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Dan NegrutView profile

Professor

• Computer Modeling and Simulation
• Autonomous Vehicles
• High Performance Computing
• +3 more

Professor Dan Negrut is a faculty member in the Department of Mechanical Engineering at the University of Wisconsin–Madison, affiliated with the College of Engineering. He holds the Mead Witter Foundation Chaired Professorship and is a recognized leader in high-performance computing and robotics simulation. Education: PhD in Mechanical Engineering, University of Iowa (1998) BS in Mechanical Engineering, Polytechnic Institute of Bucharest (1992) Research Interests: Computer modeling and simulation of robots and autonomous vehicles High-performance computing and GPU-accelerated algorithms Fluid-solid interaction and granular dynamics Terramechanics and extraterrestrial mobility Autonomous systems and sensor simulation Recent Contributions: His work focuses on advancing physics-based simulation tools like Project Chrono , which supports open-source frameworks for robotics, autonomous vehicles, and granular systems. Recent trends in his publications emphasize sim-to-real gap quantification, lunar rover mobility, and AI-driven digital twins. Awards: NSF CAREER Award (2009) NVIDIA CUDA Fellow (2010) LEED Scholar (2017) ASME Best Paper Awards (2017–2023) Advising & Grants: He advises graduate students in mechanical engineering and computer science, focusing on robotics and autonomous systems. His research is supported by federal grants and industry partnerships. Notable projects include the Synchrono platform for autonomous vehicle simulation and Chrono::Electronics for electro-mechanical systems. Labs & Teams: His team develops Project Chrono , an open-source simulation engine used globally for robotics, automotive, and aerospace applications. Collaborations span academia and industry to address challenges in autonomous systems and space exploration.

Alán Aspuru-GuzikView profile

Professor

• Quantum Computing
• Energy Materials
• AI for Discovery
• +5 more

Alán Aspuru-Guzik is a Professor in the Department of Chemistry at the University of Toronto, with a cross-appointment in the Department of Computer Science. His research focuses on interdisciplinary approaches at the intersection of theoretical chemistry, quantum computing, and artificial intelligence. He leads the development of self-driving laboratories and materials acceleration platforms, combining robotics, AI, and quantum chemistry for accelerated molecular discovery. His mission is to advance technologies like quantum computing, machine learning, and automation to discover new chemicals and materials beneficial to society. The group collaborates across disciplines, including computer science, physics, and applied mathematics. Key research areas include quantum algorithms for molecular simulation, energy materials, and biophysical systems. Notable projects involve creating autonomous laboratories that integrate experimental and computational methods. While no awards are explicitly listed in the provided texts, his work has attracted significant academic and industrial attention. His team operates from the Lash Miller Chemical Laboratories in downtown Toronto.

Sunwook KimView profile

Associate Professor

• Human Factors Engineering
• Ergonomics
• Postural Control
• +3 more

Sunwook Kim is an Associate Professor in the Department of Industrial and Systems Engineering at Virginia Tech, part of the College of Engineering. His work focuses on human factors engineering, ergonomics, and occupational biomechanics with a strong emphasis on exoskeleton technology and neurodiverse collaboration. Kim holds a Ph.D. in Industrial & Systems Engineering from Virginia Tech. His research explores how exoskeletons impact physical demands and safety in construction, manufacturing, and healthcare settings. Notable studies include evaluating passive and powered exoskeletons for tasks like lifting, overhead work, and gait assistance, alongside investigating their effects on postural control, muscle activity, and user acceptance. He also examines neurodiverse team dynamics using advanced methodologies like Hidden Markov Models and physiological signal analysis. Kim's work bridges human performance, assistive technology, and workplace safety, with applications in falls prevention, biomechanical monitoring, and ergonomic intervention design. His interdisciplinary approach integrates machine learning, sensor technologies, and biomechanical modeling to address real-world challenges. His recent articles highlight trends in exoskeleton adoption factors, human-robot collaboration, and motor adaptation during exoskeleton use. Ongoing research includes fall monitoring systems using radar sensing and feature-resonated neural networks, reflecting his commitment to advancing both theoretical and applied human factors engineering.

