Find Academic Supervisors

M. Yasin Akhtar RajaView profile

Professor

• Optoelectronics
• Photonics
• Optical Communication Networks
• +5 more

M. Yasin Akhtar Raja is a Professor of Physics and Optical Science at the University of North Carolina at Charlotte (UNC Charlotte), where he has served since 2004. He also holds an adjunct professorship in Electrical and Computer Engineering since 2011. As an undergraduate advisor, he plays a key role in student mentorship. Ph.D. in Optical Physics from the University of New Mexico (1988) M. Phil in Laser Physics from Quaid-i-Azam University (Pakistan) B.Sc. in Physics and Math from Punjab University (Lahore, Pakistan) His research focuses on optoelectronics, photonics, and optical communication networks, with expertise in VCSELs, optical amplifiers, and solar energy harvesting. He has authored over 170 publications and secured multiple patents, including foundational work on surface-emitting lasers (VCSELs). Raja has supervised 42 graduate students and chairs the undergraduate committee in his department. He co-founded the HONET-ICT international conference series and advises research initiatives in Pakistan. Notable achievements include his invention of the surface-emitting RPG laser (VCSEL), a Merit Scholarship from Pakistan, and contributions to fiber optic networks and smart grid technologies. His work spans theoretical and applied research, with applications in telecommunications, energy, and materials science.

Sandra Gail BiedronView profile

Research Professor

• Particle Accelerator Systems
• Laser Systems
• Artificial Intelligence in Controls
• +5 more

Sandra Gail Biedron is a Research Professor in the Department of Electrical and Computer Engineering at the University of New Mexico (UNM), with a secondary appointment in Mechanical Engineering. Previously, she held roles at Colorado State University (CSU) as an Affiliate Professor and at Argonne National Laboratory. She leads Element Aero, a research company, and has served as a Visiting Professor at the University of Ljubljana. Her expertise spans particle accelerators, laser systems, AI-driven controls, and applications in security/defense. Education: B.A. in Chemistry and Biology, Trinity Christian College (1994) Ph.D. in Accelerator Physics, Lund University (2001) Research Interests: Particle accelerator systems and laser technologies AI integration in complex systems (e.g., controls, prediction) Security/defense applications (e.g., detectors, sensors) Quantum information science (Coulomb crystals in storage rings) High-power lasers and free-electron lasers (FELs) Accelerator-based science, including dark matter detection Awards & Recognition: IEEE Nuclear and Plasma Sciences Society Award (2018) George T. Abell Mid-Career Faculty Award (2013) APS Fellow, OSA Senior Member, SPIE Fellow Advising & Projects: Ph.D. students: Aasma Aslam (UNM/Computer Science), Jorge Diaz Cruz (UNM/ECE), Reza Pirayesh (UNM/ME) Lead roles in DOE projects, defense contracts, and international collaborations Deputy Lead Engineer for a Boeing defense project Labs & Teams: Research group includes postdocs and scholars (e.g., Trudy Bolin, Salvador Sosa) Collaborations at Brookhaven National Lab (ATF), CERN, and Sincrotrone Trieste

Zahra RaissiView profile

Academic

• Quantum Information Theory
• Quantum Networks
• Quantum Error Correction
• +3 more

Dr. Zahra Raissi is a Junior Professor and group leader at Paderborn University's Department of Computer Science. She holds a PhD from ICFO-The Institute of Photonic Sciences (Barcelona) and postdoctoral experience at Virginia Tech and ICFO. Her research focuses on quantum information theory, quantum networks, and quantum error correction with applications in many-body entanglement and qudit systems. Affiliations: Quantum Information Junior Research Group, Institute for Photonic Quantum Systems (PhoQS) Teaching: Courses on Quantum Networks (Bachelor's) and Quantum Information (Master's) Key Awards: Brilliant Talent Awards from Iran's National Elite Foundation (2015-2017), Equal Opportunity Grants (2023-2024) Her work bridges quantum theory and experimental implementation, emphasizing practical applications in quantum communication and error correction. Research outputs include advancements in qudit-based photonic graph states and GHZ state manipulation techniques.

