جستجوی استاد راهنمای دانشگاهی

Manu Prakashمشاهده پروفایل

دانشیار

• Frugal Science
• Low-cost Diagnostic Tools
• Microscopy
• +۸ مورد دیگر

Manu Prakash is an Associate Professor of Bioengineering at Stanford University, with courtesy appointments in Biology and Oceans, and serves as a Senior Fellow at the Woods Institute for the Environment. His research spans bioengineering, oceanography, and global health with a focus on developing affordable scientific tools for communities worldwide. Dr. Prakash earned his Ph.D. in Applied Physics from MIT (2008), an M.S. in Applied Physics from MIT (2004), and a B.Tech in Computer Science and Engineering from the Indian Institute of Technology (2002). His academic journey included a Junior Fellowship at the Harvard Society of Fellows (2008-2011) before joining Stanford. Prakash's research centers around 'frugal science' - developing low-cost, accessible scientific tools that can be deployed globally. His work includes creating pocketable microscopes (Foldscope), mosquito and plankton monitoring systems, and autonomous malaria diagnostic platforms. He uses interdisciplinary approaches to understand how computation is embodied in biological matter, including cognition in single-cell protists and morphological computing in animals without neurons. His laboratory has produced numerous innovative tools deployed worldwide, including Foldscope for microscopy and Abuzz for mosquito surveillance. His publications reveal a strong focus on developing instruments for studying non-model organisms, particularly marine life, and addressing fundamental questions about cellular sensing mechanisms. MacArthur Fellow, MacArthur Foundation (2016) HHMI-Gates Faculty Scholar, HHMI (2016-2021) TR35, MIT Technology Review (2014) Brilliant 10, Popular Science (2014) TED Senior Fellow (2011-2013) Junior Fellow, Harvard Society of Fellows (2008-2011) Prakash actively mentors numerous doctoral students and postdoctoral researchers working on projects related to frugal science, ocean monitoring, and disease diagnostics. His laboratory collaborates globally with organizations including the Institute Pasteur in Senegal, UCSF Malaria Eliminate Initiative, and research institutions in Tanzania and India. Major projects include Planktoscope for ocean microbial mapping, Octopi for malaria diagnostics, and Foldscope for low-cost scientific instruments.

Pei Liمشاهده پروفایل

استادیار

• Transportation Engineering
• Artificial Intelligence
• Digital Twins
• +۵ مورد دیگر

Dr. Pei Li is an Assistant Professor in the Department of Civil and Architectural Engineering and Construction Management at the University of Wyoming. Her research focuses on advancing safety and mobility through the development of digital, intelligent transportation systems that can sense traffic, predict future conditions, and make decisions. She bridges transportation engineering with cutting-edge technologies including digital twins, AI, and V2X communication systems. Dr. Li's educational background includes: B.Eng in Logistics Engineering from Tongji University (2015) M.Eng in Communication and Transportation Engineering from Tongji University (2018) M.S. in Smart Cities from University of Central Florida (2020) Ph.D. in Civil Engineering from University of Central Florida (2021) Dr. Li's research spans multiple domains in intelligent transportation systems. Her primary interests include Digital Twins, Artificial Intelligence, Transportation Safety, and Human Factors. She develops models that leverage deep learning, computer vision, and sensor technologies to create innovative solutions for traffic management and crash prevention. Her work often addresses the challenges of real-time decision making in complex transportation environments, with particular emphasis on pedestrian safety, autonomous vehicle systems, and connected infrastructure. Dr. Li's publication record shows a progression from basic vehicle maneuver detection using smartphone sensors to sophisticated digital twin applications and explainable AI for autonomous systems. Her recent work (2024-2025) demonstrates expertise in large language models for transportation, federated digital twin frameworks, and physics-informed trajectory planning. She frequently employs advanced techniques including deep reinforcement learning, attention mechanisms, and natural language processing to address complex transportation safety challenges. Dr. Li maintains an active research presence through multiple platforms including ResearchGate, LinkedIn, GitHub (as PeiLi-Sandman), and Google Scholar. Her GitHub profile shows contributions to self-driving car projects, including implementations of particle filters, MPC controllers, and other autonomous vehicle technologies from the Udacity Self-Driving Car Engineer Nanodegree program. Dr. Li is actively recruiting students for her research group, with opportunities available for those interested in digital twins, artificial intelligence, transportation safety, and human factors research. She appears to be establishing a robust research program at the University of Wyoming focused on intelligent transportation systems, with particular emphasis on making transportation safer through advanced computing technologies.

