Professor Andrew Doherty is a prominent academic in the Faculty of Science at the University of Sydney, specializing in quantum information science and quantum computing. His research focuses on quantum error correction, quantum control, and foundational aspects of quantum mechanics, particularly involving quantum trajectories and entanglement. He leads projects within the Sydney Nanoscience Hub (SNH), contributing to advancements in superconducting qubits and topological codes. His work bridges theoretical and experimental quantum physics, with grants including the 'Quantum and Advanced Technologies' project (2024) and the ARC Training Centre for Future Leaders in Quantum Computing (2023). His publications emphasize scalable error suppression, photonic qubit systems, and code concatenation strategies, reflecting a commitment to both fundamental science and applied quantum technologies. Research Themes: Quantum error correction, quantum measurement theory, topological codes, and superconducting circuits. Key Collaborations: Involvement with international teams in quantum computing and nanoscience. Labs/Teams: Active member of the Sydney Nanoscience Hub (SNH). Professor Doherty's contributions span over 100 articles, with recent work addressing noise-aware decoding and Gottesman-Kitaev-Preskill (GKP) states. His research aims to advance fault-tolerant quantum computing and deepen understanding of quantum correlations.
Gavin Brennen is a Professor in Quantum Information Science (Core) at Macquarie University's School of Mathematical and Physical Sciences. He leads the Macquarie Centre for Quantum Engineering (MQCQE) and serves as a Chief Investigator at the Australian Research Council (ARC) Centre of Excellence for Engineered Quantum Systems (EQUS). He is also an Executive Board Member of the Sydney Quantum Academy (SQA). His research focuses on quantum computing, quantum sensing, and atomic physics, with a particular emphasis on quantum error correction and quantum LDPC codes. Key roles and affiliations include directorship of MQCQE, leadership in ARC EQUS, and SQA board membership. He has secured funding for multiple research projects, including Sydney Quantum Academy scholarships (e.g., Brennen/Gharat and Brennen/Vedl) and the Engineered Quantum Matter initiative. His work addresses quantum technologies' applications in sensing, computing, and communication. Research interests span quantum computing architectures, quantum error correction protocols, and atomic systems. Notable projects include high-rate quantum LDPC codes for neutral atom registers, cavity-based quantum gates, and quantum internet protocols. His contributions to quantum crypto-economics and blockchain security further highlight his interdisciplinary impact. He has advised on projects such as the Australian Dark Matter Detector for High-Mass Axions and collaborates internationally. Current efforts prioritize scalable quantum systems, fault-tolerant protocols, and quantum networking. His lab and teams drive innovation in quantum hardware and theoretical frameworks for emerging technologies.
Kavan Modi is a Professor at the School of Physics and Astronomy, Monash University. His research focuses on quantum information theory applied to dynamics, metrology, computation, thermodynamics, and relativity. He leads the Monash Quantum Information Science (MonQIS) group and serves as Director of the Centre for Quantum Technology at Transport for NSW (2022–2024). Education: B.Sc. Engineering Physics (Embry-Riddle Aeronautical University, 2001), M.A. Physics (University of Texas at Austin, 2004), Ph.D. Physics (University of Texas at Austin, 2008). Postdoctoral positions included the Centre for Quantum Technologies (Singapore, 2008–2011) and Clarendon Lab, Oxford (2011–2013). Joined Monash in 2014. Research interests center on quantum dynamics, non-Markovian processes, and their applications in quantum computing and information science. Projects include developing error correction codes, quantum algorithms for network analysis, and mitigating correlated noise in quantum systems. He has authored over 111 publications, with recent work emphasizing non-Markovian characterization, quantum process tomography, and topology-based quantum algorithms. Awards and grants include leadership in multiple Australian Research Council projects. Advising/Grants: Primary Chief Investigator in projects like 'Quantum Software Platform' (2023–2026) and 'Mitigating Correlated Noise in Quantum Machines' (2020–2021). Supervises graduate students and collaborates globally on quantum information science. Labs/Teams: MonQIS group focuses on foundational and applied quantum research, integrating theory and experimental collaborations.
Kwan-Wu Chin is a Professor in the School of Electrical, Computer and Telecommunications Engineering at the University of Wollongong, where he also serves as Head of Postgraduate Studies (HPS) and co-directs the Wireless Technologies Lab (WTL). His research focuses on resource allocation problems in Internet of Things (IoT) systems, maritime networks, edge computing platforms, and integrated sensing-communication systems. Chin leads an active research group currently supervising five PhD students working on UAV networks, edge computing, maritime systems, and metaverse resource allocation. He has graduated over 20 PhD students who now hold positions in academia and industry. Chin serves as editor for Elsevier Computer Communications and IEEE Internet of Things Journal. His work develops optimization techniques using graph theory, stochastic processes, and machine learning for next-generation wireless systems.