Fredrik ManneView profile

Professor

• Parallel Computing
• Distributed Computing
• Graph Algorithms
• +3 more

Fredrik Manne is a Professor at the Department of Informatics, University of Bergen, Norway. His work focuses on parallel and distributed computing, particularly in combinatorial scientific computing and self-stabilizing algorithms. He has contributed extensively to graph algorithms, including matching, coloring, and clustering, with applications in high-performance computing, numerical optimization, and wireless networks. His research involves designing algorithms for parallel architectures, including multi-core and GPU-based systems. He has co-authored numerous publications on topics such as spanning forests, vertex cover heuristics, and b-matching. His work often integrates theoretical and applied approaches, addressing challenges in sparse matrix computations and wireless mesh network communication. The recent articles highlight his exploration of graph neural networks for parallel coloring, efficient multithreaded matching algorithms, and GPU-accelerated clustering methods. These studies emphasize scalability, optimization, and real-world applications in computational science.

Michael GaliliView profile

Associate Professor

• High-Speed Optical Communications
• Silicon Photonics
• Nonlinear Fiber Optics
• +4 more

Michael Galili is an Associate Professor in the Department of Electrical and Photonics Engineering at the Technical University of Denmark (DTU). He is affiliated with the High-Speed Optical Communications Centre of Excellence for Silicon Photonics. His research focuses on high-speed optical communication systems, including nanotechnology-based components like optical filters and ultra-fast lasers for data signal processing. He explores novel solutions to handle data rates exceeding 320 Gbit/s using photonics, addressing challenges in signal processing and system design beyond traditional electronic limits. Galili leads the Nano-COM project developing nanotechnology-driven optical communication components. His work integrates advanced photonics with fiber optics, emphasizing optical signal processing, nonlinear effects, and quantum communication systems. He has supervised multiple PhD students in areas such as quantum communication multiplexing, frequency conversion, and mode division multiplexing. His recent publications span topics including all-optical switching via Fano resonance, parametric spectral shaping, and long-haul unrepeated transmission systems. He has received awards such as the Jorcks forskningspris (2021) and AEG Elektronprisen (2023). His lab, part of DTU’s Fotonik research group, collaborates internationally on projects like photonic lanterns and silicon carbide-based Kerr combs for ultra-high-speed data transmission.

Hou Man ChinView profile

Visiting Professor

• Quantum Physics and Information Technology
• Machine Learning in Photonic Systems
• Quantum Key Distribution
• +3 more

Hou Man Chin is a Visiting Professor at the Technical University of Denmark (DTU), affiliated with the Department of Electrical and Photonics Engineering and the Department of Physics. His research spans Quantum Physics and Information Technology, focusing on Machine Learning in Photonic Systems. He explores applications in quantum key distribution, optical communication systems, and quantum cryptography, with a particular emphasis on securing network infrastructure through advanced quantum protocols. Key areas of research include squeezed light generation and recovery, digital signal processing for quantum communication, and overcoming technical challenges like phase noise and signal degradation in long-distance systems. His work addresses practical implementation of quantum technologies, such as composable security frameworks and real-world deployment of quantum encryption methods. Hou Man Chin collaborates with experts in quantum technologies, including Ulrik Lund Andersen and Darko Zibar, on projects related to quantum information processing and machine learning integration. His research group (qTReX) develops semi-autonomous quantum key distribution systems and investigates vulnerabilities in modulation leakage and carrier recovery mechanisms.

• Early childhood education
• Child agency
• Pedagogy and curriculum
• +7 more

Queena Lee is a Lecturer in Early Years Education at Swinburne University of Technology, within the School of Social Sciences, Media, Film and Education. She holds a PhD from Monash University and brings extensive experience from prior roles at Monash University and Australian Catholic University, where she worked with pre-service teachers in undergraduate and postgraduate programs. Education: Doctor of Philosophy (PhD), Monash University, Australia (2020–2024) Her research is rooted in early childhood education, with a focus on child agency, pedagogy, curriculum development, and cultural-historical theory. She explores how children’s voices and participation are fostered in dynamic social-cultural contexts, and investigates sustainability, citizenship, and play as integral components of early learning. She also examines the impact of curriculum policies and the application of cultural-historical methodology in educational research. Recent publications highlight her innovative work using virtual reality (VR) and simulation technologies to enhance pre-service teacher education. Her research trends show a strong emphasis on immersive learning, teacher preparation, and cross-cultural comparative studies in early childhood settings across Australia, Indonesia, and Vietnam. She also reflects on academic identity and resilience, particularly during the pandemic. Scientific Awards: Doctoral Thesis Award 2024, Early Childhood Australia Queena actively contributes to the academic community through advising, professional development, and leadership. She is a convenor of the Cultural-historical & Activity Theory Special Interest Group (SIG) in the Australian Association for Research in Education (AARE), and is a member of professional organizations including Early Childhood Australia (ECA), AARE, and EECERA. She has led funded and non-funded research projects, particularly in pedagogy for pre-service teacher learning and VR applications in education. Her collaborative network includes researchers across Australia and internationally. Labs and Research Teams: While no formal lab is mentioned, Queena is actively involved in research teams focused on cultural-historical activity theory, early childhood pedagogy, and technology-enhanced teacher education. She collaborates with scholars on VR-based simulations and comparative international studies in early childhood education.

