Find Academic Supervisors

Vivek BoominathanView profile

Research Professor

• Computational imaging
• Computer vision
• Machine learning
• +7 more

Vivek Boominathan is an Assistant Research Professor in the Department of Electrical and Computer Engineering at Rice University. He is affiliated with the GLEE lab (Geometry, Light, & Imaging lab). His research focuses on computational imaging, combining computer vision, machine learning, applied optics, and nanofabrication to develop innovative imaging systems for applications such as robotics, medical sensing, and virtual/augmented reality. He has contributed to projects like PhlatCam (a lensless camera) and NeuWS (neural wavefront shaping). His work bridges optics, algorithms, and materials science to overcome traditional limitations in imaging systems. Boominathan's research interests include lensless imaging, optical meta-devices, turbulence mitigation, and bio-inspired imaging systems. He has developed systems like Foveated thermal imaging prototypes and real-time lensless microscopes. His lab emphasizes interdisciplinary approaches, integrating hardware design with machine learning. Key projects include: NeuWS: Neural wavefront shaping for imaging through scattering media CoIR: Compressive implicit radar for sensing applications FlatCam and PhlatCam: Ultra-thin lensless imaging devices Bioluminescence imaging in marine species His work has been published in top venues like Science Advances, Optica, and IEEE TPAMI. He collaborates with institutions like NASA JPL and industry partners on applied imaging solutions. Current research trends emphasize sensor-algorithm co-design and high-speed imaging systems for AR/VR applications. Boominathan holds a PhD in Electrical Engineering and has extensive postdoctoral experience in computational imaging. He advises projects in the GLEE lab and mentors students in hardware-software co-design for imaging systems. His lab focuses on translating theoretical innovations into practical devices with commercial potential.

Cynthia SungView profile

Associate Professor

• Computational Robotics
• Origami Robotics
• Soft Robotics
• +2 more

Cynthia Sung is an Associate Professor in the Mechanical Engineering and Applied Mechanics department at the University of Pennsylvania's School of Engineering and Applied Science, with secondary appointments in Computer and Information Science and Electrical and Systems Engineering. She directs the Sung Robotics Lab, focusing on computational methods for robot design, origami robotics, planning for distributed systems, and fabrication of reconfigurable systems. Her lab is funded by NSF, ONR, ARO, NASA, and Penn Health-Tech. Her research spans four key areas: Computational co-design integrating mechanical, electronic, and software components Soft/origami robotics leveraging compliance for adaptable systems Distributed planning for multi-robot coordination Novel fabrication techniques for deployable structures Publications show consistent focus on robotic mechanisms with recent trends in magnetic origami reconfiguration (2025), underwater jet coordination (2025), educational robotics kits (2025), and tunable-stiffness actuators (2024). Article keywords predominantly fall in Robotics, Material Science, and Control Systems. Awards & Recognition ONR Young Investigator Award (2023) NSF CAREER Award (2019) Johnson & Johnson Women in STEM2D Scholars Award (2020) Popular Mechanics Breakthrough Award (2017) Research Teams & Advising Leads the GRASP Lab-affiliated Sung Robotics group. Current doctoral students include Zhiyuan Yang (jet propulsion), Daniel Feshbach (kinematic design), and Gabriel Unger (reconfigurable structures). Recent graduates include Yipeng Zhang (MSc, SALP robotics) and Christopher Kim (PhD, self-sensing actuators).

Siqi MaView profile

Senior Lecturer

• Automated Vulnerability Detection and Repair
• Mobile Security
• IoT Security
• +4 more

Dr. Siqi Ma is a Senior Lecturer at the UNSW Institute for Cyber Security (IFCYBER) within the School of Systems & Computing at the University of New South Wales (UNSW). He previously served as a Lecturer at the University of Queensland's School of Information Technology and Electrical Engineering (ITEE). He holds a Ph.D. in Information Systems from Singapore Management University (2018) and was a Postdoctoral Research Fellow at Data61, CSIRO. He also visited Carnegie Mellon University (CMU) in 2015. Current Role: Senior Lecturer, UNSW Institute for Cyber Security Former Role: Lecturer, University of Queensland Education: Ph.D. (Singapore Management University), Postdoc (Data61, CSIRO) His research spans automated vulnerability detection, mobile security, IoT security, network authentication, and graph-based adversarial robustness. Recent work focuses on drone configuration bugs, Android malware analysis via GNNs, federated learning privacy, and credential leakage in open-source projects. Key trends in his 2024-2025 publications include automated security analysis for embedded systems, deepfake detection in multimedia, and privacy-preserving mechanisms for distributed networks. He collaborates with institutions like Purdue University, Singapore Management University, and CSIRO Data61.