Professor Yue Rong is a Full Professor at Curtin University's Department of Electrical and Computer Engineering, within the School of Electrical Engineering, Computing and Mathematical Sciences. He holds editorial roles at IEEE Transactions on Signal Processing and IEEE Wireless Communications Letters. His research focuses on signal processing for communications, underwater acoustic systems, wireless networks, and healthcare IoT. Rong has authored over 140 journal and conference papers and received multiple awards, including the 2010 Young Researcher of the Year Award. Education: B.E. (Electrical Engineering), Shanghai Jiao Tong University (1999) M.Sc. (Electrical Engineering), University of Duisburg-Essen (2002) Ph.D. (Electrical Engineering), Darmstadt University of Technology (2005) Research Interests: Rong's work spans cooperative MIMO communications, underwater acoustic systems, OFDM modulation, radar-based healthcare monitoring, and secure wireless protocols. His innovations include adaptive modulation schemes for underwater environments and radar-based vital signs detection. Recent trends in his publications emphasize AI-driven signal processing for healthcare IoT and underwater optical communication systems. Awards: Best Paper Awards (WCSP 2011, APCOMM 2010) Chinese Government Award (2004) DAAD/ABB Fellowship (2001-2002) Grants & Labs: His research is supported by grants focusing on UAV-enabled data collection and underwater network optimization. He leads projects in the Distributed Data Fusion and Emerging Technologies (DDFE) lab, advancing radar-cardiography and wearable health monitoring systems.
Dr. Ying He is a Senior Lecturer at the School of Electrical and Data Engineering, University of Technology Sydney (UTS). Her research focuses on wireless communication networks, particularly integrating machine learning with satellite and terrestrial systems. She holds a BEng from Beijing University of Posts and Telecommunications (2009) and a PhD from UTS (2017). Prior to her academic role, she worked on TD-LTE chip design at the Chinese Academy of Sciences. Affiliations : Faculty of Engineering and Information Technology Global Big Data Technologies Centre (GBDTC) Education : BEng in Telecommunications Engineering, Beijing University of Posts and Telecommunications (2009) PhD in Engineering (Telecommunications), UTS (2017) Her research interests include satellite communication (GEO-LEO integration), spectrum sharing, vehicular communication, and applying machine learning to physical layer algorithms. Notable contributions include optimizing beam design in LEO networks and developing secure IoT systems. She supervises PhD/Master’s students and teaches courses like CCNA and capstone projects. Funded projects span satellite networks, IoT security, and supply chain tracking. Recent grants include SmartSat CRC initiatives and collaborations with industry partners like Intel and Ericsson. Her work addresses challenges in 6G, UAV-enabled computing, and resilient quantum algorithms.
Dr. James Saunderson is a Senior Lecturer and Director of Education in the Department of Electrical and Computer Systems Engineering at Monash University. He holds a PhD in Electrical Engineering and Computer Science from MIT and has held postdoctoral roles at Caltech and the University of Washington. His expertise spans convex optimization, semidefinite programming, and quantum information theory. Education : PhD in EECS, MIT (2015) MS in EECS, MIT (2011) Bachelor of Engineering (Honours) and Bachelor of Science (Honours), University of Melbourne (2008) Research Interests : Convex optimization, quantum information theory, signal processing, and algorithm design. Focuses on algebraic and geometric aspects of optimization, with applications in engineering and quantum systems. Recent Projects : Exploiting duality in quantum relative entropy optimization Hyperbolic programming and conic optimization Applications in nanotechnology and bioinformatics Teaching : Courses include Control System Design, Signals and Systems, and Optimization for Engineers. Awards : SIAM Optimization Best Paper Prize (2020) Grants and Collaborations : Australian Research Council Discovery Early-Career Research Fellow (2020–2024) Leading projects in quantum optimization and bioengineering applications.