Russ AlgarView profile

Professor

• Luminescent Materials
• Fluorescence Spectroscopy
• Bio/Chemical Sensing
• +7 more

Russ Algar is a Professor at the Department of Chemistry within the Faculty of Science at the University of British Columbia (UBC) . Holding a Canada Research Chair (Tier 2) in Biochemical Sensing since 2012 and a Michael Smith Foundation for Health Research Scholar since 2014, he leads the Algar Research Group , focusing on luminescent materials for bioanalysis, fluorescence spectroscopy, FRET networks, and point-of-care diagnostic devices. Ph.D. , University of Toronto (2010) M.Sc. , University of Toronto (2006) Hon.B.Sc. , University of Toronto (2005) His research spans luminescent materials , biochemical sensing , FRET-based probes , and smartphone-integrated diagnostic platforms . Recent work emphasizes quantum dot bioconjugates , supra-nanoparticle assemblies , and environmental nanoparticle interactions . Publications highlight innovations in time-gated spectroscopy , photonic logic gates , and sterically controlled enzymatic assays . Key trends in his work include quantum dot-based diagnostics (14% of recent articles), FRET network engineering (12%), point-of-care devices (10%), nanoparticle surface chemistry (9%), and single-molecule detection (8%). Collaborations extend to UBC's LASIR , Hudson Group , and TRIUMF . Canada Research Chair (2012-Present) Michael Smith Foundation Scholar (2014-Present) NSERC Postdoctoral Fellowship (2010-2012) UBC Chemistry Basic Skills Test developer Editorial Board : Analytical Chemistry Research , Chemosensors , Nano Reviews The group develops quantum dot-biomolecule conjugates for intracellular sensing and low-cost diagnostic tools . Current projects involve photonic molecular logic , bioconjugation chemistries , and single-molecule imaging systems . Funding comes from NSERC , Michael Smith Foundation , and Canada Research Chairs program.

Gregor RehderView profile

Professor

• Marine Biogeochemistry
• Chemical Oceanography
• Greenhouse Gases
• +5 more

Prof. Gregor Rehder is Professor of Marine Chemistry and Deputy Head of the Marine Chemistry Section at the Leibniz Institute for Baltic Sea Research Warnemünde (IOW), an institute affiliated with the University of Rostock. Since 2006, he has led the Biogeochemistry of Environmentally Relevant Gases Working Group, focusing on greenhouse gas dynamics in marine systems. His work spans Research Priority 1 and 2 of the IOW program, emphasizing Baltic Sea biogeochemistry. Rehder holds a Diploma (1993) from the University of Bayreuth and a Ph.D. (1996) from the University of Kiel. His career includes positions at GEOMAR Kiel and Monterey Bay Aquarium Research Institute. Research interests center on marine greenhouse gases (CH₄, N₂O, CO₂), carbon cycling, and ocean acidification. He develops advanced sensors for gas monitoring and studies land-sea interactions affecting coastal biogeochemistry. Recent work explores methane leakage impacts, carbon dioxide removal technologies, and Baltic Sea acidification. Publications (2018-2025) show strong emphasis on: Baltic Sea greenhouse gas fluxes and carbon dynamics Coastal peatland rewetting effects Ocean alkalinity enhancement strategies Nord Stream methane leak impacts In-situ sensor development for marine gases He actively advises doctoral students, with 10+ completed PhD supervisions on topics like methane fluxes, ocean acidification, and trace gas liberation. Current projects include: RINGO (ICOS readiness for global observations) BONUS INTEGRAL (Baltic carbon/gas monitoring) EVAR (Benguela Upwelling System under climate change) Baltic Transcoast (land-sea matter flows) Rehder coordinates equipment on the VOS Finnmaid research vessel (ICOS infrastructure) and collaborates in international networks including ICOS-Oceans and the American Geophysical Union.

