Find Academic Supervisors

• Wireless Communications
• Internet of Things (IoT)
• Optimization
• +7 more

Dr. Khoa Phan is a Senior Lecturer in the Department of Computer Science and Information Technology at La Trobe University, Australia. He holds an ARC DECRA Senior Research Fellowship (2020-2023) and has held prior positions at UCLA, Monash University, and others. His academic background includes a B.Eng. (UNSW), two M.Sc. degrees (University of Alberta and Caltech), and a Ph.D. in Electrical Engineering from McGill University. Dr. Phan's research focuses on optimizing next-generation communication networks, particularly in wireless communications, IoT, satellite systems, and machine learning applications. He has secured significant grants, including ARC Discovery Projects and industry partnerships. His work emphasizes secure cyber-physical systems, federated learning, and edge computing. He has received prestigious awards such as the ARC DECRA and Atwood Fellowship. His research spans over 100 publications, with contributions to areas like OTFS modulation, secure satellite communications, and graph-based anomaly detection. He actively supervises PhD students and collaborates internationally, including initiatives to strengthen ties between La Trobe University and Vietnamese institutions. Grants include ARC Discovery Projects (totaling $1.3M+), CRC SmartSAT, and industry scholarships. His work addresses energy efficiency, secure resource allocation, and AI-driven solutions for 5G/6G networks and the metaverse.

Risteski AleksandarView profile

Professor

• Telecommunications
• Cybersecurity
• Blockchain Technology
• +5 more

Professor Risteski Aleksandar holds a Ph.D. in Telecommunications and has been a faculty member at the Faculty of Electrical Engineering and Information Technologies, University Ss. Cyril and Methodius, since 1996. He currently serves as a Professor and has held roles including Vice-Dean for Science and International Cooperation (2008–2016). His research focuses on telecommunications, cybersecurity, blockchain applications in education, and IoT security. He has extensive industry experience, including internships at IBM T.J. Watson Research Center in the U.S. Education: Ph.D. in Telecommunications (2001–2004) M.Sc. in Telecommunications (1997–2000) Dipl. Ing. in Electronics and Telecommunications (1991–1996) Research Interests: Blockchain technology for academic credential verification Cybersecurity in tactical communication systems IoT energy efficiency and reliability Network intrusion detection using deep learning Anti-forgery systems using AI and blockchain Publications Trends: Over 50 publications since 2000, with recent focus on blockchain applications in education, cybersecurity frameworks for 5G networks, and IoT energy optimization. His work bridges theoretical advancements with practical implementations in telecommunication infrastructure. Awards: No specific awards listed, though his contributions to blockchain-based educational systems and cybersecurity research are notable. Advising & Grants: No listed students, but active in research projects funded by industry partnerships. Collaborations include IBM Research and initiatives in Macedonia's telecommunication sector. Labs/Teams: Affiliated with the Institute of Telecommunications at his faculty, focusing on network security and emerging technologies.

Michael ReimerView profile

Associate Professor

• Quantum Optics
• Quantum Photonics
• Semiconductor Nanowires
• +3 more

Michael Reimer is an Associate Professor at the University of Waterloo, affiliated with the Institute for Quantum Computing (IQC). His primary role involves advancing quantum photonic technologies through experimental and theoretical research. He is a full-time faculty member with expertise in semiconductor nanowire-based devices, quantum dot systems, and their integration with atomic ensembles for quantum communication applications. His research interests focus on developing high-efficiency single-photon sources and detectors, metamaterials for photonic applications, and leveraging cold atoms in hollow-core fibers to enhance quantum state manipulation. He also explores hybrid quantum-classical systems, particularly in optimizing signal-to-noise ratios (SNR) and mitigating nonlinear impairments in optical networks. His work bridges fundamental quantum optics with practical implementations in quantum computing and secure communication systems. Recent articles highlight trends toward achieving near-unity absorption in metamaterials, on-demand photon generation with quantum dots, and probabilistic constellation shaping for optical networks. While no scientific awards are explicitly mentioned, his contributions to quantum photonic devices are notable. No specific grants or advisees are detailed in the provided text, but his affiliation with IQC suggests involvement in collaborative research projects. He is affiliated with the Institute for Quantum Computing, a leading academic unit at the University of Waterloo.

