Prof. Dr. Hüseyin Yapıcı is a faculty member in the Department of Mechanical Engineering at Başkent University . His research focuses on Nuclear Energy Systems , Accelerator Technology , and Thermodynamics . Nuclear Reactor Design Energy Systems Optimization Heat Transfer Analysis His work involves numerical simulations , neutronic analysis , and nuclear waste transmutation . Recent publications highlight three-dimensional power density modeling in accelerator-driven systems and tritium production studies. Prof. Yapıcı has supervised numerous students, including Gizem Bakır , Alper Buğra Arslan , and Büşra Durmaz , across diverse projects from fusion-fission hybrids to renewable energy systems .
Mikael Johansson is a Professor at Kungliga Tekniska Högskolan (KTH), specializing in Control Technology . He teaches and coordinates courses such as Distributed Optimization (FEL3311) and various advanced-level degree projects in computer science, electrical engineering, and systems engineering. His research spans Control Systems , Machine Learning , and Optimization , with a focus on asynchronous algorithms, federated learning, and applications in energy systems and construction. His work includes 15 recent publications on topics like neural networks, distributed optimization, and battery technology. Notable areas of contribution are in asynchronous learning, federated learning with privacy constraints, and quasi-Newton methods for optimization. His research bridges theoretical advancements with practical applications in urban design, healthcare, and autonomous systems.
Dr. Sana Jahanshahi Anbuhi is an Associate Professor at the Department of Chemical and Materials Engineering , Gina Cody School of Engineering and Computer Science , Concordia University. She holds the Concordia University Research Chair Tier II in Stable Bio/Chemo-Sensors and serves as the Graduate Program Director for PhD and MASc programs. Her research focuses on Paper-based microfluidic devices and thermal stabilization of biologics for portable diagnostic applications. Education: Ph.D. in Chemical Engineering (2015), McMaster University , Canada B.Sc. in Chemical Engineering, Sharif University of Technology , Iran Her work emphasizes point-of-care diagnostics , bio-sensing , and detection of pesticides , heavy metals , and microorganisms . Recent publications highlight gold nanoparticle-based tablets for colorimetric assays in environmental monitoring and food safety . She has also contributed to flow control in paper microfluidics and vaccine stabilization using sugar films . Scientific patents include methods for stabilizing molecules without refrigeration and pullulan mixtures for preserving chemicals. Her teaching activities include courses on Advanced Separation Processes , Thermodynamics I , and Research Protocols and Safety . She actively mentors researchers and has participated in numerous international conferences and media features, including interviews in Le Devoir and The Globe and Mail .
John E. Taylor is the Frederick Law Olmsted Professor and Associate Chair for Faculty Development and Research Innovation at the Georgia Institute of Technology's School of Civil and Environmental Engineering within the College of Engineering. His research focuses on the intersection of human and engineered networks, with particular emphasis on creating resilient infrastructure systems that serve society's needs while creating more livable communities. Taylor's research interests span multiple domains including Smart City Digital Twins , Urban Infrastructure Resilience , Network Dynamics , and Building-Occupant Interaction . His work examines how human behavior, infrastructure systems, and environmental factors interact during normal operations and extreme events. He has developed innovative approaches to understanding urban systems through the lens of network theory and computational modeling. His publication record demonstrates consistent contributions to the fields of urban analytics and infrastructure resilience, with a recent focus on digital twin technologies for urban systems. Taylor's work shows a clear trajectory toward increasingly sophisticated integration of AI, network science, and civil infrastructure engineering to address complex urban challenges. His research has particular relevance for cities facing climate change impacts and seeking to build more equitable and resilient communities. Taylor leads the Network Dynamics Lab at Georgia Tech, where he mentors PhD students and postdoctoral researchers. His lab has produced significant work on human-infrastructure interaction, particularly during disasters and extreme events. The lab's research combines computational modeling, data analytics, and field studies to understand and improve urban systems. His work has been applied to real-world challenges including river emergency response systems, urban heat exposure forecasting, and disaster response optimization. Taylor has collaborated with city officials and agencies to implement systems that have demonstrable community benefits, such as the AI-enabled camera system for drowning prevention on the Chattahoochee River and crime reduction systems using mobile cameras guided by AI algorithms.