SJ Kimمشاهده پروفایل

دانشیار

• Intelligent Interactive Media and Systems
• Human-Computer Interaction
• Augmented and Virtual Reality
• +۵ مورد دیگر

SJ (Si Jung) Kim, Ph.D. is an Associate Professor in the Department of Entertainment Engineering and Design at the Howard R. Hughes College of Engineering, University of Nevada, Las Vegas (UNLV) , and serves as the founding director of the Digital Experience Lab (DEX Lab) . With more than 20 years of interdisciplinary experience spanning human-computer interaction, mechatronics, and intelligent systems, he leads cutting-edge research that bridges cyber-physical systems and interactive media to enhance user experiences. Education: Ph.D. in Human-Computer Interaction (HCI) M.S. in Robotics B.S. in Electronic/Mechatronics Engineering Research Interests: Dr. Kim’s work centers on intelligent interactive interfaces and technologies grounded in human-factors theory and HCI principles. Core areas include: Design and evaluation of immersive AR/VR systems Machine-learning-driven human augmentation Cyber-physical systems that seamlessly merge physical and digital worlds User-centered design of next-generation entertainment and educational technologies His research agenda emphasizes interdisciplinary collaboration to push technological boundaries while ensuring meaningful human benefit. Publication Landscape: Across 50+ peer-reviewed works from 1998 to 2024, Dr. Kim’s scholarship reveals three dominant trajectories: (1) convergence of mixed reality and IoT/digital-twin ecosystems, (2) empirical studies on user presence, cognition, and performance in virtual environments, and (3) development of novel hardware–software platforms for education, healthcare, and entertainment. These contributions collectively advance the theoretical and practical frameworks for intelligent interactive systems. Professional Appointments & Collaborations: Associate Professor, UNLV (current) Director, Digital Experience Lab (DEX Lab) Former roles: Samsung Electronics, Korea Institute of Science & Technology (KIST), Electronics and Telecommunications Research Institute (ETRI), and HP Labs, Palo Alto (intern) Labs & Teams: The DEX Lab under Dr. Kim’s direction is dedicated to exploring and advancing intelligent interactive media and systems. The lab fosters an environment of collaboration among graduate researchers and industry partners, focusing on projects that integrate AR/VR, AI, and IoT to create transformative user experiences.

Michael Papoutsidakisمشاهده پروفایل

استاد

• Automatic Control Systems
• Mechatronics
• Industrial Automation
• +۸ مورد دیگر

Professor Michael Papoutsidakis is affiliated with the Department of Industrial Design and Production Engineering at the University of West Attica. His academic career spans research in industrial automation, mechatronics, and intelligent control systems, with a focus on applications in hydraulic/pneumatic systems, robotics, and Industry 4.0 technologies. PhD from Bristol Robotics Laboratory (2004) MSc in Automatic Control Systems from University of the West of England (2004) Graduated from TEI Piraeus Automation Engineering (2000) His research interests include: Modeling of fluid power systems AI-driven control algorithms Smart logistics and ERP systems Embedded systems for motion devices Autonomous robotic platforms Wireless sensor networks in industrial applications Recent publications highlight his work at the intersection of 3D printing, robotics, and Industry 4.0, including advancements in digital twins, biomimetic manufacturing, and drone technology. His research emphasizes practical implementations for industrial and educational contexts. 2005 Patent for robotic training base 2025 Digital Twin Systems research 2024 UAV fuzzy control systems Contact: mipapou@uniwa.gr