Karthik DantuView profile

Associate Professor

• Mobile Sensor Networks
• Robot Networks
• Networked Embedded Systems
• +8 more

Karthik Dantu is an Associate Professor in the Department of Computer Science and Engineering at the University at Buffalo, State University of New York, within the School of Engineering and Applied Sciences. His research focuses on mobile sensor networks, robot networks, networked embedded systems, mobile computing, wireless networks, and embedded operating systems. He leads the Distributed Robotics and Networked Embedded Sensing (DRONES) Lab and has received significant funding including an NSF CAREER Award. Dr. Dantu's educational background includes: PhD in Computer Science from University of Southern California (2009) BE in Computer Science from Sri Jayachamarajendra College of Engineering (1999) His research interests center on algorithmic and systems challenges in Edge Computing Systems, with particular focus on enabling seamless vision sensing in cloud-edge environments. Dantu's work bridges mobile systems and robotics, developing novel approaches for UAV software, visual SLAM, and distributed sensing. His research addresses critical challenges in resource-constrained environments, security, and real-time performance for mobile and robotic systems, with emphasis on practical implementations that solve real-world problems in autonomous systems. Dr. Dantu's publication record shows a strong trajectory in mobile systems and robotics research, with increasing focus on edge computing applications for visual sensing. His recent work demonstrates expertise in adapting visual SLAM to edge environments, securing mobile systems through technologies like Rushmore, and developing novel approaches for UAV software reliability and depth sensing. The research spans theoretical algorithms and practical system implementations, with particular strength in bringing academic research to practical applications in robotics and mobile computing. Dr. Dantu has received several scientific honors: NSF CAREER Award on Enabling Seamless Vision Sensing in Cloud-Edge Systems Outstanding service award from the Office of International Services NSF Travel Grant for SenSys 2005 Conference Travel Grant for SIGCOMM 2002 As an advisor, Dr. Dantu has mentored numerous PhD students to completion, with graduates now working at companies like Samsung Research and Zoox Inc., or continuing academic careers as Assistant Professors. His research is supported by substantial grants including a DARPA OFFSET Sprint 4 award ($470k), an NSF CAREER award ($550k), and multiple NSF collaborative grants totaling over $1.5 million. He serves on numerous conference committees including Mobicom, MobiSys, and ICRA, demonstrating leadership in the mobile systems and robotics research communities. Dr. Dantu leads the Distributed Robotics and Networked Embedded Sensing (DRONES) Lab at UB, which focuses on developing algorithms and systems for mobile sensor networks, robot networks, and embedded sensing applications. The lab's work spans theoretical foundations to practical implementations, with particular expertise in UAV systems, visual SLAM, and edge computing for robotics, maintaining strong collaborations with industry partners and other academic institutions to advance the state of the art in mobile and robotic systems.

Xin PengView profile

Professor

• Software Analytics
• Intelligent Software Development
• Microservice
• +4 more

Xin Peng is a Professor and Deputy Dean at the School of Computer Science, Fudan University, China. He leads the CodeWisdom research team focusing on intelligent software engineering techniques for development, maintenance, and operation of software systems. His educational background includes a PhD in Computer Science (2001-2006) and Bachelor's degree in Computer Science (1997-2001), both from Fudan University. He progressed through the academic ranks from Assistant Professor (2006-2010) to Associate Professor (2010-2015) and finally to Professor (2015-present). Professor Peng's research interests span Software Analytics, Intelligent Software Development, Microservice systems, and AIOps. His work leverages AI technologies including deep learning and knowledge graphs to develop intelligent software engineering techniques. A significant portion of his recent work focuses on applying Large Language Models to various software engineering tasks, including vulnerability detection, API usage analysis, and test automation. His publication record shows a clear trend toward increasingly sophisticated applications of AI in software engineering, with recent work heavily featuring LLMs for tasks ranging from vulnerability patch porting to resource leak detection. The research spans multiple domains including microservice systems, automotive software, and Web of Things security. Best Paper Award of ICSM 2011 ACM SIGSOFT Distinguished Paper Award of ASE 2018 and 2021 IEEE TCSE Distinguished Paper Award of ICSME 2018, 2019, and 2020 IEEE Transactions on Software Engineering Best Paper award for 2018 Professor Peng serves in numerous leadership roles including Deputy Director of CCF Technical Committee on Software Engineering, Co-Editor-in-Chief of Journal of Software: Evolution and Process, and Associate Editor for ACM Transactions on Software Engineering and Methodology. He has been actively involved in program committees for major software engineering conferences including ICSE, ASE, ESEC/FSE, and ICSME. He leads the CodeWisdom research team at Fudan University, which has developed several benchmark systems including TrainTicket for microservice research. The team's work bridges academic research with industrial applications, particularly in microservice systems analysis and intelligent software development tools.