Emmanuel CecchetView profile

Research Fellow

• Operating Systems
• Distributed Systems
• Dependable Systems
• +6 more

Emmanuel Cecchet is a Senior Research Fellow at the University of Massachusetts Amherst's Department of Computer Science. He is affiliated with multiple research groups including the Laboratory for Advanced System Software (LASS), the Commonwealth Center for Forensics & Society, and the Advanced Networked Systems Research Group. His research focuses on distributed systems, dependability, high availability, databases, and benchmarking. Cecchet has held roles as a postdoctoral researcher at Rice University, a Research Scientist at INRIA, and Chief Architect at Continuent. He has received numerous awards, including the Best Paper Award at IWQoS 2013 and the Best PhD Thesis Award from Institut National Polytechnique de Grenoble (2004). His work includes projects like BenchLab, Open Cloud Testbed (OCT), and contributions to middleware systems such as C-JDBC and Sequoia. Education: PhD in Distributed Systems from Institut National Polytechnique de Grenoble (2001). Research Interests: Operating Systems, Distributed Systems, Dependable Systems, Databases, Virtualization, Networking, and Open Source Software. He also contributes to data forensics and leads the Frog Racing foundation as an amateur car racer. Key Projects: BenchLab for realistic benchmarking, CloudLab for cloud infrastructure research, and WiFiMon for mobility analytics using WiFi sensing. He has served on program committees for Eurosys, SRDS, and other conferences.

Bahar HaghighatView profile

Assistant Professor

• Robotics
• Control Systems
• Artificial Intelligence
• +11 more

Bahar Haghighat is a Tenure Track Assistant Professor in Robotics and Automation at the Faculty of Science and Engineering, University of Groningen. She leads the Distributed Autonomous Intelligent Systems (DAISY) Lab as Principal Investigator and contributes to academic governance as a Member of the Faculty Council. Her professional affiliations include the Royal Netherlands Institute of Engineers (KIVI), the Institute of Electrical and Electronics Engineers (IEEE), and editorial roles with Nature Portfolio Journal Robotics and Springer Nature Journal Autonomous Robots. Her educational background includes: PhD in Robotics, Control, and Intelligent Systems from the Swiss Federal Institute of Technology in Lausanne (EPFL), Switzerland (2018) Master's degree in Electrical Engineering/Digital Electronics from Sharif University of Technology (SUT), Tehran, Iran Bachelor's degree in Electrical Engineering/Physics (double major) from Sharif University of Technology (SUT), Tehran, Iran Dr. Haghighat's research focuses on building novel miniaturized robotic swarms and algorithmic frameworks for sensing, surveying, and inspection applications. Her work spans mechatronics, electronics, embedded systems, embedded artificial intelligence and machine learning, and distributed systems. She envisions developing surface, aquatic, and aerial miniaturized robot swarms and small-scale intelligent devices for basic research and commercial applications including inspection of complex structures, environmental monitoring, space exploration, and search-and-rescue operations. Her recent publications demonstrate a strong focus on swarm robotics, particularly using particle swarm optimization techniques for multi-robot coordination, surface inspection tasks, and spacecraft hull inspection. Her research shows an interdisciplinary approach combining mechatronic design with advanced algorithms for self-assembly and collective decision-making in resource-constrained robotic systems. Her notable scientific achievements include: EPFL's PhD research award of Gilbert Hausmann for the best PhD thesis in mechanical engineering, electricity, and physics (2019) EPFL distinction of excellence for a PhD thesis in Robotics, Control, and Intelligent Systems (2018) Swiss National Science Foundation Postdoc Mobility Fellowship (2019) Swiss National Science Foundation Early Postdoc Mobility Fellowship (2017) Third place in EPFL's "My Thesis in 180 Seconds" competition (2017) EECS Rising Star recognition (2021 at MIT and 2019 at UIUC) Dr. Haghighat has served as Program Co-Chair for The International Symposium on Distributed Autonomous Robotic Systems (DARS) and has held visiting scholar positions at MIT and Harvard University. Her research has received media attention for applications in Mars rover technology and drone swarms for defect detection. She leads the DAISY Lab, which focuses on distributed autonomous intelligent systems for various inspection and monitoring applications.