• Artificial Intelligence
• Fuzzy Logic
• Machine Learning
• +۳ مورد دیگر

Djordje Obradovic is a researcher at Singidunum University with a focus on artificial intelligence, fuzzy logic, and geospatial analysis. He holds a Ph.D. in Electrical Engineering and Computer Science from the University of Novi Sad (2011). Education: B.Sc., M.Sc., Ph.D. in Electrical Engineering and Computing, University of Novi Sad (1992–2011) His research spans machine learning, neural networks, and fuzzy systems applied to diverse domains including medical imaging, environmental monitoring, and social media analysis. Recent publications highlight his work on air quality modeling and panoramic image processing in GIS applications. Key contributions include intelligent systems for scoliosis screening using low-cost sensors and innovative approaches to big data management through fuzzy sets and graph theory. He actively participates in international conferences like ICIST and Sinteza, often collaborating with multidisciplinary teams. At Singidunum University, Obradovic contributes to postgraduate studies while developing software architectures for geospatial data processing, educational technology, and inspection management systems. Notable projects include SCORM-compatible e-learning platforms, anthropomorphic gait simulation systems, and web-based tools for topographical symbol detection.

• Agent Technology
• Artificial Intelligence
• Autonomous Driving
• +۹ مورد دیگر

Prof. Dr.-Ing. habil. Dr. hc Sahin Albayrak is a distinguished academic and entrepreneur at the Technical University of Berlin , where he founded and directs the Distributed Artificial Intelligence Laboratory (DAI Laboratory) . He leads the Agent Technologies in Business Applications and Telecommunications research group and serves as founding member of Deutsche Telekom Laboratories (2004) and European Center for ICT (EICT) (2005). As initiator of Connected Living e.V. (2009) and managing director of German-Turkish Advanced Research Center for ICT (2012), he bridges international collaborations. He also founded IOLITE GmbH (2014) and other startups. Research Focus: Agent technology, autonomous driving, smart cities, cyber security, machine learning, and AI applications in energy systems Awards: Federal Cross of Merit (2014), multiple Best Paper Awards Leadership: Director of DAI Laboratory, head of research group at TU Berlin His 20+ recent publications (2022-2025) demonstrate expertise in agent-based architectures , smart mobility solutions , context-aware computing , and AI-driven security systems . Notable trends include integrating large language models into database interfaces, optimizing multi-agent coordination for logistics, and advancing explainable AI through feature attribution frameworks. Scientific Contributions: Recipient of Germany's Bundesverdienstkreuz for German-Turkish cooperation Best Paper Award at Smart Grid Architectures conference

• Machine Learning
• Artificial Intelligence
• Agent-Based Modelling and Simulation
• +۷ مورد دیگر

Professor Douglas Creighton is a Deakin Distinguished Professor and Director of the Institute for Intelligent Systems Research and Innovation (IISRI) at Deakin University. With a career spanning complex systems modeling, AI, and agent-based simulation, he leads a 100-strong research team working on real-world defense, transport, med tech, and advanced manufacturing solutions. His current research program includes three pillars: systems thinking and quantitative analytics, computational intelligence, and agent-based modeling. PhD in Industrial/Systems Engineering from Deakin University Bachelor of Engineering (Systems Engineering) and Bachelor of Science (Physics) from Australian National University His research strengths include smart transport systems, simulation modeling, robotics, and data analytics. Recent publications focus on stress quantification via EEG analysis, video instance segmentation, and ethical AI implementation in rail systems. He has developed trust estimation algorithms for autonomous agents and contributed to frameworks for rural community health engagement. Scientific recognition includes: SAE Mobility Engineering Excellence Gold Award (2016) IISRI Excellence in Industry Collaboration Award (2020) Three best paper awards at IEEE conferences As a supervisor, he currently guides research on: Mental stress quantification using brain connectivity Multi-cloud decision architecture Immersive technology for Industry 5.0 repair engineers Causal loop diagram representation for public health His industry collaborations span Australian Defence, Alstom Transport, Boeing, and rail/water organizations. Current grants include projects with the Australian Electoral Commission, Flame Security International, and advanced aerial mobility research.