Mujdat CetinView profile

Professor

• Computational Imaging
• Signal Processing
• Machine Learning
• +5 more

Mujdat Cetin is a Professor of Electrical and Computer Engineering at the University of Rochester, serving as the Robin and Tim Wentworth Director of the Goergen Institute for Data Science and Director of the New York State Center of Excellence in Data Science. Previously, he held faculty positions at Sabanci University, Istanbul, Turkey, and MIT. He earned his BS from Bogazici University (1993), MS from the University of Salford (1995), and PhD from Boston University (2001). His research focuses on computational imaging, signal processing, and machine learning applications in biomedical imaging, radar systems, and neuroscience. Key areas include uncertainty quantification in imaging, probabilistic methods for image analysis, and brain-computer interfaces. His work bridges electrical engineering, computer science, and biomedical applications. Notable awards include the IEEE Signal Processing Society Best Paper Award and the Turkish Academy of Sciences Distinguished Young Scientist Award. He is an IEEE Fellow and has held editorial roles for journals like IEEE Transactions on Computational Imaging and SIAM Journal on Imaging Sciences. His contributions span conference leadership, including Technical Program Co-chair roles for major signal processing and fusion events. Cetin’s research group has advanced computational sensing, medical imaging algorithms, and EEG-based emotion/motor imagery classification. Ongoing work emphasizes integrating physics-based models with deep learning for robust imaging and signal analysis.

Stephen ArrowsmithView profile

Professor

• Seismoacoustics
• Infrasound Propagation
• Earthquake Detection
• +3 more

Stephen Arrowsmith is a Professor and Hamilton Chair in Earth Sciences at Southern Methodist University (SMU). His research focuses on seismoacoustics, infrasound propagation, and geophysical monitoring of natural and anthropogenic phenomena. He holds a Ph.D. from the University of Leeds and has contributed significantly to nuclear test monitoring, atmospheric dynamics, and machine learning applications in geophysics. Key research areas include: Integration of seismic and acoustic data for event detection and discrimination Analysis of infrasound signals from earthquakes, explosions, and bolide impacts Development of automated detection algorithms using machine learning Urban seismology and distributed acoustic sensing Recent work emphasizes multi-modal data fusion, with studies on the Korean Peninsula, Tonga eruptions, and North Korean nuclear explosions. His contributions include advancing global infrasound networks and improving stratospheric atmospheric modeling through infrasound observations. He maintains an active research website at allthespheres.com .

• Haptics
• Human-Computer Interaction
• Acoustic Engineering
• +3 more

Yasutoshi Makino is a researcher specializing in ultrasound-based haptics, tactile feedback systems, and human-computer interaction. He has collaborated extensively with Hiroyuki Shinoda and other colleagues, focusing on mid-air haptic displays, noncontact object manipulation, and sensory reproduction. Research Interests Makino's work explores the intersection of acoustics, neuroscience, and engineering to create immersive tactile experiences without physical contact. His innovations include ultrasound-driven actuation mechanisms, thermal sensation rendering, and real-time human motion prediction for robotic systems. Recent Publications The 15 most recent articles highlight advancements in airborne ultrasound tactile displays, texture synthesis via GANs, and applications in guide dog training analysis, virtual reality, and interactive robotics. Key themes include dynamic pressure control , multi-stimulus integration , and low-latency systems . Collaborations Co-authored with Masahiro Fujiwara (43 papers) Collaborated with Hiroyuki Shinoda (145 papers) Worked with Shun Suzuki, Takaaki Kamigaki, and Ryoya Onishi on thermal and mechanical haptic feedback systems.