• Thoracic Surgery
• Robotic Surgery
• Minimally Invasive Surgery
• +7 more

Daniel S. Oh, MD is a Clinical Associate Professor of Surgery (Practitioner) at the Keck School of Medicine of the University of Southern California, specializing in general thoracic surgery with a focus on minimally invasive and robotic techniques. He serves as the medical director at the USC-St. Jude Center for Thoracic and Esophageal Diseases in Fullerton, where he sees patients exclusively. Dr. Oh has extensive experience in robotic-assisted thoracic procedures, with approximately 90 percent of his major operations performed using robotic assistance since 2011. Medical Degree: Not specified in text Surgical Training: USC and Harvard Medical School (Brigham and Women's Hospital) Dr. Oh's research interests center on advancing robotic surgical techniques, particularly in thoracic and esophageal procedures. He actively collaborates with Intuitive Surgical to improve robotic technology, surgical training methods, and develop new procedures that enhance patient outcomes. His work emphasizes a disease-specific rather than technology-specific approach, making him unique among thoracic surgeons as he also performs advanced endoscopic and bronchoscopic procedures. Analysis of Dr. Oh's recent publications reveals a strong focus on objective performance metrics in robotic surgery, surgical education methodologies, and optimizing robotic-assisted thoracic procedures. His research spans both clinical outcomes and technological innovations, with particular attention to quantifying surgical skill, workflow efficiency, and the learning curve associated with robotic techniques. The publications demonstrate a consistent trajectory toward establishing evidence-based standards for robotic surgical training and performance assessment. Dr. Oh is a strong advocate for multidisciplinary care, working closely with colleagues in gastroenterology, pulmonology, medical oncology, radiation oncology, radiology, and pathology to provide comprehensive, patient-tailored treatment. His clinical philosophy emphasizes a team-based approach to achieve optimal outcomes for patients with complex thoracic conditions.

Vaggelis GiannikasView profile

Professor

• Supply Chain Management
• Logistics
• Operations Management
• +5 more

Vaggelis Giannikas is a Professor of Management Information, Decisions & Operations at the University of Bath, where he also serves as Director of the Centre for Smart Warehousing and Logistics Systems and Director of Studies for the MSc in Operations, Logistics, and Supply Chain Management. His research focuses on the adoption and evaluation of emerging technologies in supply chain and logistics operations, with particular emphasis on digitalization, robotics, and automation in manufacturing and warehouse environments. Giannikas holds a PhD in Operations Management and Technology from the University of Cambridge (2010–2014). His work aligns with UN Sustainable Development Goals, contributing to sustainable urban freight logistics and resilient supply chain practices. He leads multiple projects funded by Innovate UK and the Engineering and Physical Sciences Research Council (EPSRC), including Logidot AI Assistant for Enhanced AI Competency in Logistics and Made Smarter Innovation: People-Led Digitalisation. His research interests span technology implementation challenges, warehouse automation, human-robot collaboration, and dynamic inventory optimization. He actively supervises doctoral students exploring digital technologies in logistics and supply chain management. Key areas of exploration include last-mile delivery efficiency, robotic adoption in SMEs, and stochastic programming for production resilience under disruptions. Giannikas collaborates widely with industry partners, focusing on practical applications such as AMR-assisted picking systems, urban micro-fulfillment centers, and dark store operations. His work bridges academic research with real-world logistics challenges, emphasizing both technological innovation and human-centric design in digital transformation initiatives.

• Robotics
• Control Systems
• Sensor Technology
• +3 more

Kartik Ariyur is a Lecturer in the Department of Mechanical Engineering at Purdue University, based remotely. His research focuses on autonomous systems, control systems, sensor technology, and energy systems. His work spans applications in robotics, navigation, and environmental sustainability. Key projects include improving UAV navigation accuracy, developing LiDAR-based traffic monitoring systems, and optimizing wireless networks through adaptive control techniques. Education details are not explicitly listed, but his publications suggest expertise in control systems, robotics, and interdisciplinary engineering. His research interests emphasize practical applications of advanced control theory in real-world systems, including autonomous vehicles and renewable energy systems. Recent publications highlight contributions to geolocation using celestial and magnetic sensing, multi-object tracking with LiDAR, and adaptive control algorithms for hypersonic vehicles. While no specific awards are listed, his extensive publication record reflects active engagement in cutting-edge engineering research. Advising and grants: No formal advisees are listed, but his research collaborations likely involve graduate students and interdisciplinary teams. His work aligns with initiatives in smart infrastructure, autonomous systems, and sustainable energy. No specific grants are mentioned, but his projects suggest funding from sources like the USDOT Regional University Transportation Center. Research activities include contributions to labs focused on autonomous systems, sensor networks, and control systems engineering. His work often integrates hardware and software solutions for real-world challenges in transportation and environmental monitoring.

