Find Academic Supervisors

• Collaborative Robotics
• Manufacturing Systems
• Human-Robot Interaction
• +5 more

Omkar Salunkhe is a Postdoc researcher at Chalmers University of Technology, working within the Department of Industrial and Materials Science, specifically in the Production Systems division. His research focuses on advanced manufacturing systems, human-robot collaboration, and Industry 4.0 technologies, with particular emphasis on practical applications in wire harness assembly and final assembly processes. Salunkhe's research interests span multiple areas of modern manufacturing and automation. He specializes in collaborative robotics applications, particularly in wire harness assembly processes. His work explores task allocation between humans and robots, cost-benefit analysis of collaborative workstations, and the integration of computer vision systems in manufacturing environments. He also investigates operational flexibility in final assembly using Industry 4.0 enabling technologies, with applications in automotive and other manufacturing sectors. His research bridges theoretical concepts with practical industrial implementation, focusing on human-centered approaches to automation that maintain economic viability. Analysis of Salunkhe's publication record reveals a strong trajectory from foundational work on operational flexibility (2018-2020) to increasingly specialized research on collaborative robotics in wire harness assembly (2022-2024). His work demonstrates a clear evolution from general Industry 4.0 applications to targeted solutions for specific manufacturing challenges, with a consistent focus on the human element in automated systems. The 2025 MAXLabs project represents a significant expansion of his research into integrated cyber-physical testbeds for broader manufacturing research. Salunkhe has been actively involved in multiple research projects funded by VINNOVA, the European Commission, and other organizations. These include MAXLabs, EWASS (Empowering Human Workers for Assembly of Wire Harnesses), PLENUM, and Digital work Instructions for cognitive work. His collaborative network includes prominent researchers such as Johan Stahre, Anna Syberfeldt, and David Romero, reflecting strong interdisciplinary and industry-connected research activities.

Aijun SongView profile

Associate Professor

• Underwater Acoustic Communications
• Signal Processing
• Robotics
• +5 more

Dr. Aijun Song is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Alabama College of Engineering. He is affiliated with the Center for Water Quality Research and the Alabama Water Institute. His work bridges engineering, environmental science, and technology, with a focus on developing innovative underwater communication systems and autonomous vehicle technologies for water monitoring applications. Dr. Song's educational background includes: Ph.D. in Electrical and Computer Engineering from University of Delaware M.S. in Electrical and Computer Engineering from Xidian University, Xi'an, China B.S. in Electrical and Computer Engineering from Xidian University, Xi'an, China Dr. Song's research primarily focuses on underwater acoustic communications, signal processing, and autonomous vehicle technologies. His work addresses challenges in underwater wireless communications including channel modeling, equalization techniques, and full-duplex communication systems. He has made significant contributions to the development of underwater sensor networks, acoustic transceivers, and communication protocols for autonomous underwater vehicles. His research has important applications in environmental monitoring, ocean exploration, and water quality assessment. Dr. Song's recent publications demonstrate a strong trend toward practical implementations of underwater communication technologies, with increasing emphasis on reconfigurable intelligent surfaces, energy-efficient systems, and real-world testbed validation. His work spans theoretical development, simulation, and extensive field testing in lake and river environments. The research addresses critical challenges in underwater communication including channel variability, interference cancellation, and long-range transmission. Dr. Song has received notable recognition for his work: NSF CAREER Award from the National Science Foundation (2021) Outstanding Faculty/Staff-Initiated Engagement Effort by the Council on Community-Based Partnerships at the University of Alabama (2019) Outstanding Service Award from the 8th ACM International Conference on Underwater Networks & Systems (2013) Dr. Song actively mentors students and collaborates on interdisciplinary research projects. He serves as co-principal investigator for the USGS FLOW Academy, working with Dr. Lisa Davis and Dr. Steven Burian to provide hands-on water science education. His leadership in the Tuscaloosa MATHCOUNTS program has significantly impacted local STEM education, particularly for underserved populations and female students. Dr. Song's research has been supported by significant funding including an NSF CAREER award and collaborations with the US Geological Survey. Dr. Song leads a research team focused on underwater robotics and wireless communication technologies. His lab develops and tests autonomous underwater vehicles including JaiaBots and EcoMapper systems. The team is advancing underwater swarming technologies to enhance water monitoring capabilities, with an emphasis on creating open-source, low-cost solutions for automated water data collection and rapid flood disaster response. Recent field demonstrations at the Black Warrior River and Lake Tuscaloosa showcase the practical applications of his research.