Balu SanthanamView profile

Professor

• Signal Processing
• Communications
• Fractional Fourier Analysis
• +4 more

Balu Santhanam is a Professor in the Department of Electrical and Computer Engineering at the University of New Mexico. He is affiliated with the Signal Processing and Communications research groups. His academic journey includes a PhD from Georgia Institute of Technology (1998), an MS from Georgia Tech (1994), and a BS from Saint Louis University (1992). Research interests span signal representations, ICA-SVM hybrid systems, discrete fractional Fourier analysis, and applications in SAR vibrometry. He has received notable awards, including the ECE Distinguished Teacher Award (2000, 2005) and the Lawton Ellis Award (2012). His work includes 3 U.S. patents related to signal processing and SAR imagery. Teaching focuses on digital signal processing, probability theory, and multirate systems. His research emphasizes chirp parameter estimation, SAR-based vibration detection, and robust communication systems. Key contributions include advancements in DFRFT applications and clutter suppression techniques. Education: PhD (Georgia Tech, 1998), MS (Georgia Tech, 1994), BS (Saint Louis University, 1992) Labs/Teams: Signal Processing Group, Communications Research Team

• Electronics
• Optics
• Physics
• +8 more

Dr. Cristina de Dios Fernández is an Associate Professor at Carlos III University of Madrid, affiliated with the School of Engineering and the Department of Electronic Technology . She leads the research group Sensors and Instrumentation Techniques (SIT) and holds an ORCID iD 0000-0001-5474-7407 . Research Interests span Photonics , Terahertz Technologies , Optical Frequency Combs , Quantum Sensing , Biomedical Optics , and Integrated Photonics . Her work focuses on Developing compact confocal microscopes for nitrogen-vacancy centers Advancing dual-comb spectroscopy for biomedical and industrial applications Optimizing VCSEL-based optical frequency combs Designing photonic chips for THz dual-comb spectrometers Projects & Grants include principal investigator roles in initiatives like Cátedra Universidad-Empresa EPIQ (2024-2027) and HYPERTERA (2019-2020), alongside researcher roles in EU-funded programs such as OILTEBIA (2013-2017) and CELTA (2016-2020). Patents include Hyperspectral Imaging based on Dual Frequency Comb (2022), and she supervised the thesis VCSEL-based Optical Frequency Comb Generation, Expansion and Optimization (2016).

• Optoelectronics
• Liquid Crystal Technologies
• Visible Light Communication (VLC)
• +4 more

Juan Carlos Torres Zafra is a Visiting Professor at Universidad Carlos III de Madrid. His research focuses on optoelectronics, liquid crystal technologies, visible light communication (VLC), and sensor systems. His work spans interdisciplinary areas including energy-harvesting IoT nodes, indoor positioning systems, and optical communication interfaces for high-definition media transmission. Torres Zafra has contributed to advancements in semiconductor materials (e.g., perovskites), low-cost sensor networks, and hybrid RF-VLC positioning systems. His research also extends to educational technology, exploring tools like Telegram and Google Workspace for improving student engagement in cybersecurity engineering programs. Notable projects include the GUTI group's work on optical vortices using liquid crystal devices and the development of tunable resonators based on liquid crystal capacitance. His publications from 2020–2025 highlight trends in VLC system optimization, AI-driven disinformation detection (SmartVote-AI initiative), and medical studies on amyloidosis therapy outcomes. Torres Zafra’s work often emphasizes practical applications in robotics, automotive systems, and sustainable energy solutions. While no formal awards are listed, his extensive publication record (over 80 entries from 2004–2025) reflects sustained contributions to photonics, sensor engineering, and liquid crystal device innovation. His research integrates hardware design, algorithm development, and material science to address challenges in modern communication systems and assistive technologies for visually impaired patients.

