Find Academic Supervisors

Ahmed BOUBRIMAView profile

Researcher

• Sensor Networks
• Drone Networks
• Wireless Sensing
• +3 more

Dr. Ahmed Boubrima is a tenured faculty researcher at Inria (AGORA team, Lyon, France) since 2023, specializing in sensor networks, drone networks, and environmental sensing. He holds a Ph.D. from INSA Lyon (2019) and master's degrees from École Nationale Supérieure d'Informatique, Algiers (2015). His research focuses on optimizing wireless sensor network deployment for environmental monitoring, with applications in urban air quality and autonomous drone systems. Boubrima has led projects like the ASTRO postdoc at Rice University (2019-2022) and contributed to initiatives at the University of Ottawa as a visiting researcher. Research Interests: Design of energy-efficient sensing platforms for environmental monitoring Autonomous data-driven sensing via networked drones Optimization models for sensor network deployment Resilient environmental mapping using UAVs Awards: Best Paper Award at ACM DroNet@MobiSys 2020 Best Paper Award at UNET 2016 IEEE ComSoc France Chapter Prize (2015) Advising & Teaching: Supervises PhD students and mentors over 20 graduate researchers. Teaches networking courses at INSA Lyon's Telecommunications Department, including Fundamentals of Computer Networking and Performance Analysis. Labs/Teams: Leads the AGORA team at Inria, focusing on algorithmic game theory and networked systems. Collaborates with global institutions on environmental sensing and drone networks.

Elizabeth BehrmanView profile

Professor

• Quantum Information Theory
• Quantum Computing
• Quantum Machine Learning
• +3 more

Elizabeth Behrman is a Professor at Wichita State University (WSU), affiliated with the Department of Mathematics, Statistics, and Physics within the Fairmount College of Liberal Arts and Sciences. She holds a Ph.D. from the University of Illinois at Urbana-Champaign (1985). Her research spans quantum computing, quantum machine learning, and quantum neural networks, with interdisciplinary collaborations in Mathematics, Electrical Engineering, Aerospace Engineering, and Chemistry. Her work includes pioneering studies on quantum control, entanglement estimation, and applications of quantum algorithms in fields like medical imaging and language processing. Key research interests include quantum information theory, quantum algorithms, and the integration of machine learning with quantum systems. Behrman’s contributions to quantum repeaters, quantum generative adversarial networks, and qutrit-based learning networks highlight her focus on advancing quantum technologies for practical applications. She has published extensively on topics ranging from quantum circuit design to noise-resilient algorithms. Collaborative projects involve optimizing quantum hardware through machine learning and exploring hybrid quantum-classical methods. Her work has been featured in venues like IEEE Transactions and YouTube, emphasizing both theoretical and experimental advancements. Behrman’s research also extends to historical contributions in materials science, including studies on ceramic superconductors and inorganic buckyballs. While no specific scientific awards are listed, her prolific publication record and interdisciplinary impact reflect significant contributions to quantum science. Her advising and grant activities are not detailed here, but her collaborations suggest active participation in research networks and funding initiatives.

Xavier PicView profile

Research Fellow

• DNA Data Storage
• Image Coding
• Data Compression
• +3 more

Xavier Pic is a Research Fellow at EURECOM's Data Science department. His work focuses on advancing DNA-based data storage technologies, particularly in the intersection of computer science, bioengineering, and machine learning. He specializes in developing innovative coding algorithms, entropy coders, and neural network architectures for robust image and media storage on synthetic DNA. Key research areas include implicit neural representations, multiple description coding, and compressive autoencoders. His contributions address challenges in long-term data preservation, error resilience, and efficient encoding-decoding processes. Xavier actively explores applications ranging from molecular biology-driven storage solutions to hybrid systems combining classical algorithms (e.g., JPEG) with modern deep learning techniques. His research portfolio reflects interdisciplinary collaboration, bridging computer science with synthetic biology. Prior to his current role, he contributed to text alignment projects using deep learning and dynamic programming for historical document analysis.