Karen M Feigh is a Professor and Associate Chair for Research in the Daniel Guggenheim School of Aerospace Engineering at the Georgia Institute of Technology, holding the prestigious David S. Lewis Professorship. Her interdisciplinary work integrates aerospace engineering with cognitive sciences to address human-machine interaction challenges in complex aviation and autonomy systems. Education B.S. in Aerospace Engineering, Georgia Institute of Technology MPhil in Aeronautics, Cranfield University, UK Ph.D. in Industrial and Systems Engineering, Georgia Institute of Technology Dr. Feigh's research centers on cognitive engineering applications for flight operations and air traffic management. Through ethnographic studies, human-in-the-loop experiments, and expert system design, she develops solutions that align technology with human cognitive processes to enhance safety and efficiency in NextGen air traffic concepts, vertical lift systems, and autonomous vehicle operations. Scientific Awards David S. Lewis Professorship in the School of Aerospace Engineering (2025) AIAA Wilbur and Orville Wright Graduate Award (2006) Zonta International Amelia Earhart Fellowship (2005) National Science Foundation Graduate Research Fellowship (2001-2006) Marshall Scholarship (2001-2003) As director of the Cognitive Engineering Center (CEC), Dr. Feigh mentors graduate researchers and leads interdisciplinary collaborations across Georgia Tech's research ecosystem. The CEC, embedded within the Vertical Lift Research Center of Excellence and Institute for Robotics and Intelligent Machines, secures funding from agencies including NSF and AIAA to advance adaptive intelligence for industrial robotics and air traffic control systems. Laboratories and Collaborations The Cognitive Engineering Center under Dr. Feigh's leadership conducts field work, human-subjects studies, and mathematical modeling to solve human-machine interaction challenges. The lab maintains active partnerships with NASA, FAA, and industry stakeholders to implement research findings in real-world aerospace operations, with current focus on adaptive interfaces for autonomous systems and crew decision support tools.
Kwanghee Jeong is a Research Fellow at the University of Western Australia , affiliated with the Fluid Science and Resources research group within the School of Engineering and Chemical Engineering Department . His work focuses on energy transport, decarbonisation technologies, and flow assurance. Education: PhD in Chemical Engineering (UWA, 2020), BSc in Mechanical Engineering (Dongguk University, 2014) Research Themes include: Flow Assurance for hydrogen, CO2, and natural gas pipelines Carbon Capture & Emissions Management (MOFs, Raman spectroscopy) Cryogenic Hydrogen Process Engineering (liquefaction, boil-off gas) Cold Energy Utilisation and Waste Heat Recovery Hydrate Formation Kinetics via Acoustic Levitation Article Trends reflect expertise in: Using Raman spectroscopy for real-time adsorption and phase transition analysis Developing Joule-Thomson loops to simulate pipeline conditions Optimizing Metal-Organic Frameworks for GHG separation Advancing hydrogen liquefaction efficiency through catalysis Addressing microplastics and hydrate nucleation via spectroscopic methods Scientific Awards : Best Poster Award (2023) - Natural Gas UWA Travel Award (2017) ARC PhD Scholarship (2016) He contributes to UN Sustainable Development Goals via decarbonisation research and has collaborated with Chevron, Woodside Energy, and Curtin University. His technical skills include Aspen HYSYS, OLGA simulations, HAZOP studies, and Differential Scanning Calorimetry (DSC).