Professor Simon Devitt is Research Director of the Centre for Quantum Software and Information (QSI) at the University of Technology Sydney's Faculty of Engineering and Information Technology, School of Computer Science. He also holds several prestigious international appointments including InstituteQ Visiting Chair of Excellence in Quantum Technologies at Aalto University, Finland, and visiting positions at RIKEN in Japan. As a leading figure in quantum computing research, he directs the Australian Quantum Software Network and co-founded quantum education startup Eigensystems Pty Ltd. His educational background includes: PhD in Physics from University of Melbourne (2004-2007) BSc (Hons) in Physics from University of Melbourne (2000-2003) Professor Devitt's research spans quantum software, quantum architecture, and quantum error correction, with a focus on making quantum computing practical at scale. His work addresses fundamental challenges in quantum computing architecture when scaled to millions or billions of qubits. He has pioneered approaches to quantum error correction, resource estimation, and quantum network design, particularly through his leadership of the Quantum Technology at Scale (QTS) research group. His research bridges theoretical foundations with practical implementation challenges, aiming to shape the evolution of quantum technology over the coming decades. His recent publications demonstrate a strong focus on practical quantum computing challenges, with particular emphasis on error correction techniques, resource estimation, and quantum architecture. A significant portion of his work addresses the surface code and its variants, exploring ways to optimize qubit usage and error rates. He has also made important contributions to quantum networking, particularly through the concept of "quantum sneakernet," and to quantum education and standardization efforts that will be critical for the emerging quantum industry. His notable awards and recognitions include: Fellow of the Australian Institute of Physics Fellow of the Royal Society of New South Wales Warren Prize from the Royal Society of NSW InstituteQ Visiting Chair of Excellence in Quantum Technology Professor Devitt actively mentors numerous PhD students, postdocs, and researchers through his Quantum Technology at Scale group. His research is supported by significant funding from diverse sources including Google Academic Research Awards, Sydney Quantum Academy, DARPA, and the Japanese Society for the Promotion of Science. He has led projects on quantum sneakernet networks, quantum algorithm benchmarking frameworks, and quantum software tools that address critical challenges in the field. He leads the Quantum Technology at Scale (QTS) research group at UTS, which focuses on the design and architectural challenges of quantum computing and communications technology at scale. The group includes researchers working on quantum computing architectures, quantum networking (Rottnest Quantum Sneakernet project), and quantum software (Quokka project). The team collaborates extensively with international partners including Aalto University in Finland, University of New South Wales, Keio University in Japan, and industry leaders like Rigetti Computing.
Professor Jinho Choi is a Chair and Professor in Radio Frequency at the School of Electrical and Mechanical Engineering, University of Adelaide, Australia. He holds a B.E. (magna cum laude) from Sogang University, and M.S.E. and Ph.D. degrees from KAIST. His research focuses on advancing wireless communication and sensing technologies, particularly in IoT, 5G/6G, non-terrestrial networks, and cognitive satellite systems. He authored three books and has been recognized with the 1999 EURASIP Best Paper Award, IEEE Fellowship, and inclusion in Stanford's Top 2% Scientists list since 2020. He currently serves as a Senior Editor of IEEE Wireless Communications Letters and editorial roles in multiple journals. Education: B.E. (Electronics Engineering) - Sogang University, Seoul (1989) M.S.E. (Electrical Engineering) - KAIST (1991) Ph.D. (Electrical Engineering) - KAIST (1994) Research Interests: Professor Choi's work addresses connectivity challenges in non-terrestrial networks, leveraging statistical signal processing and machine learning. Current projects include UAV-assisted LEO satellite technologies, cognitive satellite radios, and semantic communication protocols. His research aims to enhance global connectivity and efficiency in terrestrial and satellite networks. Publications: His recent work spans semantic communication, satellite quantum key distribution, federated learning optimization, and coverage diversity in mega constellations. These studies reflect trends in 6G-ready technologies, AI-driven communication systems, and hybrid satellite-terrestrial networks. Awards: 1999 Best Paper Award for Signal Processing (EURASIP) IEEE Fellow (Leadership in technical excellence) World’s Top 2% Scientists (Stanford University, 2020–present) Grants & Supervision: As a senior academic, he oversees grants in wireless innovation and has advised numerous students on advanced communication systems. His lab focuses on next-generation networks, integrating theoretical insights with practical implementations. Labs/Teams: Active in interdisciplinary teams at the University of Adelaide, collaborating on projects funded by industry and government to bridge gaps between academic research and real-world applications.
Dr. Dominic Williamson is a theoretical quantum physicist and DECRA Research Fellow at the School of Physics, University of Sydney. He specializes in quantum phases of matter and their applications to quantum error correction and computing. His work bridges condensed matter theory and quantum information science, focusing on fracton topological phases and fault-tolerant quantum architectures. Education: PhD in Physics from the University of Vienna (2017); Postdoctoral research at Yale University, Stanford University, and IBM Quantum. Current roles include faculty membership at the University of Sydney’s Quantum Science Group and prior industry experience at IBM and PsiQuantum. Research interests: Topological phases of matter, quantum error correction codes (e.g., fracton codes, QLDPC systems), fault-tolerant quantum computing architectures, and non-Abelian anyon systems. Recent breakthroughs include low-overhead quantum architectures and novel approaches to parallelized logical measurements. Grants: 2022 ARC Discovery Early Career Researcher Award for topological phases in quantum computation. Collaborations include projects on gauging logical operators and quantum code surgery. Professional activities: Editor for Quantum , frequent speaker at international conferences, and mentor for students at all levels (undergraduate to postdoctoral). Active in open-source research and public engagement through platforms like arXiv and Google Scholar.