Martin Nordal PetersenView profile

Associate Professor

• Internet of Things
• Optical Networking
• Wireless Communication
• +3 more

Martin Nordal Petersen is an Associate Professor at the Department of Electrical and Photonics Engineering , Technical University of Denmark (DTU) . His work spans Internet of Things (IoT) , optical networking , and wireless communication systems, with notable contributions to LoRa , NB-IoT , and LPWAN technologies. He actively supervises PhD projects on topics such as machine learning in IoT edge devices , secure 5G communication , and smart community architectures . Active projects (2024–2027): Machine Learning in IoT Edge Devices , Deterministic and Secure 5G Communication Finished projects (2021–2024; 2018–2021; 2015–2018): Reliable M2M/IoT Communication , Smart Communities , IoT 100% , Network Slicing His research explores: IoT Reliability : Multi-RAT communication, backup systems, and signal propagation Optical Networks : Alien wavelength integration, SDN control, and network emulation platforms Wireless Innovation : GPS-free geolocation, maritime NB-IoT use cases, and multimode fiber distribution Current collaborations emphasize cross-disciplinary applications of IoT in healthcare , industrial ergonomics , and smart environments .

Vikram IyerView profile

Assistant Professor

• Robotics
• Ubiquitous Computing
• Sensing & Embedded Systems
• +7 more

Vikram Iyer is an Assistant Professor at the Paul G. Allen School of Computer Science and Engineering and holds an Adjunct Appointment in Mechanical Engineering at the University of Washington. He co-directs the CS for Environment Initiative , focusing on interdisciplinary solutions that bridge computing, biology, and physical systems for environmental sustainability. Education : Ph.D. in Electrical & Computer Engineering (University of Washington), B.S. in Electrical Engineering and Computer Sciences (UC Berkeley) Research Interests revolve around bio-inspired wireless systems , environmentally sustainable electronics , and miniaturized autonomous robotics . His work includes: Biodegradable circuit boards Battery-free wireless sensors Insect-scale vision systems Wind-dispersed environmental monitors AI tools for sustainable design Article Trends highlight contributions to green hardware , energy-autonomous robotics , and environmental sensing networks , often integrating machine learning with physical world interaction . Awards include: NSF CAREER Award SIGMOBILE Dissertation Award Marconi Society Paul Baran Young Scholar Best Paper Awards (SIGCOMM 2016, Sensys 2018) Google/Amazon Research Awards Students advised include Kyle Johnson (NSF Fellow), Vicente Arroyos (GEM Fellow), and Qiuyue Xue (co-advised with Shwetak Patel). His lab collaborates with the Networks & Mobile Systems Lab and Urban Innovation Initiative .