• High Performance Computing
• HPC Interconnection Networks
• Enterprise Data Centre Networks
• +6 more

Ernst Gunnar Gran is Associate Professor at the Department of Information Security and Communication Technology at the Norwegian University of Science and Technology (NTNU), where he heads the communication technology discipline. He also holds an adjunct research scientist position at Simula Research Laboratory, where he headed the Cloud department until December 2016. His research spans high performance computing (HPC), HPC interconnection networks, enterprise data centre networks, cloud computing, and data-intensive processing in multi-clouds. He serves as the Scientific Leader of Communication Technologies in the RCN-funded infrastructure project eX3 (Experimental Infrastructure for Exploration of Exascale Computing) and has significant experience with both RCN-funded and EU-funded research projects, including the H2020 project Melodic (Multi-cloud Execution-ware for Large-scale Optimised Data-Intensive Computing). Gran received his M.Sc. and Ph.D. degrees in computer science from the Department of Informatics, University of Oslo, in 2007 and 2014, respectively. Both theses focused on different aspects of resource management in high performance interconnection networks. He previously headed the RCN-funded project ERAC (Efficient and Robust Architecture for Big Data Clouds) and led the design, implementation, and deployment of the multi-homed IP-based research testbed NorNet Core. Gran also has several years of experience as a system administrator and scientific programmer. His research interests center on the intersection of high performance computing and networking, with particular focus on anomaly detection in time series data, HPC interconnection networks, network virtualization, and cloud computing infrastructure. His work demonstrates a consistent evolution from fundamental networking research to applied solutions for modern computing challenges, particularly in IoT security and smart home applications. His recent publications show a strong emphasis on developing lightweight, real-time anomaly detection systems using deep learning techniques. Analysis of his publication trends reveals a clear progression from traditional HPC networking research toward time series anomaly detection applications, particularly for IoT systems. His 15 most recent publications show dual focus areas: approximately 60% concentrate on anomaly detection methods for time series data (particularly for IoT applications), while the remaining 40% maintain his foundational work in HPC networking, virtualization, and cloud infrastructure. This evolution demonstrates his ability to adapt core networking expertise to emerging application domains while maintaining technical depth. While no specific scientific awards are mentioned in the provided text, Gran's leadership roles in significant research projects (eX3, Melodic, ERAC) indicate recognition of his research capabilities within the academic and research funding communities. His position as Scientific Leader of Communication Technologies in the RCN-funded eX3 project further demonstrates his standing in the Norwegian research community. Gran's teaching responsibilities include serving as course coordinator for DCSG1006 Data Communication and Networks, DCSG2001 Interconnected Networks and Network Security, and Networks: Administration, Programming and Security. His research leadership extends to significant grant-funded projects, including the RCN-funded eX3 infrastructure project and the EU H2020 Melodic project. His previous leadership of the ERAC project and the NorNet Core research testbed demonstrates sustained ability to secure and manage substantial research funding. His laboratory and team affiliations include the Department of Information Security and Communication Technology at NTNU, where he heads the communication technology discipline, and Simula Research Laboratory, where he maintains an adjunct position. The NorNet Core research testbed, which he led the development of, represents a significant infrastructure contribution to the networking research community. His current work with the eX3 project suggests ongoing involvement in experimental infrastructure for exascale computing exploration.

• Quantum Optical Communications
• Free Space Optical Communications
• Machine Learning Applications
• +3 more

Dmitrii Briantcev is a Researcher at the CONNECT Centre, Trinity College Dublin, working on the IrelandQCI project in Quantum Optical Communications since June 2023. He holds a Bachelor's in Radiophysics from Saint Petersburg State University (2018) and MS/PhD in Electrical and Computer Engineering from KAUST, where his research focused on Machine Learning and Physical Simulations for Free Space Optical (FSO) communication systems. His educational background: Bachelor in Radiophysics, Saint Petersburg State University (2018) MS and PhD in Electrical and Computer Engineering, King Abdullah University of Science and Technology (KAUST) Dmitrii's research spans optical and quantum communications domains. His current IrelandQCI project involves building national quantum communication infrastructure, while prior PhD work developed machine learning models for FSO reliability. His broader interests integrate Cybersecurity, Satellite Communications, and Smart Cities applications in next-generation networks. As part of CONNECT's quantum communications team, he contributes to Ireland's quantum testbed development. No information is available regarding advisory roles, grants, or scientific awards.