• Wireless Communications
• Network Optimization
• Quality of Service (QoS)
• +3 more

Francisco M. Delicado Martínez is an academic researcher specializing in telecommunications, wireless networks, and IoT applications. His work focuses on Quality of Service (QoS) mechanisms, Software Defined Networks (SDN), and blockchain integration in fog computing environments. He has contributed to optimizing resource allocation in OFDMA and IEEE 802.16 networks, and developed IoT-based systems for environmental monitoring (e.g., glyphosate detection, agrochemical spray drifts, and Aedes aegypti surveillance). His recent research emphasizes low-cost IoT ecosystems and blockchain-driven e-government services for public administration and construction management. Research interests span across wireless communications, network optimization, and distributed computing architectures. His publications address challenges in contention resolution, bandwidth request mechanisms, and machine learning integration for disease vector monitoring. Collaborations include projects on fog computing orchestration, SDN-based network enhancements, and multimedia transmission over TDMA/TDD wireless networks. Key contributions include the S-HIDRA architecture (blockchain & SDN for fog computing), DriftGLY and SpectroGLY IoT systems, and the MosquIoT framework for mosquito population monitoring. His work bridges theoretical network protocols with practical applications in agriculture, public health, and smart infrastructure.

Ewa DeelmanView profile

Research Professor

• Scientific Workflow Management
• Distributed Systems
• Resource Provisioning
• +5 more

Ewa Deelman is a Research Professor in the Department of Computer Science at the University of Southern California (USC) and a Principal Scientist at the USC Information Sciences Institute. She also directs Science Automation Technologies, a research group focused on automating scientific processes through advanced workflow management solutions. Her work is foundational in enabling complex scientific computations across distributed computing environments. Deelman's research centers on scientific workflow automation, including resource provisioning, data management, and job scheduling in distributed systems. She pioneered workflow planning for distributed computations and leads the development of the Pegasus Workflow Management System. Current interests extend to anomaly detection using machine learning, quantum-classical hybrid workflows, and edge-to-cloud continuum integration. Her group's work bridges theoretical advances with practical tools for domain sciences like seismology and molecular dynamics. Analysis of her recent publications reveals a strong emphasis on enhancing workflow robustness through machine learning and emerging technologies. Key trends include LLM-based scheduling optimization, pandemic-driven resilience studies, and quantum workflow integration. Her work increasingly addresses cross-cutting challenges in data-intensive science, particularly in managing computational workflows across heterogeneous infrastructures from edge devices to cloud platforms. As Director of Science Automation Technologies, Deelman oversees a team that has made Pegasus a cornerstone tool in scientific computing. The system handles complex workflow orchestration for projects like CyberShake (seismic hazard analysis) and molecular dynamics simulations, automating data movement, execution, and error recovery across campus clusters, supercomputers, and cloud resources.

• Cryptography
• Cybersecurity
• Hardware Security
• +3 more

Elisabeth Oswald is a University Professor at the Alpen-Adria-Universität Klagenfurt, affiliated with the Institut für Artificial Intelligence und Cybersecurity. Her research focuses on cryptographic security, side-channel attacks, and leakage detection in hardware and software implementations. She is a key contributor to advancements in cryptographic resilience, countermeasures against side-channel vulnerabilities, and the development of efficient security evaluation frameworks. Her work spans theoretical and applied cryptography, with a strong emphasis on practical security challenges in embedded systems and cryptographic protocols. Notable areas include the analysis of masking techniques, multi-task learning applications in AES implementations, and the certification of leakage-resistant systems. She also explores statistical methods for evaluating cryptographic systems' robustness, such as mutual information estimation and distinguisher-based approaches. Her articles from 2021–2025 highlight contributions to post-quantum cryptography (e.g., FrodoKEM optimization), leakage model completeness, and the practical implications of side-channel countermeasures. While no specific awards are listed, her extensive publication record underscores her influence in the field. She is actively involved in academic governance, including membership in the Curricularkommission Informatik.

