabilitation systems and workplace exercise programs. Key themes include musculoskeletal rehabilitation, sports biomechanics, and clinical exercise physiology. Awards: Marshall Memorial Fellowship (2006), Chairman’s Award for Medical Science Excellence (1997). Grants/Projects: Coordinator of the Erasmus+ project “Therapeutic Exercise at Workspace” (2014–present), contributor to EU-funded research on sport tourism and rehabilitation protocols. Labs/Teams: Active in the “Therapeutic Exercise and Rehabilitation Lab” and collaborates with international institutions on EU-funded projects.

• Digital Disruption in Media Industries
• Cultural and Creative Industries
• Screen and Media Culture
• +۳ مورد دیگر

Professor Mark Evans is the Interim Dean of the Faculty of Design, Architecture and Building at the University of Technology Sydney (UTS). Previously, he held roles as Pro Vice-Chancellor (Enterprise Learning) and Head of the School of Communication at UTS. His academic career spans over 12 years in senior administrative positions, emphasizing institutional transformation, international partnerships, and interdisciplinary learning solutions. Research Interests: Evans is a leading scholar in digital disruption within media industries, focusing on music and journalism. His work examines the internationalization of higher education curricula in transnational ventures. He has authored/edited seven books, including studies on digital music industries and religious influences in popular culture. His research often bridges cultural studies, media ethics, and creative industry dynamics. Professional Contributions: He has held Visiting Professorships at NYU, University of Amsterdam, and Turku University. His funded research includes an ARC grant on 'Duty of Care in the Contemporary Music Industries'. He edits academic journals like Perfect Beat and oversees series such as Genre, Music and Sound . Academic Leadership: Evans collaborates with industry partners to design custom learning programs and has developed cross-disciplinary curricula. His leadership focuses on enhancing teaching quality, research impact, and institutional revenue strategies.

Damu Dingمشاهده پروفایل

پژوهشگر

• Network Security
• DDoS Detection
• Programmable Network Devices
• +۵ مورد دیگر

Dr. Damu Ding is a researcher specializing in network security and programmable data planes, currently affiliated with the Department of Computer Science and Engineering at the University of Bologna. With a PhD completed in 2021 from the same institution, Dr. Ding has established a robust research profile focused on leveraging programmable network devices for security applications and network monitoring. Dr. Ding's research interests center around network security mechanisms, particularly DDoS detection systems implemented directly within programmable switches using the P4 language. Their work bridges theoretical network security concepts with practical implementations in modern data plane programmable networks. Key areas of investigation include network traffic entropy analysis, flow cardinality estimation, volumetric attack detection, and in-network machine learning applications. Analysis of Dr. Ding's publication record from 2019-2024 reveals a consistent research trajectory focused on pushing security functionality into the network data plane. The publications demonstrate increasing sophistication in leveraging programmable switches for security applications, moving from basic heavy-hitter detection to complex DDoS mitigation systems and in-network machine learning. This research sits at the intersection of networking, security, and systems, with strong practical implications for modern network infrastructure. Dr. Ding has established productive collaborations with researchers including Marco Savi, Domenico Siracusa, and Noa Zilberman, resulting in numerous publications in top networking venues including IEEE Transactions on Network and Service Management, IEEE Transactions on Dependable and Secure Computing, and INFOCOM. Their work has been published in both journal and conference formats, demonstrating impact across the networking research community. As a researcher who completed their PhD relatively recently (2021), Dr. Ding represents an emerging voice in the network security and programmable networking space, with a growing body of work that addresses critical challenges in modern network security architectures.

• Big data analytics
• Scalable intelligent information systems
• Cloud data analytics
• +۶ مورد دیگر