Scott L. NyklView profile

Professor

• Computer Vision
• Real Time 3D Computer Graphics
• Sensor Fusion
• +12 more

Dr. Scott L. Nykl is a Professor in the Department of Computer Science at the Air Force Institute of Technology (AFIT), part of the Graduate School of Engineering & Management. He is a leading researcher in computer vision, real-time 3D graphics, and autonomous aerial systems, with a focus on automated aerial refueling and navigation in GPS-denied environments. Education: Ph.D. in Computer Science, Ohio University (2008–2013), Summa Cum Laude, GPA: 4.0/4.0 M.S. in Computer Science, Ohio University (2011–2012), Summa Cum Laude, GPA: 4.0/4.0 B.S. in Software Engineering, University of Wisconsin–Platteville (2002–2006), Summa Cum Laude, GPA: 3.94/4.0 Dr. Nykl's research interests include computer vision, sensor fusion, interactive virtual worlds, and real-time 3D graphics, with applications in aerospace and defense. His work bridges simulation and real-world deployment, particularly in autonomous aerial refueling using stereo and monocular vision. He has pioneered techniques in pose estimation, occlusion mitigation, and sim-to-real transfer learning. His recent publications and projects show a strong trend toward robust, vision-based navigation systems for unmanned and manned aircraft, with emphasis on reliability, accuracy, and real-time performance. His work frequently appears in IEEE, AIAA, and ION venues, reflecting its high technical and operational relevance. Scientific Awards and Recognitions: 2024 Harold Brown Award – Highest U.S. Air Force scientific honor 2024 General Bernard A. Schreiver Award 2025 AETC Airmen of the Year Multiple Air Force Outstanding Scientist/Engineer Awards (2017–2023) Best Paper Award, ACM SIGGRAPH i3D 2013 Forbes' The Greatest Young Inventors in America (2012) NSF GK-12 Fellow (2006) Dr. Nykl has advised numerous graduate students and collaborated extensively on projects involving automated aerial refueling, 3D reconstruction, and cyber education. He has secured significant research funding, including a $100,000 Ohio Third Frontier grant. His work has led to multiple patents and technology transfers. He leads research integrating virtual worlds, digital twins, and augmented reality for both research and pedagogy. Laboratories and Research Teams: His work is conducted within AFIT’s research ecosystem, involving collaborations with the Air Force Research Laboratory (AFRL), Boeing, and academic partners. He leads projects under the Aerial Refueling Systems Advisory Group (ARSAG) and presents regularly at ION, AIAA, and IEEE conferences.

• Power Electronic Converters
• Embedded Systems
• Analog and Mixed-Signal Circuit Design
• +5 more

Dr. Anwar Ali is a Lecturer in the Department of Electronic and Electrical Engineering at Swansea University's Bay Campus, affiliated with the School of Aerospace, Civil, Electrical and Mechanical Engineering. He holds an M.S. in Electronic Engineering (2010) and a Ph.D. in Electronic and Communication Engineering (2014) from Politecnico di Torino, Italy. His research focuses on: Power electronic converters and conditioning systems Embedded systems for aerospace applications Analog/mixed-signal circuit design Satellite technologies including power management Attitude determination and control systems Thermal modeling of aerospace systems Dr. Ali has authored over 50 publications with recent works concentrated in satellite power systems, thermal analysis of spacecraft, machine learning applications in healthcare/robotics, and energy harvesting techniques. His research demonstrates consistent innovation in small satellite technologies and cross-disciplinary applications of electrical engineering principles. He currently supervises PhD projects on: Wireless power transfer for implantable medical devices Integrated power and attitude control optimization for small spacecraft and teaches modules including Analogue Design, Software Engineering, Embedded System Design, and Integrated Circuit Design.

Emil LupuView profile

Professor

• Computer System Security
• Artificial Intelligence and Image Processing
• Computer Communications Networks
• +5 more

Professor Emil Lupu is a Professor of Computer Systems at the Department of Computing , Imperial College London. He leads the Resilient Information Systems Security Group and serves as Co-Director of the National Research Institute in Trustworthy Inter-Connected Cyber-Physical Systems (RITICS) . As a Security Science Fellow at Imperial’s Institute for Security Science and Technology, his work bridges academic research with real-world security challenges. Education: PhD in Computing, Imperial College London (1994–1998) His research focuses on security and resilience of cyber-physical systems (CPS) , with emphasis on defending against data spoofing attacks , adversarial machine learning , and IoT vulnerabilities . He pioneered the Ponder policy systems for access control and the Self-Managed Cell framework for autonomic computing, and developed Bayesian Attack Graphs for scalable risk assessment in CPS. Recent publications highlight trends in adversarial robustness (2025–2022), including LIDAR spoofing defense for autonomous vehicles, LLM security , and attack graph analysis for IoT. His work explores the intersection of safety and security , applying model-checking to identify adversarial threats in train control, microgrids, and aviation systems. Scientific Awards: Security Science Fellowship, Imperial College London (2011–present) As co-founder of the PETRAS National Centre of Excellence in IoT Cybersecurity (2016–2021), he advanced security methodologies for interconnected systems. His collaborations with institutions like the Cyber Security Body of Knowledge (CyBoK) demonstrate his leadership in shaping cybersecurity research standards. Current projects include the RITICS Institute , focusing on trustworthy cyber-physical systems, and exploring generative AI for security poisoning with practical defenses against adversarial ML.