• Nanomedicine
• Targeted Drug Delivery Systems
• Antimicrobial Peptides
• +7 more

Rohan Shah is a Lecturer at Swinburne University of Technology's Department of Chemistry and Biotechnology, School of Science, Computing and Emerging Technologies. He holds a PhD from Swinburne, supported by the Victoria-India Doctoral Scholarship, and was awarded the Sparrho Early Career Researcher Prize for lipid nanoparticle work. His research focuses on nanomedicine, antimicrobial peptides, and sustainable biotechnology solutions for global health challenges. He has held academic roles at Swinburne and RMIT, including Lecturer and Academic Tutor, and is a registered pharmacist and Chartered Member of the Royal Australian Chemical Institute (RACI). Dr. Shah's research explores targeted drug delivery systems, systems biology, and metabolomics applications in food and environmental science. He has secured significant grants (e.g., $1.2M+ in external funding) and collaborates globally. His editorial roles include Frontiers in Sustainable Food Systems, Metabolites, and Food Science and Nutrition Cases. He has authored over 100 publications, with recent work addressing PFAS toxicity in wildlife, food additive health impacts, and nanoformulated drug delivery. Professional activities include serving as Treasurer of the RACI's Early Career Chemists Group and committee roles in the Young Chemists Group. His work spans 15+ years of grants, 99+ publications, and supervision of four HDR students. He advocates for food additive reformulation, sustainable technologies, and improved drug delivery systems.

Patrick VogelView profile

Researcher

• Magnetic Particle Imaging
• Medical Imaging
• Nano-Optics
• +3 more

Dr. Patrick Vogel is a Habilitation candidate and researcher in the Magnetic Particle Imaging (MPI) group at the University of Würzburg's Faculty of Physics and Astronomy, Department of Experimental Physics V. His work focuses on advancing MPI technology for clinical applications, including imaging safety assessments, interventional procedures, and nanoparticle-based diagnostics. He contributes to the development of portable MPI scanners and hybrid imaging systems, collaborating with the AG Behr research group. His research spans magnetic particle spectroscopy, vascular imaging, and biomaterial characterization. Vogel has pioneered studies on MPI-guided endovascular interventions and the application of MPI in perfusion models. His work bridges physics, biomedical engineering, and clinical practice, with a focus on translating MPI into real-world medical diagnostics and surgery support. Key projects include the design of human-sized MPI scanners, safety evaluations of medical implants, and the use of synthetic tracers like Synomag®. He collaborates with interdisciplinary teams to address challenges in vascular imaging, nanoparticle behavior analysis, and real-time imaging systems.

• Stochastic Simulation
• Optimization
• Machine Learning
• +5 more

Giulia Pedrielli is an Associate Professor at Arizona State University's School of Computing and Augmented Intelligence, with affiliations as a Senior Global Futures Scientist. She holds a Ph.D., M.Sc., and B.S. in Mechanical and Industrial Engineering from Politecnico di Milano, Italy. Her research focuses on stochastic simulation, optimization, and machine learning applications in biomanufacturing, digital twins, and cyber-physical systems. She has contributed to frameworks for pandemic modeling (PySIRTEM), RNA design, and high-dimensional optimization. Pedrielli has collaborated with institutions like NUS and UC Berkeley, and her work spans biomedical engineering, supply chain resilience, and security of critical infrastructure. Recent articles emphasize co-simulation tools, AI-driven logic translation, and falsification methods for CPS security. Her teaching includes advanced stochastic simulation courses and thesis supervision across multiple disciplines. Education: Ph.D. Mechanical Engineering, Politecnico di Milano, Italy M.Sc. Industrial Engineering, Politecnico di Milano, Italy B.S. Industrial Engineering, Politecnico di Milano, Italy Research interests integrate simulation-based optimization with machine learning, particularly in safety-critical systems like healthcare and smart infrastructure. She develops digital twin methodologies for real-time control under uncertainty, leveraging Gaussian processes and Bayesian approaches. Pedrielli's work bridges theoretical advancements (e.g., BASSO optimization algorithm) with practical applications in biomanufacturing and pandemic response.