Burcu ÖzkanView profile

Researcher

• Algorithms
• Theory & Logic
• Programming Languages
• +9 more

Burcu Özkan is a researcher at the Max Planck Institute for Software Systems (MPI-SWS), part of the Max Planck Society. Her work focuses on foundational areas of computer science including algorithms, programming languages, verification, and cyber-physical systems. She also explores distributed systems, networked/mobile systems, security, privacy, and social/information systems. Her research interests span theoretical and applied topics such as formal methods for system verification, resilient distributed computing, and privacy-preserving technologies. While no specific articles or awards are listed, her affiliations suggest involvement in cutting-edge CS research aligned with MPI-SWS's focus areas. Email: burcu@mpi-sws.org | Website: https://people.mpi-sws.org/~burcu (Note: The website currently returns a 404 error)

Barry CrokeView profile

Associate Professor

• Environmental Modeling
• Water Resource Management
• Hydrology
• +3 more

Barry Croke is an Associate Professor at the Australian National University (ANU), holding a joint appointment with the Fenner School of Environment & Society and the Mathematical Sciences Institute since 2006. His expertise spans environmental modeling, water resource management, hydrology, and uncertainty analysis. He currently serves as president of the International Commission on Water Resources Systems (ICWRS) within the International Association of Hydrological Sciences (IAHS), and leads the Applied and Computational Mathematics stream at the Modelling and Simulation Society of Australia and New Zealand. Dr. Croke holds a BSc in Theoretical Physics and a PhD in Astrophysics from the University of New South Wales. His research focuses on model development for predicting streamflow, water quality, and integrated resource management. Notable areas include flood resilience strategies, ungauged site hydrologic prediction, and improving community resilience to flood events. His work emphasizes addressing uncertainty in environmental datasets through sensitivity and uncertainty analysis. He leads projects such as the One Basin CRC and collaborates on initiatives like community-led flood intelligence networks. His contributions extend to editorial roles at Hydrology Research and advisory positions in global hydrological organizations.

Yanjing LiView profile

Assistant Professor

• Computer Architecture
• Hardware Security
• Emerging Technologies
• +4 more

Yanjing Li is an Assistant Professor in the Department of Computer Science (Systems Group) at the University of Chicago. She holds a Ph.D. in Electrical Engineering from Stanford University, an M.S. in Mathematical Sciences (with honors) and a B.S. in Electrical and Computer Engineering (with a double major in Computer Science) from Carnegie Mellon University. Her research focuses on computer architecture, hardware security, emerging technologies, and the intersection of machine learning with robust system design. Education: Ph.D., Electrical Engineering, Stanford University M.S., Mathematical Sciences (Honors), Carnegie Mellon University B.S., Electrical and Computer Engineering (Double Major in Computer Science), Carnegie Mellon University Research Interests: Professor Li explores efficient, intelligent, and secure computer architectures. Key areas include photonic interconnects, fail-secure architectures, resilience in deep learning accelerators, and cross-layer system design. Her work emphasizes energy-efficient computing and hardware security against failures and attacks. Awards & Honors: 2022 DAC Under-40 Innovators Award 2021 Google Research Scholar Award 2015 Intel Labs Gordy Academy Award Outstanding Dissertation Award (European Design and Automation Association) Multiple Best Paper Awards at IEEE/ACM Conferences Advising & Projects: Leads the YLab, mentoring PhD students like Yi He and Zequan Zhou. Active projects include UpDown (graph analytics acceleration), photonic interconnects funded by NSF/E2CDA, and fail-secure architectures. Collaborates on NSF-funded photonic computing research with UIUC and UChicago teams. Labs & Groups: Directs YLab and contributes to the Systems Group, fostering interdisciplinary work in systems, programming languages, and hardware-software co-design.