Professor Lyudmila Mihaylova is a distinguished academic at the University of Sheffield's School of Electrical and Electronic Engineering, where she holds the position of Professor of Signal Processing and Control. She has established herself as a leading researcher in the fields of signal processing, Bayesian methods, and autonomous systems, with significant contributions to particle filtering techniques for intelligent transportation systems. Her work bridges theoretical developments with practical applications across multiple domains including transportation, healthcare, and industrial automation. Prof. Mihaylova's research interests center on nonlinear filtering, sequential Monte Carlo methods, statistical signal processing, and sensor data fusion. Her work spans both theoretical advancements and practical implementations, with particular focus on high-dimensional problems including vehicular traffic flow estimation, image processing, and localization in sensor networks. She has extensive experience with various image modalities such as optical, thermal, LIDAR, SAR, and hyperspectral imaging. Her group actively develops novel methods for autonomous intelligent systems focusing on sensing, tracking, decision making, and machine learning applications. Analysis of Prof. Mihaylova's recent publications reveals a strong trend toward uncertainty quantification in machine learning models, particularly for safety-critical applications. Her work increasingly integrates traditional signal processing techniques with modern deep learning approaches, with applications spanning sewer inspection robotics, medical diagnostics (particularly sleep apnea detection), UAV swarm tracking, industrial manufacturing, and autonomous vehicle systems. A significant portion of her recent research focuses on developing robust methods that can handle incomplete or outlier-corrupted data while providing reliable uncertainty estimates. Among her notable professional achievements: President of the International Society of Information Fusion (ISIF) Senior member of the IEEE Signal Processing Society Associate Editor for IEEE Transactions on Aerospace and Electronic Systems Associate Editor for Elsevier Signal Processing Journal Prof. Mihaylova has successfully mentored numerous PhD students and postdoctoral researchers, many of whom have gone on to prominent academic and industry positions. Her research has been supported by major funding bodies including EPSRC, EU, MOD/DSTL, and industry partners, with recent projects including 'Protecting Environments with UAV Swarms' (InnovateUK, 2022-2024), 'ShiRAS: Towards Safe and Reliable Autonomy in Sensor Driven Systems' (NSF-EPSRC, 2019-2023), and 'Confident safety integration for Cobots' (Lloyd's Register Foundation, 2019-2020). Her research group follows a collaborative approach with the philosophy 'We share knowledge, we grow.' Prof. Mihaylova maintains active research collaborations with institutions worldwide and has held previous academic positions at Lancaster University (2006-2013) and University of Bristol (2004-2006), along with research visiting positions at the University of Ghent, Katholic University of Leuven, and the Bulgarian Academy of Sciences.
John F. Reid is a prominent Research Professor at the University of Illinois at Urbana-Champaign in the College of Engineering , with dual appointments in Computer Science and Agricultural and Biological Engineering . He serves as Executive Director of the Center for Digital Agriculture . With over 35 years of experience in academic and industrial R&D, his career spans faculty roles at UIUC (1986-2000), leadership at Deere & Company (2000-2020), and Vice President positions at Brunswick Corporation (2020-2022). Education : Ph.D. in Agricultural Engineering (Texas A&M, 1987), M.S. and B.S. in Agricultural Engineering (Virginia Tech, 1982 & 1980) Dr. Reid's research focuses on agricultural automation , machine vision , and innovation management . He has pioneered agricultural robotics , precision technologies , and embodied AI applications in food, construction, and marine systems. His work has resulted in over 30 patents in automated guidance , sensor systems , and agricultural informatics . His scientific contributions center on stereo vision navigation , 3D field mapping , and adaptive control systems for mobile equipment. These innovations underpin modern precision agriculture and agricultural robotics frameworks. Major awards include: NAE Election (2019) ASABE Fellow (2004) University Scholar (1995) Academy of Engineering Excellence (2020) He holds leadership roles in international organizations including the CIGR Working Group on Circular Bioeconomy Systems (Chair 2024-present) and Fraunhofer USA (2013-2022).