AJung MoonView profile

Assistant Professor

• Human-Robot Interaction
• AI Ethics
• Robot Ethics
• +4 more

AJung Moon is an Assistant Professor in the Department of Electrical & Computer Engineering at McGill University, Canada. She directs the McGill Responsible Autonomy & Intelligent System Ethics (RAISE) Lab, an interdisciplinary group exploring ethical and societal implications of AI/robotics. Her affiliations include the McGill Centre for Intelligent Machines, Mila, and the Bensadoun School of Retail Management (Faculty of Management). She holds roles in global tech-policy initiatives like the IEEE Global Initiative and the International Panel on Autonomous Weapons Regulation (IPRAW). Her research focuses on human-robot interaction, AI ethics, and governance of autonomous systems. Key interests include ethical design practices, nonverbal communication in HRI, and translating ethics principles into technical workflows. She advocates for inclusive policy design through initiatives like the Open Roboethics Institute. Her recent work emphasizes systemic risk analysis for AI systems, comparative evaluations of ethics frameworks, and sociotechnical harm reduction strategies. Publications address topics ranging from ADAS liability to hesitation gestures in robot collaboration. Moon's lab actively bridges engineering and social science perspectives to advance responsible AI development. Her advisory roles include the UN Digital Cooperation Panel and Canada’s AI Advisory Council (2019-2021). She has pioneered participatory policy frameworks and demonstrated how safety engineering principles can improve AI system accountability.

Chew Ek PengView profile

Associate Professor

• Port Logistics
• Maritime Transportation
• Simulation Optimization
• +3 more

Chew Ek Peng is an Associate Professor and Deputy Head at the Institute of Operations Research and Analytics (IORA), part of the National University of Singapore’s Smart Nation Research Cluster. His research focuses on optimizing port logistics, maritime transportation systems, and inventory management through advanced simulation techniques and data-driven methodologies. His work spans critical areas such as automated port operations, simulation-optimization frameworks, and stochastic systems analysis. Notably, he develops solutions for challenges like AGV scheduling, container relocation problems, and intermodal terminal design. His research integrates machine learning (e.g., hybrid neural networks) with traditional operations research methods. Recent publications highlight contributions to electric vehicle sustainability in carsharing systems, multi-agent reinforcement learning for AGV recharging, and facility location under random utility models. His work emphasizes practical applications in smart logistics, disaster response optimization, and supply chain resilience. Chew Ek Peng collaborates on projects like digital twin validation frameworks and modular simulation pipelines for residential energy modeling. His research has been applied to real-world scenarios such as Singapore’s construction demand forecasting and pandemic impact analyses using modified SEIR models.

Susan FingerView profile

Professor

• Engineering Education
• Collaborative Learning
• Design Theory and Methodology
• +3 more

Susan Finger is a Professor of Civil and Environmental Engineering at Carnegie Mellon University (CMU), affiliated with Carnegie Mellon Architecture and the Integrative Design, Arts and Technology Network (IDeATe). She serves as Associate Dean for IDeATe and holds affiliations with the Robotics Institute, Mechanical Engineering, and the Institute for Complex Engineered Systems (ICES). Her research explores collaborative learning dynamics in engineering education, focusing on how social interactions influence project outcomes and design processes. Education: B.A. Astronomy (University of Pennsylvania), M.A. Operations Research (University of Pennsylvania), Ph.D. Electric Power Systems (MIT) Professional Roles: Former NSF Program Director, Co-Founder/Editor-in-Chief of Research in Engineering Design Research interests span design representation, integration of design/manufacturing, and computer-supported cooperative learning. Key contributions include frameworks for analyzing team collaboration through document/message exchanges and advocating for technology/culture intersections in education. Publications reflect a focus on engineering pedagogy and design theory, with recent work addressing STEM education initiatives and assessment methodologies for collaborative learning environments.