Yanlei Diao is a Professor of Computer Science at Ecole Polytechnique in France and also holds a professorship at the University of Massachusetts Amherst. She joined Ecole Polytechnique in September 2015 and leads the CEDAR research team focusing on Rich Data Exploration at Cloud Scale. Her work bridges theoretical computer science with practical big data systems that address real-world challenges in data analytics. Professor Diao's research spans big data analytics, scalable intelligent information systems, and cloud data processing infrastructure. Her work emphasizes practical solutions for explainable anomaly detection, interactive data exploration, and uncertain data management. She has pioneered systems like UDAO (a next-generation optimizer for cloud analytics), EXAD (explainable anomaly detection), AIDEme (interactive data exploration), and GESALL (genomic scalable analysis) that have influenced both academia and industry. Her recent publications reveal a strong focus on making big data analytics more explainable, efficient, and accessible. She has developed frameworks for unsupervised anomaly detection across heterogeneous domains, created benchmarks like Exathlon for evaluating explainable anomaly detection systems, and advanced human-in-the-loop approaches for interactive database exploration. Her work consistently bridges theoretical foundations with practical implementations in distributed systems. Selected Awards: ERC Consolidator Award (2017-2023) for "Charting a New Horizon of Big and Fast Data Analysis through Integrated Algorithm Design" CRA-W Borg Early Career Award (2013) NSF CAREER Award (2008) IBM Innovation Award on Scalable Data Analytics (2010) Professor Diao actively mentors PhD and Master's students, with former students now holding positions at top technology companies including Google, Facebook, Amazon, Netflix, and Huawei. Her research is supported by diverse funding sources including the European Research Council, National Science Foundation, ANR, and industry partners like Google, IBM, and Alibaba. She serves as PC Co-Chair of PVLDB 2025-2026 and has delivered keynotes at major industry events including Amazon Machine Learning Workshop (2024), SWIFT AI Forum (2023), and Berlin Institute for the Foundations of Learning and Data (2022). Her CEDAR research team at Inria/LIX develops cutting-edge technologies for big data analytics, with current projects focusing on foundation models for big data, explainable AI for anomaly detection, and genomic data analysis at scale. The team maintains strong collaborations with industry partners including Alibaba Cloud, where joint work has led to significant publications at top database conferences.

Ke Yiمشاهده پروفایل

استاد

• Database theory and systems
• Query processing
• Data security and privacy
• +۷ مورد دیگر

Ke Yi is a Professor in the Department of Computer Science and Engineering at the Hong Kong University of Science and Technology (HKUST), where he also serves as Director of the MSc Program in Big Data Technology. His research spans database theory and systems, query processing, data security and privacy, parallel and distributed algorithms, and computational geometry, with a focus on bridging theoretical guarantees with practical implementations. Dr. Yi earned his B.Eng. in Computer Science and Technology from Tsinghua University (1997-2001) and his Ph.D. in Computer Science from Duke University (2001-2006), advised by Professors Pankaj K. Agarwal and Lars Arge. Before joining HKUST in 2007, he was a Research Specialist at AT&T Labs-Research (2006-2007). His research interests center on database theory and systems with particular emphasis on query processing techniques, data security and privacy mechanisms, and efficient algorithms for big data. Yi's work consistently demonstrates the rich interdependence between theoretical foundations and practical implementations, favoring simple algorithms with elegant analyses that provide valuable insights for real-world applications. His research group has developed several notable system prototypes including Quorion (query optimization), DPSQL (differentially private SQL), SparkSQL+ (next-generation query planning), SecYan (secure query processing), CROWN/Cquirrel (continuous query processing), and XDB (online aggregation). Yi's publication record shows a clear evolution toward privacy-preserving database technologies, particularly differential privacy, with an increasing focus on practical implementations that maintain theoretical guarantees. His recent work has centered on query processing under differential privacy, secure multi-party computation for databases, and efficient algorithms for big data analytics, demonstrating consistent contributions to both theoretical foundations and practical systems. ACM SIGMOD Best Paper Award (2016, 2022) ACM PODS Test-of-Time Award (2022) ACM Distinguished Member (2021) Multiple ACM SIGMOD Best Paper Honorable Mentions Google Faculty Research Award (2010) HKUST School of Engineering Young Investigator Research Award (2012) Professor Yi has supervised numerous Ph.D. and MPhil students, many of whom have gone on to prestigious academic and industry positions at institutions including Nanyang Technological University, University of Waterloo, EPFL, Alibaba Cloud, and Google. His research has been generously supported by Hong Kong RGC, Alibaba, Huawei, ByteDance, Microsoft, and Google. In addition to his research leadership, Yi has made significant contributions to the academic community through editorial roles (ACM TODS, IEEE TKDE), program committee chairs (PODS 2026, ICDT 2021), and numerous service roles in top database conferences. His laboratory, the HKUST Database Lab (hkustDB), has become a leading center for database research in Asia, developing innovative prototypes that bridge theoretical database research with practical implementations. The lab maintains active GitHub repositories for their open-source projects and collaborates extensively with both academic and industry partners worldwide.

• Environmental Analytical Chemistry
• Per- and Polyfluoroalkyl Substances (PFAS)
• Groundwater Contamination
• +۳ مورد دیگر