• Robotics
• Artificial Intelligence
• Task and Motion Planning
• +4 more

Natalia Belotti is a tenure-track Lecturer in the School of Computing at the Australian National University (ANU), affiliated with the ANU College of Systems & Society. Her research focuses on robotics and artificial intelligence, emphasizing planning algorithms for human-centric environments. She holds a PhD and MS from Rutgers University and was a postdoctoral research associate at Rice University under Prof. Lydia Kavraki. Education: PhD and MS in Robotics, Rutgers University Postdoctoral Fellowship at Rice University Her research interests include multi-robot planning, task-motion integration, human-robot collaboration, and algorithmic guarantees in practical robotics systems. Recent work explores generative models for unobserved object detection, privacy-aware motion planning, and optimal grasp strategies in cluttered environments. Awards: Best Paper Award at IEEE MRS Nomination for Best Paper in Automation at IEEE ICRA Her current projects bridge theoretical robotics with real-world applications, involving AI-driven automation and human-centric system design. She actively contributes to conferences as an associate editor of IEEE Robotics and Automation Letters.

Pamela T BhattiView profile

Professor

• Neural Prosthetics
• Biomedical Engineering
• Cardiac Imaging
• +3 more

Dr. Pamela T Bhatti is a Professor and Associate Chair for Strategic Initiatives and Innovation at Georgia Tech's School of Electrical and Computer Engineering. Her research focuses on neural prosthetics for sensory loss (cochlear/ vestibular implants), cardiac imaging for cardiovascular disease, and engineering entrepreneurship. She holds degrees from UC Berkeley (B.S. Bioengineering), University of Washington (M.S. EE), University of Michigan (Ph.D. EE), and an M.S. in Clinical Research from Emory University. She co-founded Camerad Technologies to combat medical imaging errors and serves as Editor-in-Chief of IEEE Journal of Translational Engineering in Health and Medicine. Education B.S. Bioengineering, UC Berkeley (1989) M.S. Electrical Engineering, University of Washington (1993) Ph.D. Electrical Engineering, University of Michigan (2006) M.S. Clinical Research, Emory University (2013) Research Interests Dr. Bhatti's work spans: Neural Prosthetics : Developing micromagnetic cochlear stimulation and vestibular implants Cardiac Imaging : Innovations in cardiac gating techniques for CT imaging Entrepreneurship : Bridging academic research with clinical applications through startup ventures and mentorship programs Recent Research Trends Her 2021-2025 work emphasizes: AI-driven cardiac imaging frameworks Micromagnetic stimulation alternatives to traditional cochlear implants Entrepreneurial training for clinical researchers Awards 2017 Georgia Tech Class of 1934 Outstanding Interdisciplinary Activities Award Editorial roles in Science—Translational Medicine and IEEE Journal Advising & Innovation Guided mentorship programs for junior faculty and pioneered patient photography integration in radiology workflows. Active in translational research training through programs like NCATS I-Corps. Labs/Teams Leads interdisciplinary teams developing medical devices at the interface of electrical engineering and clinical medicine.

• Precision Agriculture
• Digital Twin Technology
• Crop Growth Modeling
• +4 more

Frits van Evert is a Researcher in the Department of Applied Ecology at Wageningen University & Research, specializing in precision agriculture and digital twin technology. His work focuses on crop growth modeling, sustainable farming systems, and agricultural robotics. He leads several high-profile projects such as ROBS4CROPS and GALIRUMI, which integrate digital twins with robotic solutions for arable and dairy farming. Key contributions include developing decision support systems using remote sensing and crop models, improving nitrogen management strategies, and creating open data platforms like Akkerweb. Van Evert's research spans multiple disciplines, including crop physiology, climate change impacts, and farm-level sustainability. He has published over 192 research outputs, including datasets on potato growth dynamics and grassland weed management. His projects emphasize collaboration with industry stakeholders to bridge the gap between academic research and practical agricultural applications. Projects: ROBS4CROPS (robotic farming systems), GALIRUMI (computer vision for grassland), and Digital Twin initiatives Key datasets: Potato growth in the Netherlands, RumexWeeds grassland data, and UAV-based multispectral datasets Technical expertise: Crop modeling (WOFOST, SWAP), remote sensing integration, and ISO 11783 communication protocols His recent work explores digital twin applications for real-time farm management, climate adaptation strategies, and the economic viability of robotic solutions. Van Evert actively engages with industry through workshops, media contributions, and keynote lectures on precision agriculture's future.