Christiane C. Schubert is an Assistant Professor in Medical Education at the School of Medicine and an Assistant Professor in Interdisciplinary Studies at the School of Behavioral Health at Loma Linda University. Her dual appointments reflect her interdisciplinary approach to healthcare research and education, bridging medical education with behavioral health perspectives. Dr. Schubert's educational background includes: PhD from Loma Linda University (2008) MS from Northern Arizona University (1999) BS from Northern Arizona University (1997) Her research program focuses on understanding healthcare systems through multiple lenses. She investigates how patients with chronic illnesses navigate self-care within complex healthcare environments, with particular attention to macroergonomic factors that influence patient work systems. Dr. Schubert examines resilience in healthcare settings, exploring how both patients and providers adapt to challenges in clinical environments. Her work addresses cultural factors in healthcare, particularly examining how acculturation affects health-promoting behaviors among Arab Americans. Through her studies on novice-expert differences in emergency medicine, she contributes to understanding cognitive work processes in high-stakes clinical settings. Her interdisciplinary approach integrates insights from medical education, behavioral health, and systems engineering to address complex healthcare challenges. Dr. Schubert's scholarly output from 2012-2017 demonstrates consistent contributions across healthcare resilience, patient work systems, medical education, and cultural competence. Her publications reveal a trajectory of increasingly sophisticated systems thinking applied to healthcare delivery challenges, with a particular emphasis on understanding patient experiences and clinician cognition within complex healthcare environments. Dr. Schubert has maintained an active research and publication record since completing her PhD in 2008. Her work demonstrates a commitment to improving healthcare delivery through better understanding of patient experiences, clinician cognition, and system-level factors that influence healthcare outcomes. Her interdisciplinary appointments position her to bridge traditional academic boundaries in addressing complex healthcare challenges.
Amir Bahadori serves as Professor and Nuclear Engineering Program Director in the Department of Mechanical and Nuclear Engineering at Kansas State University's Carl R. Ice College of Engineering, holding the Hal and Mary Siegele Professorship in Engineering. He directs the Radiological Engineering Analysis Laboratory (REAL) and established the Institute for Radiation Health Studies (IRHS) in 2024, focusing on radiation protection, space radiation environments, and radiation health effects. His educational background includes: Ph.D. in Biomedical Engineering, University of Florida (2012) M.S. in Nuclear Engineering Sciences, University of Florida (2010) B.S. in Mechanical Engineering and Mathematics, Kansas State University (2008) Bahadori's research spans radiation transport modeling, dosimetry, and risk assessment with applications in space exploration, medical physics, and radiation epidemiology. He develops computational frameworks for radiation exposure scenarios and biological response prediction, emphasizing space radiation protection for Artemis missions and chronic exposure studies through the Million Person Study collaboration. Analysis of his recent publications reveals dominant themes in space radiation measurement (Artemis missions), radiation epidemiology (Million Person Study innovations), and advanced detection systems (miniaturized neutron spectrometers). His work increasingly integrates big data approaches for radiation risk assessment and electrostatic shielding concepts for deep-space exploration. His scientific recognition includes: NASA Graduate Student Research Fellowship (2009) Certified Health Physicist designation Big 12 faculty fellowship (2022-2023) NCRP council election (2024) Two USPTO patents Bahadori secures substantial research funding from NASA for space radiation instrumentation, Department of Energy projects via the Kansas City National Security Campus, and collaborative epidemiological studies. He mentors nuclear engineering graduate students while leading interdisciplinary teams developing radiation protection solutions for aerospace and medical applications. His laboratory infrastructure includes the REAL with Beocat high-performance computing resources, radiation detectors, and a 3D printer, plus the IRHS with a Precision X-ray XRad320 irradiator and radon chamber. These facilities support collaborations across K-State colleges and external organizations for radiation health effect studies.