• ICT in Logistics
• Cyber-Physical Systems (CPS)
• Engineering Education
• +6 more

Jannicke Baalsrud Hauge is an Associate Professor in Production Logistics at KTH Royal Institute of Technology's Södertälje campus. She holds a PhD in Engineering from the University of Bremen and has extensive experience in research and education spanning over two decades. Current roles include coordinating digital and physical testbeds for logistics in projects like Digilog and CB743 Unilog . Active in EIT Urban Mobility and managing EU/EIT Digital research projects. Responsible for master's programs in Sustainable Production Development and Applied Logistics . Her research focuses on integrating ICT (including CPS ) into logistics and supply chain networks, alongside innovations in engineering education . She leads the BIBA Gaming Lab and contributes to serious gaming applications for industrial systems. She has authored over 250 papers and serves on multiple academic boards. Her teaching includes courses on Lean Production , Logistics in Production , and Digitalisation for Sustainable Production , reflecting her commitment to sustainable and optimized production systems.

Joan CondellView profile

Professor

• Digital Intelligent Technologies
• Imaging Technologies
• Security
• +6 more

Professor Joan Condell is a leading academic at Ulster University , holding the title of Professor of Intelligent Technologies in the School of Computing, Engineering and Intelligent Systems . Her work spans imaging, digital technologies, and wearable systems with applications in security, energy, and healthcare. Education : BSc in Mathematics, Statistics and Computing (Ulster), MSc in Industrial Mathematics (University of Strathclyde), PhD in Mathematics and Theoretical Computing (Ulster). Leadership : Senior Fellow of the Centre for Higher Education Research and Practice, Fellow of the Higher Education Academy, and Core Member of the Computer Science Research Institute. Research Focus : Digital intelligent technologies, imaging, wearables, and commercialisation of academic innovation. She has founded spinout companies and secured over £56M in grants, including EU FP7 funding and current European projects totaling €22.5M. Recognition : Distinguished Teaching and Learning Fellowship (2011), Innovation and Enterprise Awards, and active roles on funding panels for UK Research Councils, Irish Research Council, and Innovate UK.

Veljko PejovićView profile

Associate Professor

• Mobile deep learning
• Approximate computing
• Resource-efficient computing
• +6 more

Veljko Pejović is an Associate Professor at the Faculty of Computer and Information Science (FRI), University of Ljubljana, Slovenia, where he also serves as Head of the Computer Communications Laboratory. His research focuses on mobile computing with special emphasis on resource efficiency in mobile and IoT environments. His educational background includes a PhD in Computer Science from the University of California, Santa Barbara (2012) and a dipl. ing (BS) from the University of Belgrade, Serbia (2006). Pejović's research interests center around mobile deep learning, approximate computing, and resource-efficient computing. His work explores how computation accuracy can be dynamically adapted based on contextual factors to optimize resource usage without significantly compromising user experience. He has made significant contributions to mobile sensing, machine learning on resource-constrained devices, and security in IoT environments. His recent publications reveal a strong trend toward making AI more efficient and accessible on mobile and edge devices, with particular focus on approximate computing techniques, federated learning frameworks, and context-aware adaptation of computational resources. His research spans applications from precision agriculture using UAVs to behavioral authentication in IoT environments and mental health inference from mobile sensor data. Scientific Awards: 10-Year Impact Runner Up Award at ACM UbiComp for InterruptMe work Outstanding research achievement award for 2024 by the Faculty of Computer and Information Science Best Paper Nominee (top 4%) at UbiComp'14 for InterruptMe Pejović actively mentors PhD and master's students, with numerous theses resulting in workshop, conference, and journal publications. He serves as Associate Editor for ACM IMWUT and ACM JCSS, and has held organizational roles in major conferences including ACM UbiComp 2025. His research is supported by multiple significant projects including approXimation for adaptable diStributed artificial intelligence (ARIS), CODA, AgriAdapt, and CARMA. His laboratory, the Computer Communications Laboratory at FRI, focuses on developing practical systems and frameworks for resource-efficient mobile computing, with several open-source tools and datasets publicly available for the research community.