Anthony RizzoView profile

Assistant Professor

• Integrated photonics
• Quantum photonics
• Neuromorphic photonics
• +4 more

Anthony Rizzo is an Assistant Professor of Engineering at Dartmouth College, leading the Rizzo Integrated Photonic Systems Laboratory. His research focuses on integrated photonics, quantum photonics, and neuromorphic photonics, with applications in high-speed data communication, quantum computing, and energy-efficient systems. He holds a PhD in Electrical Engineering from Columbia University (2022), an MS from Columbia (2019), and a BS in Physics from Haverford College (2017). His work has been funded by organizations such as the Toyota Research Institute and the U.S. Army Research Laboratory. Key research areas include silicon photonics for ultra-low energy optical interconnects, photonic-electronic integration, and novel photonic materials like aluminum nitride. Notable achievements include the first demonstration of a Kerr comb-driven silicon photonic link and advancements in 3D photonic integration for terabit-scale data links. His lab explores applications in quantum sensing, neuromorphic computing, and visible wavelength photonics for atomic systems. Funding Sources: Toyota Research Institute, U.S. Army Research Laboratory, Thayer School of Engineering, AIM Photonics Courses Taught: ENGS 23 (Distributed Systems and Fields), ENGS 60 (Solid-State Electronic Devices) Recent publications highlight breakthroughs in ultra-low loss waveguides, scalable photonic linear neurons, and energy-efficient modulators. His work bridges fundamental photonics research with practical applications in next-generation communication and computing systems.

Kwaku DayieView profile

Professor

• RNA structural biology
• Nuclear Magnetic Resonance (NMR) spectroscopy
• Biophysical methods
• +7 more

Kwaku Dayie is a Professor in the Department of Chemistry and Biochemistry at the University of Maryland. His research focuses on RNA structural biology, NMR spectroscopy, and biophysical methods to study RNA dynamics and function. He leads a lab developing advanced NMR techniques for large RNA molecules and has contributed to understanding RNA's role in catalysis, gene regulation, and viral processes. Education: B.A., Physics with Honors, 1990, Hamilton College Ph.D., Biophysics, 1996, Harvard University Postdoctoral, MIT (1998), Scripps Research Institute (2000) Research Interests: The structural basis of RNA signaling in pathogenic bacteria, RNA viruses (HIV, HBV), and long noncoding RNAs. His lab develops isotopic labeling methods and NMR tools to study RNA dynamics and function, aiming to guide RNA-based drug design. Awards: Henry C. Welcome Fellowship (2008) National Technical Association Nsoroma Technology Award (2007) Jane Coffin Childs Memorial Fund Postdoctoral Fellowship (1998) Grants & Service: NIH review panelist (2012-2018), NSF reviewer (2005-2006), and judge for Intel ISEF (2003). Serves on editorial boards for Molecules and NPG Scientific Reports (2018). Labs & Teams: Directs an interdisciplinary lab focused on RNA structural biology, collaborating on NMR method development and RNA-drug interaction studies.

Shuvra S. BhattacharyyaView profile

Professor

• Signal Processing
• Embedded Systems
• Biomedical Engineering
• +3 more

Shuvra S. Bhattacharyya is a Professor at the University of Maryland, College Park (UMD), Department of Electrical and Computer Engineering, with a joint appointment in UMIACS. He is also a part-time visiting professor at Tampere University (Finland) and INSA Rennes (France). His research focuses on signal processing systems, embedded systems, biomedical engineering, and machine learning. He has authored 7 books and over 300 papers, and directs the Maryland DSPCAD Research Group. He holds an NSF Career Award and is an IEEE Fellow. His honors include the Fulbright Senior Specialist and FiDiPro Professorship. He advises graduate students and leads projects in neural decoding, cyber-physical systems, and criminal justice AI. Education: B.S., University of Wisconsin-Madison Ph.D., University of California, Berkeley Research Interests: Signal processing architectures, biomedical circuits, embedded software, hardware/software co-design, and AI for healthcare and criminal justice. His work emphasizes real-time systems, energy efficiency, and interdisciplinary applications. Grants & Awards: NIH Grant for real-time neural decoding (2023) IEEE Fellow (2011) Jimmy Lin Entrepreneurship Award (2012) Labs & Teams: Maryland DSPCAD Research Group, collaborating on dynamic data-driven systems, neural interface technologies, and AI ethics in criminal justice. His work integrates academic and industrial partnerships, including roles at Hitachi America and Kuck & Associates.