Ali EslamiView profile

Associate Professor

• Cyber-Physical Systems
• Machine Learning
• Error Control Coding
• +7 more

Ali Eslami is an Associate Professor in the Department of Electrical and Computer Engineering at Wichita State University. His research focuses on applying probabilistic methods and machine learning to study complex systems such as gene regulatory networks and cyber-physical systems. He holds a Ph.D. from the University of Massachusetts Amherst and has collaborated with prominent institutions like Duke University and Georgia Tech. His work spans error control coding, IoT design, and resilient network analysis. Education: Ph.D. in Electrical and Computer Engineering, University of Massachusetts Amherst (2013) M.Sc. in Communications Systems & Signal Processing, Sharif University of Technology (2006) B.Sc. in Electrical Engineering, Sharif University of Technology (2004) Research Interests: Probabilistic methods for complex networks Machine learning in cyber-physical systems Error control coding in communications and biological systems Resilience in multi-layer networks IoT and wireless network design Awards: Recipient of the Young Faculty Risk Taker Award (2017) from Wichita State University's Office of Academic Affairs Advising & Collaborations: Advised over a dozen graduate and undergraduate students, many of whom have pursued roles in academia and industry Collaborated with leading researchers at Duke University, Texas A&M, and Georgia Tech Labs & Teams: Leads a research group focused on evolutionary AI and network resilience Team members have presented at conferences and developed projects like Shocker Controls TM

Arsenia CHORTIView profile

Professor

• 5G/6G Networks
• Wireless Security
• Physical Layer Security
• +6 more

Dr. Arsenia CHORTI is a Full Professor at École Nationale Supérieure d'Électronique et de ses Applications (ENSEA), affiliated with the ETIS laboratory and the Barkhausen Institut. She specializes in 5G/6G wireless systems, with a focus on physical layer security, network security, and secure communication protocols. Her research addresses challenges in authentication, confidentiality, and integrity in next-generation networks. Teaching responsibilities include Digital Communications, Cryptography fundamentals, and IoT security. She actively contributes to IEEE initiatives, serving as Chair of the Physical Layer Security Focus Group and TPC Chair for IEEE ICC 2023. Her publications (over 120 articles) emphasize practical security solutions for 6G, including AI/ML-driven security frameworks and physical layer authentication protocols. Key affiliations: ETIS Lab, Barkhausen Institut Editorial roles: IEEE ComSoc Best Readings Research foci: Secret key generation, secure slicing, jamming mitigation, and physical layer cryptography Her work bridges theoretical security principles with real-world implementations, addressing emerging threats in IoT, vehicular networks, and cyber-physical systems.

• Fault-Tolerant Computing
• Asynchronous Circuits
• Digital System Design
• +3 more

Florian Ferdinand Huemer is a PostDoc Researcher at the Embedded Computing Systems department (E191-02 Faculty Council Substitute Member) within the Faculty of Informatics at Vienna University of Technology. His work focuses on fault-tolerant asynchronous circuits, delay-insensitive communication protocols, and FPGA reliability analysis. BSc , Vienna University of Technology Dipl.-Ing. , Vienna University of Technology Dr.techn. , Vienna University of Technology Key research areas include: Fault-Tolerant Computing : Designing systems resilient to transient faults and radiation effects. Asynchronous Circuits : Developing quasi-delay-insensitive logic and Muller pipelines. Embedded Metrology : Applying polarization cameras and time-to-digital converters for industrial measurements. Recent publications address: 2024 : Polarization camera-based inline thickness measurement and FPGA ring oscillator synchronization. 2023 : Mitigating single-event transients in QDI logic. 2021 : Automated fault-injection frameworks and QDI pipeline sensitivity analysis. Projects funded by the Austrian Science Fund (FWF) during 2013-2018 explored self-stabilizing Byzantine fault-tolerant algorithms. Supervisions include: Haschke (2024): QDI adder comparison Spitzer (2024): Automated fault-injection framework Schwendinger (2022): Asynchronous circuit testing tools Pircher (2022): Smart SoC testing via IJTAG Behal (2021): QDI design template fault sensitivity