Ronald Alexander LopezView profile

Research Fellow

• Astronomy
• Astrophysics
• Instrumentation
• +4 more

Ronald Alexander Lopez is a Research Fellow in the Department of Physics at the University of California Santa Barbara (UCSB). As an NSF Astronomy and Astrophysics Postdoctoral Fellow, his work focuses on astronomical instrumentation, particularly in the discovery and characterization of directly imaged exoplanets and debris disks. Education: Ph.D. in Astronomy and Astrophysics (2023) from the University of California, Los Angeles (UCLA). Current research includes developing an MKID high-resolution multi-object spectrograph testbed for exoplanet characterization and contributing to the commissioning plan and testing for the updated polarimetry mode on the GPI 2.0 instrument. His work bridges infrared instrumentation with observational astrophysics, targeting advancements in direct imaging techniques. Scientific Awards NSF Astronomy and Astrophysics Postdoctoral Fellowship

• Electrical engineering
• Electronics, sensors and digital hardware
• Distributed computing and systems software
• +6 more

Masood Parvania is the Roger P. Webb Endowed Professor at the University of Utah in Electrical and Computer Engineering. He serves as Director of the Utah Smart Energy Laboratory (U-Smart) and Co-Director of the NSF WIRED Global Center . His research focuses on mathematical optimization , control theory , and machine learning applications in power system operation, resilience, and interdependent infrastructure modeling. His work addresses critical challenges including: Equity-aware grid restoration Climate-resilient energy systems Cyber-physical security analysis Hybrid energy storage coordination Extreme heat event mitigation strategies Key research trends across his 15 most recent publications reveal deep integration of: Renewable energy with storage systems Machine learning in real-time grid operation Cybersecurity frameworks for critical infrastructure Equity metrics in energy distribution Honors include: IEEE Outstanding Associate Editor Award (2022) University of Utah Presidential Scholar (2020) IEEE Utah Section Outstanding Educator Award (2017) Multiple Best Reviewer and Distinguished Service Awards As Associate Editor for IEEE Transactions on Power Systems , he actively shapes energy research discourse while leading NSF-funded initiatives like: U.S.-Canada Climate-Resilient Grid Center ($90M+ Western EV Infrastructure Scale-Up Wasatch Multi-Modal Corridor Electrification

Venkata Sriram Siddhardh NadendlaView profile

Assistant Professor

• Cyber-physical-human systems
• Human-system interaction
• Statistical inference
• +5 more

Dr. Venkata Sriram Siddhardh Nadendla serves as an Assistant Professor in the Department of Computer Science within the College of Engineering at Missouri University of Science and Technology. His research bridges theoretical foundations in information theory with practical applications in cyber-physical-human systems across critical infrastructure domains. His educational background includes: PhD in Electrical Engineering and Computer Science from Syracuse University MS from Louisiana State University BE from SCSVMV University, India Dr. Nadendla's research spans cyber-physical-human systems with particular emphasis on human-system interaction , statistical inference , and multi-agent decision making . His work integrates machine learning, game theory, and behavioral decision theory to address challenges in transportation systems, mining safety, and cybersecurity. Recent publications show growing focus on fairness in AI systems and neuromorphic computing applications. Analysis of his 15 most recent publications reveals concentration in transportation systems (20%), cybersecurity (25%), human-AI interaction (30%), and healthcare applications (10%), with remaining work spanning mining safety and theoretical decision frameworks. His research demonstrates consistent progression from theoretical foundations toward practical implementations in critical infrastructure. Dr. Nadendla is actively affiliated with the Center for Intelligent Infrastructure at Missouri S&T, where he contributes to developing smart infrastructure solutions. His work uniquely combines quantum cognition models with traditional game theory approaches to model human decision-making in complex systems.

Kürsat YurtView profile

Research Fellow

• High Performance Computing
• Performance Portable Programming
• Rotor and Wake Aerodynamics
• +3 more

Kürsat Yurt, M.Sc., serves as a Research Associate at the Institute for Rotorcraft and Vertical Flight, Technical University of Munich (TUM), based at Boltzmannstr. 15, 85748 Garching, Germany. His role encompasses advanced computational research in vertical flight systems, thesis supervision, and participation in multiple national and international projects targeting next-generation rotorcraft technologies and urban air mobility solutions. Yurt's research spans High Performance Computing, Performance Portable Programming, Rotor and Wake Aerodynamics, and Aeroelasticity. He develops GPU-accelerated meshless methods for large eddy simulations, creates real-time guidance algorithms for urban obstacle avoidance, and investigates morphing airfoil dynamics through fluid-structure interaction frameworks. His work bridges computational mechanics with practical rotorcraft design challenges, emphasizing energy efficiency and flight safety in complex environments. His 2022-2025 publications reveal a cohesive trajectory in computational rotorcraft aerodynamics, featuring innovations in meshless GPU simulations, partitioned coupling techniques, and urban air mobility guidance systems. These works integrate computational fluid dynamics, high-performance computing, and aerospace engineering to address vertical flight challenges including wake modeling, morphing rotor blades, and rotor-airframe interactions. Yurt actively supervises Master's and Bachelor's theses on vortex particle methods, rotorcraft simulation frameworks, and morphing rotor technologies. His research is funded through key projects: ENGEL - Energy Efficient Flight Guidance VARI-SPEED II ARCTIS LaBouR complemented by completed initiatives like InteReSt II and TEMA-UAV. The Institute provides critical infrastructure for his work through specialized facilities: Whirl Tower for rotor dynamics testing Flight Simulator Facilities for pilot-in-loop studies Unmanned Rotorcraft Testbed (AREA) High-performance GPU/CPU clusters for computational workloads These resources enable experimental validation of his computational models and support the institute's mission in vertical flight innovation.