Christian Zwiener is a Professor (W3) for Environmental Analytical Chemistry at the Center for Applied Geoscience, University of Tübingen since 2009. He holds a Habilitation and Venia Legendi in Water Chemistry (KIT, 2004) and a Ph.D. in Water Chemistry (Technical University of Munich, 1995). His research focuses on PFAS analysis , non-target screening , and environmental fate of contaminants using high-resolution mass spectrometry . Education: Habilitation in Water Chemistry, KIT (2004) Ph.D. in Water Chemistry, Technical University of Munich (1995) Diploma in Analytical and Environmental Chemistry, University of Ulm (1989) Research Trends: PFAS contamination in soils , human hair , and textiles Non-target screening workflows for novel contaminants and transformation products Environmental fate of pharmaceuticals and biocides Development of HRMS data mining tools (e.g., FindPFΔS, PFΔScreen) Scientific Awards: Level II Scientific and Technological Achievement Award (STAA) , EPA (2008) Research Award , Water Chemical Society, GDCh (2001) Professional Service: Chairman, Journal Vom Wasser (2016–present) Delegate, EUChemS Division of Chemistry & Environment (2020–present) Member of Water Research Perspectives Commission (2018–present) Advisory Board, VEGAS, University of Stuttgart (2014–present) His work bridges analytical chemistry , environmental toxicology , and public health , with key contributions to PFAS contamination and CKDu groundwater links . He has developed standardized methods for PFAS analysis and electrochemical oxidation protocols for contaminant degradation.

Ilkyeun Raمشاهده پروفایل

دانشیار

• Computer Networks
• Distributed Systems
• Cloud Computing
• +۵ مورد دیگر

Ilkyeun Ra serves as Associate Professor in the Department of Computer Science and Engineering at the University of Colorado Denver, where he has taught since 2001. His instructional responsibilities span undergraduate and graduate courses including Operating Systems, Computer Networks, and Cloud Computing. His educational background comprises: Ph.D. in Computer and Information Science, Syracuse University (2001) M.S. in Computer Science, University of Colorado Boulder B.S. and M.S. in Computer Science, Sogang University Dr. Ra's research concentrates on adaptive distributed systems and high-speed communication networks for high-performance computing. Current investigations focus on microservice autoscaling in cloud environments, multimedia streaming protocols over named data networks, and social media-driven disaster management systems. His methodology integrates reinforcement learning, blockchain, and real-time analytics to address scalability and reliability challenges in distributed architectures. Analysis of his 2018-2024 publications reveals dominant themes in cloud-native systems (46%), disaster informatics (23%), and network protocol innovation (31%). Key methodological trends include reinforcement learning applications for resource optimization (3 articles), blockchain implementations for privacy preservation (2 articles), and social media analytics for crisis response (3 articles). Scientific recognition includes: Outstanding paper award at IEEE The 26th International Conference on Advanced Communications Technologies (2024) Dr. Ra actively recruits Ph.D. students for distributed systems research. His funded projects include NIH support for the Hospital Computerized Disaster Information Management System (1G08LM009710-01, 2008-2011) and ETRI (South Korea) collaboration on parallel data processing frameworks. Current grants focus on cloud-based disaster management and edge network optimization. He directs the Distributed Computing and Networking Research Lab, which operates three specialized teams: the Cloud Microservices Group developing reinforcement learning autoscalers, the Multimedia Streaming Team designing NDN protocols, and the Disaster Informatics Unit analyzing social media for real-time crisis response.

• Information Systems
• Business Analytics
• IT Capability Continuity
• +۴ مورد دیگر

Dr. Jinho Kim is an Assistant Professor of Information Systems Management (MIS) at the University of Houston-Downtown (UHD). He previously taught business analytics at Lewis University (2020-2022) and brings 14 years of industry experience from Samsung, LG, Akamai Technologies, and Korea Telecom. Education Ph.D., Information Technology and Supply Chain Management — Old Dominion University MBA, Business Administration — University of Minnesota Research Interests Dr. Kim’s research is organized into three primary streams: IT Capability Continuity: Examining managerial and organizational factors that sustain firms’ IT capabilities and their long-term impact on business performance. Mobile ICT & National Productivity: Investigating how mobile information and communication technologies influence national productivity across developed and developing economies. Distributed Big-Data Analytics: Designing novel clustering algorithms tailored for globally distributed big-data environments. Publications & Trends His recent publications in Information & Management , Journal of Global Economy, Trade and International Business , and Journal of Management Analytics collectively explore strategic IT management, emerging network technologies (6G, IoT), and data-driven insights for global competitiveness. Scientific Awards & Honors No specific awards were mentioned in the provided text. Teaching & Service Dr. Kim regularly teaches undergraduate courses such as Management of Information Systems (MIS 3302) , Programming & Applications Development (MIS 3330) , Business Intelligence (MIS 4320) , and Cyber Networked Security . He emphasizes real-world applications drawn from his extensive industry background and fosters interactive, student-centered learning environments. He also contributes to departmental service, including formative assessment initiatives for core MIS courses.