• Robotics
• Robot Audition
• Optimal Filtering and Estimation
• +۴ مورد دیگر

He Kong is an Associate Professor at Southern University of Science and Technology (SUSTech), affiliated with the School of Automation and Intelligent Manufacturing, where he also serves as Deputy Director of the SUSTech Institute of Robotics. Previously, he was an Assistant Professor in the Department of Mechanical and Energy Engineering at SUSTech from January to May 2022. Prior to joining SUSTech, he was a Research Fellow at the Australian Centre for Field Robotics, University of Sydney (2016-2021), and at Cranfield University's Advanced Vehicle Engineering Centre (2015-2016). He received his Ph.D. in Electrical Engineering from the University of Newcastle, Australia (2014), M.E. in Control Science and Engineering from Harbin Institute of Technology (2010), and B.E. in Electrical Engineering and Automation from China University of Mining and Technology (2004). His research focuses on robotic intelligent perception and decision making, robot audition, optimal filtering and estimation, and advanced control methods. Specifically, he works on active multi-mode perception, parameter calibration of robot audition systems, optimal filtering under unknown inputs, and fully actuated system approaches. His work has significant applications in precision agriculture, environmental monitoring, and robotic inspection of hazardous industries such as chemical and mining operations. His recent publications reveal a strong emphasis on multi-modal perception systems, particularly combining visual and auditory sensing for robotic applications. His research shows a progression from theoretical control methods toward practical implementations in field robotics, with increasing focus on real-world applications in agriculture and hazardous environments. Finalist for Youth Author Prize, IFAC Workshop on Robot Control (2019) Fifth China Robotics Academic Annual Conference Best Poster Award (2024) 14th International Conference on Indoor Positioning and Indoor Navigation Best Paper Award (2024) The Equity Scholarship, Council of International Students Australia (2011) Outstanding Postgraduate Students Award, Harbin Institute of Technology (2010) Professor Kong actively supervises numerous PhD and Master's students and has established a productive research group focused on active intelligent systems. His laboratory is equipped with advanced facilities including over 30 motion capture systems, Unitree humanoid robots, robot dogs, wheeled mobile robots, and custom-developed platforms like Cubli and acoustic perception systems. He serves on editorial boards for several prestigious journals including IEEE Robotics and Automation Letters and IEEE Sensors Letters, and has been an Associate Editor for major robotics conferences such as IEEE ICRA and IEEE/RSJ IROS.

Parminder Singh Kangمشاهده پروفایل

دانشیار

• Supply Chain Management
• Machine Learning
• Artificial Intelligence
• +۵ مورد دیگر

Dr. Parminder Singh Kang serves as Associate Professor in the Department of Decision Sciences at MacEwan University's School of Business, specializing in supply chain optimization through advanced analytics and machine learning. His cross-disciplinary research integrates people, process, and technology elements to solve complex industrial and service operations challenges. Education: PhD from De Montfort University M.Sc. from De Montfort University Dr. Kang's research centers on applying AI/ML, combinatorial optimization, and simulation modeling to enhance supply chain resilience and customer-centric service systems. His work bridges theoretical frameworks with industry applications, focusing on sustainable digitization, risk profiling, and process improvement through evolutionary algorithms and Lean/Six Sigma methodologies. Recent projects address circular economy integration and Service 4.0 transformation. His publication portfolio reveals strong trends in machine learning applications for supply chain risk analysis, text mining for competency mapping, and digital twin development for customer-centric operations. The research spans theoretical models like HI-TOP to practical case studies on pandemic disruptions and ERP implementation, demonstrating industry-relevant academic contributions. Scientific Awards: Best Paper Award, Administrative Sciences Association of Canada (2018) Horace Pops Medal Award, Wire Cable Conference (2015) Dr. Kang supervises senior student independent studies while teaching business intelligence, machine learning, and supply chain management courses at undergraduate, graduate, and MBA levels. His research is funded by NSERC, MITACS, Alberta Innovates, and industry partners including Fluor Canada, Apana Technologies, and the City of Calgary, supporting projects valued at over $2M annually. He leads collaborative research with Panjab University, CPA Canada, and TATA Steel Europe, focusing on supply chain digitization and process optimization. His work with UK-based SMEs and Canadian organizations drives practical implementation of analytics frameworks in real-world operational environments.