Neda Haj Hosseini is a Senior Lecturer and Associate Professor in Biomedical Engineering at Linköping University's Department of Biomedical Engineering (IMT) . She contributes to teaching courses like TBMT56 - Medical Technology and TBME08 - Biomedical Modeling and Simulation , while leading research initiatives in AI-driven cancer diagnostics and biomedical optics. Research Focus: Development of AI methods for cancer diagnostics, optical coherence tomography (OCT) applications, and fluorescence spectroscopy in surgical guidance Affiliations: Center for Medical Image Science and Visualization (CMIV) , Analytic Imaging Diagnostic Arena (AIDA) , Swedish Medical Technology Association Recent Research Trends demonstrate expertise in applying deep learning to: Pediatric brain tumor classification using multimodal imaging Optical biopsy techniques for intraoperative decision support Automated biomarker quantification in histopathology Medical imaging data integrity and algorithm validation Scientific Awards include grants from: Joanna Cocozza Foundation (2022) Swedish Childhood Cancer Foundation (2024) Academic Leadership involves mentoring students in projects such as: "Multiple Instance Attention-based Learning for Brain Tumor Classification" "Vision Transformers for Multiclass Brain Tumor Tissue Classification" "Reaction-diffusion Models for Image-driven Tumor Simulation"
Colin Drummond, PhD, MBA is a Professor in the Department of Biomedical Engineering at both the Case School of Engineering and School of Medicine , where he also serves as Assistant Department Chair. His research focuses on simulation and applied informatics to enhance healthcare decision-making with translational applications in wearable technology and conversational agents for isolated patients. Doctorate in Biomedical Engineering (PhD) Master of Business Administration (MBA) Research interests span healthcare informatics , wearable analytics , and clinical decision support systems . Recent work explores: Physiological monitoring through wearable sensors Heart rate accuracy in consumer devices like Apple Watch Conversational agents for polypharmacy management Performance assessment in athletes and post-surgical rehabilitation
Summary Luis A. Duffaut Espinosa is an Assistant Professor in the Department of Electrical and Biomedical Engineering at the University of Vermont (UVM), affiliated with the College of Engineering and Mathematical Sciences. His research focuses on control theory, estimation, robotics, and nonlinear systems with applications in autonomy, quantum control, and environmental monitoring. He holds a Ph.D. in Electrical and Computer Engineering from Old Dominion University (2009) and has held academic positions at George Mason University and postdoctoral roles at Johns Hopkins University and the University of New South Wales. Education: Ph.D. in Electrical and Computer Engineering (2009), Old Dominion University M.S. in Mathematics (2005), Pontificia Universidad Católica del Perú B.S. in Physics (2003), Universidad Nacional de Ingeniería, Peru Research Interests: His work emphasizes data-driven control and estimation methodologies, including model-free approaches for power systems, environmental monitoring, and quantum control. Current projects include real-time data assimilation in harsh environments, resilient robotics in GPS-denied conditions, and SAR with small satellites. He co-directs the Autonomous and Intelligent Systems Research Laboratory (AIRLab) and is part of the CREATE center. Recognition: 2024 NSF CAREER Award for work on safety-aware data-driven control frameworks Teaching & Advising: He teaches courses in estimation theory, control systems, and signal processing. Advises a team of graduate and undergraduate students focusing on autonomy, robotics, and control systems. Notable students include Danial Waleed (Ph.D. 2024), Jacob Friz-Trillo (M.S. 2025), and Farnaz Boudaghi (Ph.D. candidate). Labs & Collaborations: AIRLab: Focuses on data-driven control for autonomy in robotics and engineered systems CREATE: Research on resilient energy and autonomous technologies
Harpreet S. Dhillon is the W. Martin Johnson Professor of Engineering and Associate Dean for Research and Innovation at Virginia Tech's College of Engineering. He holds appointments in the Bradley Department of Electrical and Computer Engineering. His research focuses on wireless communications, stochastic geometry, machine learning, and next-generation network systems. Education: Ph.D., University of Texas at Austin (2013); M.S., Virginia Tech (2010); B.Tech., Indian Institute of Technology Guwahati (2008). Research Interests: Communication Theory, Stochastic Geometry, Machine Learning for Communication Systems, Heterogeneous Networks, IoT, and Energy Harvesting. He leads projects on vision-aided localization, LEO satellite systems, and RIS-aided networks. Key Awards: IEEE Fellow (2023), AAIA Fellow (2022), IEEE Heinrich Hertz Award (2016), and numerous early-career recognitions. His work has resulted in over 150 journal/conference publications. Advising: Supervises Ph.D. students in cutting-edge research areas like 6G localization and RIS optimization. His advisees have won awards such as the VT ECE Blackwell Award for Best Dissertation. Labs/Teams: Head of the research group focusing on communication theory and localization. Collaborates on projects funded by agencies like NSF and industry partners.
Anis Fatima is an Assistant Professor in the Department of Manufacturing and Mechanical Engineering Technology at Michigan Technological University's College of Engineering. Her research focuses on digitalization of manufacturing processes, sustainable manufacturing practices, and human factors engineering. Office: EERC 321 Contact: 906-487-1968 Teaching interests include machine tool fundamentals, statistical methods, manufacturing processes, advanced manufacturing techniques, industrial safety, applied quality control, and organizational leadership.