Hannah M. Carrollمشاهده پروفایل

استادیار

• Ecology
• Environmental Science
• Paleoclimatology
• +۴ مورد دیگر

Hannah M. Carroll is an Assistant Professor of Environmental Science and Ecology at Western Colorado University, affiliated with the Natural & Environmental Sciences Department and the Clark Family School of Environment & Sustainability, where she teaches Environmental Biology, Science of Sustainability, Ecological Research Methods, and Scientific Computing. Her educational background includes: Ph.D. in Ecology & Evolutionary Biology and Environmental Science (co-majors), Iowa State University, 2020 B.S. in Environmental Science, University of Washington-Tacoma, 2008 Dr. Carroll's research integrates paleoclimatology, ecology, and biogeochemistry to investigate plant-climate interactions across geologic timescales. She specializes in clumped isotope paleothermometry, developing open-source software for reproducible statistical analysis while exploring applications in evolutionary biology and environmental reconstruction. Her educational philosophy emphasizes evidence-based methods to advance equity in STEM. Analysis of her recent publications reveals a dominant focus on methodological innovation in isotope geochemistry, particularly clumped isotope calibration and standardization, with expanding interdisciplinary applications spanning entomology, marine biomineralization, and ecological education. These works consistently address climate reconstruction challenges through technical refinement and cross-field collaboration. Her scientific recognition includes: IRACDA@UCLA faculty training program postdoctoral fellowship UCLA Center for Diverse Leadership in Science Early Career Fellowship Dr. Carroll actively contributes to undergraduate and graduate science education through curriculum development in ecological methods and computational science, though specific advising details and research grants are not documented in available materials. Her work reflects strong alignment with the university's environmental sustainability mission through both research and pedagogy.

Dov Krugerمشاهده پروفایل

استاد آموزشی

• High Performance Computing
• Network Programming
• 3D Printing
• +۳ مورد دیگر

Dov Kruger is an Associate Teaching Professor in the Department of Electrical Engineering at Rutgers University. He holds a BE in Electrical Engineering, an MS in Computer Science, and a PhD in Ocean Engineering, all from Stevens Institute of Technology. Prior to Rutgers, he spent 10 years as a professor at Stevens. His research focuses on high-performance computing, network programming, 3D printing, and computing education. He explores re-engineering software for efficiency, distributed programming models, and innovations in data compression and secure networking. His work also encompasses underwater acoustics and sensor systems from earlier career phases. Key themes in his recent articles include real-time video processing, federated learning privacy, AI bias mitigation, and blockchain-based systems. His earlier contributions involved underwater robotics and environmental sensor networks in estuaries. Dr. Kruger seeks collaborators in FPGA, network programming, and 3D printing. He has no listed scientific awards but maintains active research in multidisciplinary computer science and engineering education.

Adel Alaeddiniمشاهده پروفایل

استاد

• Mechanical Engineering
• Artificial Intelligence
• Machine Learning
• +۹ مورد دیگر

Dr. Adel Alaeddini is a Professor of Mechanical Engineering at Southern Methodist University (SMU) and holds courtesy professorships in Operations Research and Engineering Management and Computer Science. He serves as the O'Donnell Foundation Professor and Co-Executive Director of the Center for Digital and Human-Augmented Manufacturing (CDHAM). His research integrates physics-inspired artificial intelligence and machine learning methods to address challenges in Advanced Manufacturing, Healthcare, and Energy Systems. Education: Post Doctoral Research, University of Michigan Ph.D., Wayne State University Ph.D., Iran University of Science and Technology, Tehran, Iran Dr. Alaeddini's research focuses on: Physics-Inspired Machine Learning for Engineering Prognosis and Discovery Human-Augmented Control and Optimization of Complex Systems Industry 5.0-Driven Multi-Stream Sensor Data Modeling, Analytics, and Control Sample-Efficient Learning and Optimization of Black-Box Functions Generative AI-Enhanced Digital Twins for Collaborative Design and Optimization Deep Graph Analytics for Unraveling Complex System Dynamics His publications demonstrate expertise in Gaussian Processes, Graph Neural Networks, Stochastic Programming, and Reinforced Concrete Modeling, with applications in Radiology and Biofuel Supply Chains. These works highlight interdisciplinary collaboration across Computer Science, Biomedical Engineering, and Environmental Engineering domains. Scientific Awards: Summer Faculty Fellowship (2021, 2022, 2023) - Office of Naval Research (ONR) Best Poster Award (2019) - IISE Annual Conference Young Investigator Award (2016) - Air Force Office of Scientific Research (AFOSR) Summer Faculty Fellowship (2016) - AFOSR Pierskalla Competition Finalist (2010) - INFORMS Annual Conference Best Student Paper Award (2009) - Industrial Engineering Research Conference Selected Paper (2007) - IFSA World Congress Dr. Alaeddini has secured over $8M in grants from agencies including DOD, DOE, NSF, NIH, VA, DHS, and USDA. He serves as Associate Editor for multiple journals and Technical Vice President of IISE. His work at CDHAM emphasizes Industry 5.0 and human-AI collaboration in manufacturing ecosystems.