• LLM-assisted agent systems
• Explainable AI
• Multimodal artificial intelligence
• +12 more

Dr. Yifei Dong is a Research Fellow at the Data Science Institute , University of Technology Sydney, with expertise in LLM-assisted agent systems , explainable AI , and multimodal artificial intelligence . Holding a PhD in Computer Science from UNSW Sydney and over a decade of fintech industry experience including CTO roles, he has secured $2.4 million in competitive funding for AI solutions bridging academia and real-world applications in healthcare, education, and finance. Education : PhD in Computer Science from UNSW Sydney Current Role : Research Fellow at UTS Data Science Institute (2023–present) Past Academic Appointments : Lecturer at Southern Cross University and Western Sydney University Dr. Dong’s research focuses on making AI systems transparent and socially beneficial , with contributions to adversarial AI, trustworthy digital societies, and wireless sensor networks. His recent work includes: Developing AICAttack (2025) for adversarial image captioning attacks Creating the QMAD fairness metric (2025) for dynamic environments Advancing explainable ECG diagnosis systems (2025) via multimodal LLMs As a scientific awardee (2025 RegTech Social Impact of the Year), he has pioneered AI solutions for vulnerable populations, such as NDSI participants through the "My Complaint Assistant" tool. His supervision of PhD and Honours students emphasizes technical rigor and ethical responsibility.

Mathias PelkaView profile

Professor

• Intelligent Automation Technology
• Smart Factory
• Industry 4.0
• +6 more

Mathias Pelka is a Professor at the Department of Electrical Engineering and Computer Science at Technische Hochschule Lübeck. His work focuses on intelligent automation technology, smart factory concepts, and Industry 4.0 applications. Education in Informatik (University of Lübeck), Applied Information Technology (Lübeck University of Applied Sciences), and Electrical Engineering (Milwaukee School of Engineering) His research spans localization algorithms, LiDAR-based object detection, neural networks for robotics, and underwater optical distance estimation. Key technologies include sensor fusion, recursive Bayesian filters, and time-based ranging methods. Recent publications highlight trends in autonomous vehicle sensing, indoor positioning systems, and unified location architecture frameworks. His work integrates machine learning, signal processing, and wireless communication for smart infrastructure solutions. Prior roles include software development and Scrum Master positions at Drägerwerk AG & Co. KGaA (2020-2021), software engineering at Ibeo Automotive Systems GmbH (2018-2020), and research associate positions at TH Lübeck (2013-2018).

• Computer Music
• Optical Networks
• Optimization
• +9 more

Cristina Emma Margherita Rottondi is an Associate Professor at the Department of Electronics and Telecommunications (DET) of Politecnico di Torino . She is a member of the Photonext Interdepartmental Center and contributes to research in telecommunications, computer music, and network optimization. Her work spans privacy-preserving protocols, smart grid communication, and low-latency audio streaming. Research Interests : Networked Music Performance, Optical Networks, Smart Grid Privacy, Machine Learning. Education : Not explicitly listed. Research Areas include: Smart Grid Privacy : Developing secure protocols for data aggregation and distributed energy optimization. Optical Network Design : Investigating machine learning-driven solutions and spatial division multiplexing. Networked Music Performance : Addressing latency and inclusivity in remote musical collaboration. Publication Trends highlight interdisciplinary work at the intersection of telecommunications , machine learning , and music technology . Recent articles focus on privacy-preserving smart grids , 5G-enabled musical IoT , and UDP packet trace datasets . Scientific Awards : 2020 Charles Kao Award Best Paper Awards at IEEE Online Greencomm (2014), DRCN (2017), and others N2Women Rising Star (2020) Advising includes PhD candidates working on networked music performance , accessible musical education , and medical wearable devices . She has contributed to national patents for inclusive audio hardware.