• Robotics
• Autonomous Systems
• Data Fusion
• +7 more

Hugh Durrant-Whyte is a Professor at the University of Sydney and Director of the Centre for Translational Data Science. He holds a BSc (Eng) from the University of London, an MSE, and a PhD from the University of Pennsylvania. Previously, he served as CEO of National ICT Australia (NICTA) and Director of the Australian Centre for Field Robotics (ACFR). His research focuses on robotics, autonomous systems, and data fusion, with over 350 publications and four successful startups. Education: BSc (Eng) in Engineering, University of London MSE in Robotics, University of Pennsylvania PhD in Robotics, University of Pennsylvania Affiliations: Director, Centre for Translational Data Science Former CEO, NICTA (2010-2014) Former Director, ACFR (1995-2010) His research interests span robotics, autonomous systems, and sensor networks. Notable contributions include foundational work on SLAM (Simultaneous Localization and Mapping) and decentralized data fusion. He has pioneered applications in mining automation, autonomous vehicles, and environmental modeling. His work emphasizes practical real-world systems, with projects like autonomous straddle carriers for container terminals and terrain mapping for mining operations. Awards & Honors: NSW Scientist of the Year (2010) Fellow of the Royal Society (FRS), Australian Academy of Science (FAA), and IEEE (FIEEE) Recipient of multiple IEEE Best Paper awards Grants & Labs: Leadership in securing multi-million-dollar grants for robotics and data science initiatives Centre for Translational Data Science: Focuses on translating data science into real-world impact He advises on numerous government and industry projects, bridging academic research with industrial applications. His research teams have developed influential algorithms for autonomous navigation and multi-agent systems.

Angel OteroView profile

Assistant Professor

• Artificial Intelligence in Financial/IT Audits
• Robotic Process Automation (RPA)
• Information Systems Auditing
• +3 more

Angel Otero is an Assistant Professor and Program Chair for Accounting and Finance Online Programs at the Nathan M. Bisk College of Business , Florida Institute of Technology. With over 20 years of industry experience including a 10+ year tenure at Deloitte & Touche as Senior Manager, he bridges academic research with practical expertise in public accounting, financial auditing, IT consulting , and information systems auditing . Ph.D. in Information Systems (Nova Southeastern University) M.S. in Software Engineering (Florida Tech) B.S. in Accounting (Pennsylvania State University) His research focuses on artificial intelligence (AI) and robotic process automation (RPA) in audit contexts, information systems/technology auditing , and information security audits . Publications analyze AI's impact on financial audits, blockchain implementation frameworks, and fuzzy logic-based security control assessment models. Recent work explores AI integration in accounting departments, RPA applications in financial statement audits, and cybersecurity frameworks for financial institutions. Key methodological approaches include grey systems theory , fuzzy logic evaluation , and multi-criteria analysis for IT control optimization.

• Management Accounting
• Organizational Behavior
• Information Systems
• +4 more

Sander van Triest is a researcher associated with the Faculty of Economics and Business at the University of Amsterdam. His work intersects Management Accounting , Organizational Behavior , and Information Systems , focusing on performance evaluation, control mechanisms, and employee dynamics in both public and private sectors. Education: Not explicitly detailed in the provided text. His research explores how subjective performance information , Robotic Process Automation (RPA) , and decentralization influence managerial decisions and organizational outcomes. His recent work (2023–2025) emphasizes remote work policies, enabling controls, and innovation in professional services. From 2023 to 2025, his publications highlight trends in employee autonomy , digital transformation , and management control systems . Earlier works (2000–2009) address cost structures, customer profitability, and accounting standards, with a focus on B2B contexts and cross-cultural management. Despite his extensive contributions, no scientific awards or honors are mentioned in the provided text. His academic collaborations and mentorship roles remain unspecified.

António Palma Dos ReisView profile

Professor

• Digital Transformation
• Information Systems
• Robotic Process Automation (RPA)
• +7 more

António Palma Dos Reis is a Professor at the ISEG School of Economics and Management at the University of Lisbon, specializing in Management Science and Information Systems. He holds a PhD in Management Science from the University of Wisconsin-Milwaukee (1996), along with MS (1993) and BS (1989) degrees in Management and Information Systems. His professional roles include leadership positions such as Dean and President of the ADVANCE research unit. His research focuses on digital transformation, robotic process automation (RPA), blockchain applications, and technology adoption in organizations. Notable studies include analyzing RPA's value for enterprises and blockchain's role in online gambling. He has advised over 30 master’s students on topics like cloud security, RPA implementation, and AI-driven decision systems. Reis has served on the scientific council of the Open University of Lisbon and contributed to institutional governance as a member of ISEG’s Senate. His work bridges theoretical frameworks (e.g., TOE model) with practical applications in procurement systems, mobile business, and financial decision-making. His publications span 30+ years, covering strategic performance analysis, e-procurement systems, and collaborative decision-making. Current research emphasizes organizational ambidexterity and post-AI societal impacts, reflecting a dual focus on technological innovation and managerial strategy.