Tarik KelestemurView profile

Researcher

• Robotics
• Artificial Intelligence
• Machine Learning
• +3 more

Tarik Kelestemur is a roboticist specializing in autonomous systems, with affiliations including Boston Dynamics AI Institute and Northeastern University. His work bridges robotics, artificial intelligence, and computer engineering, focusing on tactile manipulation, 3D semantic understanding, and policy learning frameworks. His research interests include: Robotics Artificial Intelligence Machine Learning Computer Engineering Autonomous Systems Human-Robot Interaction Recent publications highlight advancements in diffusion policies, vision foundation models, and 3D relational object graphs. Tarik received an Outstanding Paper Award Finalist at CoRL 2024 and contributes to open-source robotics projects like point_cloud_proc and icub_arm_imitator .

• Robotics
• Artificial Intelligence
• Automated Planning
• +3 more

Alexander Sung is a researcher at the German Research Center for Artificial Intelligence (DFKI) , affiliated with the Cooperative and Autonomous Systems group. His work focuses on robotics, autonomous systems, and planning algorithms, with applications in mobile robots and simulated environments. Research: Robotics, physics-based simulations, and uncertainty-resilient intention recognition. Publications: Contributions to conferences like ECMR-2025 and ICAPS-2023 . Contact: Email Alexander.Sung@dfki.de

Umakishore RamachandranView profile

Professor

• Distributed Systems
• Edge Computing
• Sensor Networks
• +5 more

Umakishore Ramachandran is a Professor in the School of Computer Science at Georgia Institute of Technology's College of Computing, where he directs the Embedded Pervasive Lab. He received his Ph.D. from the University of Wisconsin-Madison in 1986 and has led transformative initiatives including the Online MS in Computer Science (OMSCS) program. His research spans distributed systems, edge computing, and real-time sensor networks, with applications in smart surveillance and connected vehicles. His research interests include architectural design of parallel/distributed systems, large-scale situation awareness using camera networks, cloud-edge continuum optimization, and latency-sensitive applications for geo-distributed infrastructures. Recent work focuses on elevating edge computing to parity with cloud resources. His publications show strong emphasis on edge computing innovations (MicroEdge, FogStore), real-time video analytics (EVA, ClairvoyantEdge), and adaptive mobile systems (Foresight). Trends include multi-tier architectures, quality-of-experience optimization, and scalable processing for IoT workloads. Major Awards: IEEE Fellow (2014) NSF Presidential Young Investigator (1990) ACM/IFIP Middleware Best Paper (2022) 3x College of Computing Dean's Awards He has advised 40+ PhD students, with recent graduates at Google, Microsoft, and academia. Current NSF/CPS grants support his work on geo-distributed latency-sensitive applications. He co-leads the STAR Center and Samsung-funded embedded software programs. His Embedded Pervasive Lab develops systems like Stampede (stream processing) and DFuse (sensor fusion), with testbeds in the Aware Home and transportation networks. Teams collaborate with Intel, Microsoft, and Bosch on edge-AI deployments.

• Computer Science
• Telematics
• Smart Home Technology
• +5 more

Larissa Groth (pronouns: she/her) is a Scientific Associate in the Computer Systems and Telematics working group at the Institute of Computer Science , Freie Universität Berlin . Her role focuses on research and teaching in smart home systems, firmware updates, and networked environment robustness. Research Interests : Smart home device ecosystems, balancing power consumption with user convenience, evaluating device performance under network disruptions, and security resilience against denial-of-service attacks. Teaching Contributions : Supervising bachelor and master thesis projects on topics like automating firmware updates across heterogeneous device fleets, measuring user convenience metrics, and testing smart smoke detectors under network stress. Projects : Involved in initiatives such as the BeLife DES testbed, Einstein Center Digital Future (ECDF), Geocrowd, HyperStar, Peeroscope, RIOT, SAFEST, SKIMS, VIVE media, and X-CHECK.