Gregory DoerkView profile

Researcher

• Self-assembly
• Block copolymers
• Nanofabrication
• +5 more

Gregory Doerk is a Materials Scientist specializing in AI Accelerated Nanoscience at Brookhaven National Laboratory's Center for Functional Nanomaterials (CFN). As a key member of the Electronic Nanomaterials Group, he conducts cutting-edge research on self-assembly processes for nanofabrication applications. His work bridges fundamental polymer science with practical applications in energy, optics, and electronics manufacturing. Doerk earned his B.S. in Chemical Engineering from Case Western Reserve University (2005) and his Ph.D. in Chemical Engineering from the University of California, Berkeley (2010). His academic journey was complemented by philosophical studies that shaped his approach to scientific inquiry, recognizing both the power and limitations of scientific knowledge. Dr. Doerk's research focuses on directing the self-assembly of polymers to create tailored nano-architectures for optical, chemical, and energy applications. He specializes in block copolymer systems, developing combinatorial, high-throughput, and adaptive experimental methods to integrate self-assembly into scalable manufacturing processes. His work addresses the challenge of scaling block copolymer assembly to larger feature sizes (approaching 200nm) that can influence light for structural color applications, overcoming the natural limitations of traditional block copolymer systems. His 15 most recent publications reveal a strong trajectory toward AI-accelerated materials discovery, with increasing focus on autonomous experimentation, combinatorial approaches, and hierarchical structures. The research spans fundamental polymer science to applied nanotechnology, with applications in photonic materials, energy conversion, and advanced manufacturing. His work demonstrates a progression from basic self-assembly mechanisms to increasingly sophisticated systems incorporating machine learning and high-throughput methodologies. 2021 DOE Early Career Research Program award recipient As a senior scientist at CFN, Doerk mentors numerous users from academic and industrial institutions worldwide, helping them develop self-assembly processes for diverse applications ranging from microfluidics to biosensing. He has secured significant research funding, including the prestigious DOE Early Career award, and actively contributes to the scientific community through organizing workshops at major conferences including the American Physical Society March Meeting and the NSLS-II & CFN User Meetings. His collaborative approach has resulted in numerous interdisciplinary projects spanning multiple DOE facilities. Dr. Doerk leads research in the Electronic Nanomaterials group at CFN, where he operates specialized equipment for block copolymer self-assembly, solvent vapor annealing, and pattern transfer. His lab focuses on developing adaptive experimental methods that combine self-assembly with AI-driven discovery, creating a unique environment where traditional materials science intersects with cutting-edge computational approaches. The team regularly collaborates with researchers using Brookhaven's National Synchrotron Light Source II for in-situ characterization of self-assembly processes.

Hye Yoon ParkView profile

Associate Professor

• Biomedical Technologies
• RNA Regulation
• Neuroscience
• +5 more

Dr. Hye Yoon Park is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Minnesota. Her research focuses on developing advanced biomedical technologies for studying RNA regulation at the single-molecule and single-cell levels in living tissues and organisms. Research Interests Real-time imaging of gene expression dynamics Activity-dependent transcription in neural networks RNA localization and transport mechanisms Development of fluorescent RNA labeling systems Key Techniques Live-cell and in vivo imaging Genetic engineering of mouse models Quantitative single-molecule analysis Computational modeling of RNA transport Her recent publications highlight interdisciplinary approaches combining RNA biology, neuroscience, and nanotechnology, with particular emphasis on Arc and β-actin mRNA dynamics in neurons, optogenetic control of RNA condensation, and novel diagnostic tools like nanoparticle-enhanced QuIC assays for Parkinson's disease. She actively seeks graduate students for research and has developed specialized software such as HybTrack for particle tracking analysis.

• Nuclear and Plasma Physics
• Particle and High Energy Physics
• Astronomical Sciences
• +7 more

Dr. Shanti Krishnan is a Senior Lecturer in the School of Engineering at Swinburne University of Technology, where she conducts interdisciplinary research at the intersection of physics, engineering, and cybersecurity. Her work spans fundamental physics experiments and practical industrial applications. Her research focuses on nuclear and plasma physics , particle physics , and astronomical sciences , with key contributions to muon tomography for monitoring mining infrastructure, dark matter detection via the SABRE South experiment at the Stawell Underground Physics Laboratory, and instrumentation development for the W. M. Keck Observatory. She also explores cybersecurity in Industry 4.0 , particularly through digital twin technologies and anomaly detection in cyber-physical systems. Her recent publications highlight advancements in muon-based navigation for space exploration, cosmic ray-based cybersecurity systems, and simulation of dark matter detectors. These works demonstrate a strong trend toward applying particle physics principles to real-world engineering and security challenges. Dr. Krishnan has received multiple grants, including external funding from HILT CRC Limited and internal grants from Swinburne University, supporting projects such as impact-driven learning materials for net zero in heavy industries and digital twin applications for blood product manufacturing. Development of Impact driven learning materials for net zero in heavy industries – HILT CRC Limited (2025) Rapid Scenario Testing using digital twin for sustainable and scalable manufacturing of blood products – Swinburne University (2024) A Dynamic In-bed Weight Monitoring System for Aged Care Facilities – Cloud Burst Software Pty Ltd (2023) She is actively supervising PhD students, including a project on using digital twins and machine learning to detect cyber-attacks in Industry 4.0 manufacturing systems. Her work is supported by collaborations with institutions such as Caltech, UC Observatories, ANU, and W. M. Keck Observatory, reflecting a strong international research network. Dr. Krishnan leads and contributes to multidisciplinary research teams focusing on detector development, secure industrial systems, and sustainable manufacturing. Her lab and project teams integrate physics, engineering, and data science to solve complex real-world problems.