Pascual Campoy Cerveraمشاهده پروفایل

استاد

• Robotics
• Computer Vision
• Unmanned Aerial Vehicles (UAVs)
• +۶ مورد دیگر

Pascual Campoy Cervera is a Full Professor at the Universidad Politécnica de Madrid (UPM) and holds visiting professor positions at Delft University of Technology, Tongji University, and Queensland University of Technology. His work focuses on Control Systems , Machine Learning , and Computer Vision for Unmanned Aerial Vehicles (UAVs) . As Principal Investigator of the Computer Vision and Aerial Robotics group at UPM's Center for Automation and Robotics (CAR), he has led over 40 R&D projects with European, national, and industrial funding. Current affiliations: UPM, TU Delft, CAR-UPM Research themes: UAV autonomy, swarm robotics, embedded vision systems His research integrates cutting-edge technologies in image processing, control theory, and artificial intelligence to enhance UAV capabilities in unstructured environments. Recent projects include: Autonomous firefighting systems High-speed drone racing frameworks Swarm-based solar farm inspection Thrust vectoring for heavy UAVs Notable scientific awards include multiple international prizes at UAV competitions (IMAV12–17). His team has developed the Aerostack and Aerostack2 frameworks for aerial robotics, which address execution control, mission planning, and sensor fusion challenges.

Kelly Bijankiمشاهده پروفایل

دانشیار

• Neuromodulation
• Cognitive Neuroscience
• Neuroimaging
• +۳ مورد دیگر

Kelly Bijanki, Ph.D. , is an Associate Professor at Baylor College of Medicine with primary affiliation in Neurosurgery and joint appointments in Psychiatry and Neuroscience. Her research focuses on intracranial mapping of affective neural circuits and developing neuromodulation therapies for psychiatric disorders. Baylor College of Medicine (2016-present) Director of Intracranial Monitoring Research Research Platforms: Stereotactic EEG-informed DBS, Human Electrophysiology Research Expertise : Investigates neural substrates of mood disorders using invasive brain recordings Specializes in cingulum bundle, amygdala, and salience network stimulation Develops translational models for affective dysfunction treatment Integrates advanced neuroimaging with electrophysiological data Studies autonomic and facial motor correlates of emotional states Publication Trends : Focus on socio-affective processing networks Emphasizes brain stimulation for psychiatric conditions Combines imaging and electrophysiology in depression research Explores temporal dynamics of neural circuits Develops novel analytical methods for neurostimulation data Scientific Recognition : NIH R01 MH127006 (2021-2026) - $3.6M NIH K01 MH116364 - NIMH Mentored Career Development NIH R21 NS104953 - Exploratory Brain Stimulation Research Caroline Wiess Law Fund Support Collaborative grants with institutions like Duke, UCLA, and University of Iowa Collaborative Network : Key collaborators: Dr. Sarah Heilbronner, Dr. Nader Pouratian, Dr. Nanthia Suthana Multi-institutional partnerships in biophysics and biomedical engineering Leadership in stereotactic EEG-augmented DBS for psychiatric disorders

Peter George Martinمشاهده پروفایل

پژوهشگر ارشد

• Radiation Detection
• Nuclear Threat Reduction
• Nuclear Forensics
• +۵ مورد دیگر

Dr. Peter George Martin is a Royal Academy of Engineering Research Fellow in the School of Physics at the University of Bristol, specializing in radiation detection systems and nuclear threat reduction. His work develops responsive, high-resolution platforms for monitoring radioactive materials and enhancing nuclear security infrastructure. He earned his BSc and PhD from the University of Bristol, with doctoral research analyzing the 2011 Fukushima Daiichi Nuclear Power Plant accident across 10 orders of magnitude. His educational foundation combines physics with nuclear engineering expertise. Dr. Martin's research spans critical nuclear domains: Radiation Detection: Innovating gamma spectroscopy and sensor networks for real-time monitoring Nuclear Threat Reduction: Creating systems to prevent illicit radioactive material trafficking Nuclear Forensics: Investigating accident scenarios and radiological release incidents AI Integration: Developing machine learning algorithms for radiation data analysis Decommissioning Technologies: Pioneering robotics for nuclear site characterization His recent publications demonstrate converging trends in autonomous radiation mapping, AI-driven spectral analysis, and fundamental nuclear materials research, particularly focused on Fukushima and Chernobyl applications. Scientific recognition includes: Faculty of Science Thesis Commendation (2019) Innovus Nuclear Institute Technology Supply Chain Academic Abstract Prize (2016) Roy G. Post Scholarship (2016) Dr. Martin leads significant grant-funded initiatives including the RAIN at Chernobyl project and international collaborations with Japan, Ukraine, and the USA. His research partnerships span UK Atomic Weapons Establishment, Sellafield, IAEA, and global academic institutions, with emphasis on fieldwork at Fukushima and Chernobyl sites. He directs a research group developing open-source radiation analysis tools and autonomous mapping systems, maintaining active field deployments at nuclear facilities worldwide while advancing nuclear waste characterization methodologies.