George VosselmanView profile

Professor

• Photogrammetry
• Remote Sensing
• Laser Scanning
• +7 more

George Vosselman is a Full Professor at the University of Twente, Faculty of Geo-Information Science and Earth Observation (ITC), specializing in Geo-Information Extraction with Sensor Systems. Educated with honours at Delft University of Technology (1986) and PhD in Photogrammetry from Rheinische Friedrich Wilhelms University of Bonn (1991), he has held academic roles at the University of Stuttgart, University of Washington, and Delft University of Technology (1993–2004). Since 2004, he has been a key figure at ITC, serving as department head (2012–2018, 2023–). Education: Delft University of Technology (BSc with honours, 1986), Rheinische Friedrich Wilhelms University of Bonn (PhD with honours, 1991) His research focuses on leveraging sensor technology advancements for large-scale geo-information production. Key expertise includes quality analysis of laser altimetry data, point cloud segmentation/classification, 3D building/road modeling, and model-driven imagery analysis. He has published over 220 papers and co-edited the textbook Airborne and Terrestrial Laser Scanning (2010). Recent work integrates deep learning with geospatial data, addressing semantic segmentation, visual question answering, and drone-based mapping. Recent publications (2025–2023) highlight trends in deep learning for remote sensing , including multimodal question answering benchmarks (HRVQA), vectorized building extraction (RoIPoly), latent diffusion for road modeling (LDPoly), and drone obstacle avoidance systems. His work bridges photogrammetry , computer vision , and robotic mapping , with applications in urban planning, disaster management, and informal settlement monitoring. Scientific Awards : Hansa Luftbild (1993), ISPRS Otto von Gruber (2000), Schwidefsky Medal (2012), Karl Kraus Medal (2012), ASPRS Fairchild Award (2015), ISPRS Fellow (2020) As an educator, Vosselman has taught photogrammetry, remote sensing, and laser scanning at Delft University of Technology and globally. He chaired the ITC Examination Board (2015–2023) and modernized geo-information education in Asia/Africa. His software for point cloud processing is commercialized in Europe, and he currently leads ISPRS working groups on point cloud methodologies. Labs/teams include the Earth Observation Science Chair Group at ITC, collaborating on UAV-based datasets (UAVid, UAVPal) and indoor laser scanning systems. Recent activities (2025) involve invited talks on pulse matching limitations in laser scanning and deep learning for point cloud classification.

Martin HenzView profile

Associate Professor

• Programming Languages
• Software Engineering
• Artificial Intelligence
• +8 more

Martin Henz is an Associate Professor at the National University of Singapore , affiliated with the School of Computing and its Department of Computer Science . His academic journey includes an M.Sc. in Computer Science from Stony Brook University (1993) and a Dr.rer.nat. in Computer Science from Saarland University (1997). He has also worked as a Research Scientist at the German Research Centre for Artificial Intelligence. Research Focus : Scalable Experiential Learning, Systems for Teaching/Learning, AI in Education, Programming Languages, Algorithms, and Constraint Programming. Key Projects : Source Academy (immersive programming environment), Deep Teaching (LMS enhancements), and NUS Seafarers (maritime experiential learning). Publications span education technology, programming languages, and sustainable engineering, with recent works focusing on JavaScript-based pedagogy, automated question generation, and electric vehicle conversions. He supervised Rahul Singhal 's PhD, leading to the educational startup Cerebry, and co-founded Workforce Optimizer Pte Ltd with Alan Sevugan. Awards : NUS Annual Digital Education Award (2021) NUS Annual Teaching Excellence Award (2016/17) Fulbright Scholarship (1990) Startup @ Singapore Champion (2001)