Ali Emre Turgutمشاهده پروفایل

دانشیار

• Swarm robotics
• mechatronics
• manufacturing systems
• +۳ مورد دیگر

Ali Emre Turgut is an Associate Professor at Middle East Technical University (METU) in Ankara, Turkey. His research intersects robotics, control systems, and bio-inspired design, with a focus on swarm robotics, UAVs, and complex systems. He maintains a formal email address ( aturgut@metu.edu.tr ) and an online presence at users.metu.edu.tr/aturgut . Education B.Sc. in Electrical Engineering, METU (1996) M.Sc. in Electrical Engineering, METU (1999) Ph.D. in Electrical Engineering, METU (2008) Research Interests center on swarm robotics , mechatronics , and unmanned aerial vehicles (UAVs) . His work explores self-organization in robotic swarms, bio-inspired control mechanisms, and adaptive systems for complex environments. Key themes include: Swarm intelligence for collective motion and task specialization Design and control of aerial and legged robots Applications in environmental monitoring, manufacturing, and biological interaction Publication Trends highlight his leadership in swarm robotics, with recent works addressing predictive flocking algorithms, biohybrid platforms, and exoskeleton-assisted motor learning. His studies often integrate hardware design with computational models. Advising and Grants information is unavailable in the provided texts, though his active research role since 2008 suggests significant contributions to graduate training and funded projects in robotics.

• Energy Systems Optimization
• Systems Engineering
• Robotics
• +۳ مورد دیگر

Professor Yoshiharu Amano is affiliated with the Faculty of Science and Engineering at Waseda University in the Department of Applied Mechanics and Aerospace Engineering . With a Doctor of Engineering degree from Waseda University, his research spans energy systems, robotics, and environmental engineering. Education: Ph.D. in Mechanical Engineering (Waseda University) Current Position: Full Professor at Waseda University His research interests include: Optimization of energy systems with renewable integration Development of autonomous mobile systems and UAVs GNSS signal processing and multipath mitigation 3D mapping for industrial and environmental applications Control Moment Gyro (CMG) technology for flight stability Standardization of industrial energy management systems (IEC 63376) Recent publications focus on: Macroeconomic modeling of distributed energy resources Geothermal system optimization using deep learning CO2 emission reduction through advanced district cooling systems High-precision 3D piping measurement methods Hydrogen production economics with hybrid energy sources GNSS reliability improvements in urban environments Scientific awards highlight his contributions to: Best energy systems research (ECOS 2015, IJPGC ASME) Thermal engineering excellence (JSME 2005, 2012) Robotics innovations (ROBOMECH Journal 2011) International recognition (SICE 2021)

Sebastian Thiedeمشاهده پروفایل

استاد

• Sustainable Manufacturing
• Smart Industry
• Human-Centered Manufacturing
• +۸ مورد دیگر

Sebastian Thiede is a Full Professor specializing in Manufacturing Systems , with extensive research contributions to Smart Industry , Sustainable Manufacturing , and Human-Centered Production . His work bridges advanced technologies like Machine Learning , Simulation , and Artificial Intelligence with industrial applications, addressing critical challenges in Circular Economy , Energy Efficiency , and Factory Decarbonization . Research focuses on Battery Manufacturing , Edge Computing , and Real-Time Locating Systems (RTLS) . Key methodologies include Digital Twinning , Surrogate Modeling , and Data-Driven Process Optimization . Recent publications highlight trends in Autonomous Sensor Data Analysis (2025), Cyber-Physical Architectures for reconfigurable systems, and Circular Transition Methodologies for manufacturing. His work often integrates Human Factors with Smart Automation , emphasizing environmental and economic impacts.