Bret WindomView profile

Associate Professor

• Alternative Fuels
• Combustion Dynamics
• Laser Diagnostics
• +3 more

Bret Windom is Associate Professor of Mechanical Engineering at Colorado State University's Walter Scott, Jr. College of Engineering, specializing in combustion science and alternative fuels. He directs research on physiochemical fuel characterization, laser diagnostics, and energy conversion systems. Research investigates combustion dynamics of sustainable fuels, propulsion systems, and emission reduction strategies. Recent projects include oxymethylene ethers as low-sooting biofuels, hydrogen production systems, and hybrid SOFC-engine power generation. Funded by DOE, ONR, and Caterpillar, his work advances low-carbon energy technologies. Recipient of the SAE Teetor Educator Award (2018) and multiple research fellowships. Leads the Chemical Energy Conversion Laboratory, mentoring graduate students in combustion research. Current industrial collaborations focus on marine engine decarbonization and lubricant ignition behavior. Recent Publications demonstrate strong focus on sustainable fuels (hydrogen, LPG, OMEs), advanced diagnostics (laser spectroscopy, NMR), and energy system integration (SOFC hybrids, scramjets). Article keywords frequently include combustion optimization, emissions reduction, and alternative fuel characterization.

Cagdas OnalView profile

Associate Professor

• Soft Robotics
• Printable Robotics
• Bio-inspiration
• +3 more

Cagdas Onal is an Associate Professor of Robotics Engineering at Worcester Polytechnic Institute (WPI). He holds a BS and MS from Sabanci University (2003, 2005) and a PhD in Robotics from Carnegie Mellon University (2009). His research focuses on soft robotics, bio-inspired systems, and control theory , emphasizing the development of flexible robotic components for healthcare, industry, and sustainable applications. He leads the Soft Robotics Lab and the Future of Robots in the Workplace (FORW-RD) initiative, advancing human-centric robotics solutions. Research interests include designing bio-inspired soft robots (e.g., origami-inspired snake robots), developing modular actuation systems with embedded sensors, and exploring applications in medical devices and assistive technology. His work aligns with UN Sustainable Development Goals, particularly in healthcare access (SDG 3), quality education (SDG 4), and innovation (SDG 9). Recent projects include origami-based robotic arms for wheelchair users , self-contained underwater robots, and haptic interfaces for teleoperation. His lab collaborates on国家级 grants like the NSF-funded NRT Program and has secured patents for actuator designs (e.g., Hydro Muscle). Labs/Teams: Soft Robotics Lab, FORW-RD, NRT Program. Notable media coverage includes Worcester Telegram & Gazette and Spectrum News for innovations in human-friendly robotics.

Arnab NandiView profile

Professor

• Database Systems
• Human-Computer Interaction
• Human-in-the-Loop Data Analytics
• +5 more

Arnab Nandi is a Professor of Computer Science and Engineering at The Ohio State University, with a courtesy appointment in Biomedical Informatics. He holds leadership roles including Steering Committee Member for the Human-in-the-Loop Data Analytics (HILDA) Workshop and has served as Workshops co-chair for SIGMOD 2025-26 and Demonstrations co-chair for SIGMOD 2024. His research focuses on bridging human interaction and data infrastructure, spanning database systems, human-in-the-loop data analytics, and next-generation query interfaces. Nandi's work emphasizes interactive data exploration through projects like DICE (Distributed Interactive Cube Exploration), GestureDB (Querying Beyond Keyboards), and Omni (Multimodal Data Exploration). His recent research explores integrating LLMs into database education, augmented reality interfaces for data analytics, and multimodal approaches to video querying. Nandi has received numerous honors including the NSF CAREER Award, Google Faculty Research Award, IEEE TCDE Early Career Award, and the University's Alumni Award for Distinguished Teaching. He was also named to Columbus Business First's '40 under 40' and became an ACM Distinguished Member in 2024. As an educator, he teaches courses including CSE 3241 (Introduction to Database Systems), CSE 5242 (Advanced Database Systems), and CSE 5251 (Introduction to Software Startups). His educational innovations include DBTutor, which integrates LLMs into database systems education. At Ohio State, Nandi co-founded the OHI/O Program, which fosters tech culture through hackathons, and The STEAM Factory, an interdisciplinary research collaboration network. Prior to academia, he was founder and CEO of Mobikit, a connected vehicles data analytics startup acquired by Azuga Inc. (a Bridgestone company). His research has been supported by the NSF and industry partnerships, with applications spanning precision agriculture (CropFusion), clinical data pipelines (ICARUS), and interactive visualization systems (Perceptvis).