Associate Professor Mahyar Shirvanimoghaddam is a distinguished academic at The University of Sydney's School of Electrical & Computer Engineering, specializing in IoT, Telecommunications, and Coding Theory. His research focuses on 6G communication strategies, ultra-reliable low-latency systems, and machine learning integration in wireless networks. He holds a PhD from The University of Sydney and has received multiple accolades, including the World Economic Forum's Young Scientist award (2018) and the Australian Award for University Teaching (2020). Education: B.Sc. (1st Class Honors) in Electrical Engineering, University of Tehran (2008) M.Sc. (1st Class Honors) in Electrical Engineering, Sharif University of Technology (2010) PhD in Electrical Engineering (Telecommunications), The University of Sydney (2015) Research Interests: IoT Communication Protocols, Rateless Coding, Non-Orthogonal Multiple Access (NOMA), 5G/6G Technologies, and Federated Learning in Wireless Networks. His work on channel coding for massive IoT and URLLC has been funded by ARC Discovery Projects and European Research Council grants. He pioneered the 'Idea Factory' interdisciplinary teaching project, blending engineering and business education. Key projects include designing 6G communication strategies (ARC 2022-2024) and robust coding for mission-critical communications (ARC 2019-2021). Awards: Over 20 awards, including teaching excellence (Vice-Chancellor's Awards 2019, 2022), research recognition (IEEE Best Paper Awards), and leadership roles in IEEE and the Higher Education Academy. He supervises 1 PhD student (Tyseer BASHIR) and actively engages in editorial roles for IEEE Transactions and other journals. His team's innovations aim to bridge technological and societal challenges in IoT and smart infrastructure.
Professor Parastoo Sadeghi is a distinguished academic in the School of Engineering and Information Technology at the University of New South Wales (UNSW) Canberra, where she serves as Professor of Electrical Engineering. She joined UNSW Canberra in October 2020 after spending 15 years at the Australian National University (2005-2020). Professor Sadeghi received her bachelor's and master's degrees in electrical engineering from Sharif University of Technology, Tehran, Iran, in 1995 and 1997, respectively, and completed her Ph.D. in electrical engineering from UNSW Sydney in 2006. Professor Sadeghi's research spans several cutting-edge areas in information theory and communications, with particular emphasis on information theory , data privacy , network and index coding , wireless communications theory and systems , and spherical signal processing . Her work has resulted in over 200 refereed journal articles and conference papers, plus a book on Hilbert Space Methods in Signal Processing published by Cambridge University Press in 2013. Her recent publications demonstrate a strong focus on differential privacy mechanisms, information leakage analysis, and network coding optimization, with significant contributions to the theoretical foundations of these fields. Professor Sadeghi has held several prestigious positions in the academic community, including serving as Associate Editor for coding techniques for the IEEE Transactions on Information Theory (2016-2019), General Co-chair of the 2021 IEEE International Symposium on Information Theory in Melbourne, and as an elected member on the Board of Governors of the IEEE Information Theory Society (2019-2020). She has been a Senior Member of the IEEE since 2007 and has conducted research visits at leading institutions including the Technical University of Munich (2008) and MIT (2009, 2013, 2020). Her recent work shows increasing focus on privacy-preserving technologies and the theoretical foundations of secure communications, with numerous publications in top-tier venues. Senior Member of IEEE (since 2007) General Co-chair of 2021 IEEE International Symposium on Information Theory Associate Editor for IEEE Transactions on Information Theory (2016-2019) Elected member, IEEE Information Theory Society Board of Governors (2019-2020) Professor Sadeghi actively supervises graduate students in fundamental problems related to information theory, wireless communications, data privacy, and network coding. She offers competitive scholarships of $35,000 AUD for high-achieving PhD students with strong mathematical backgrounds. Her research group maintains strong international collaborations, as evidenced by her frequent research visits to top global institutions and numerous co-authored publications with international researchers. She continues to be an active contributor to the advancement of information theory and its applications to modern communication and privacy challenges.
Professor Sarah Johnson is a distinguished academic in the School of Engineering at the University of Newcastle, specializing in Electrical and Computer Engineering. She holds a PhD in Electrical Engineering from the same institution and has been awarded prestigious fellowships including an ARC Future Fellowship. Her research applies engineering solutions to digital information processing and error correction coding, with significant applications in secure communications and biomedical technologies. Her research interests span: Signal processing for secure data transmission Error correction codes for reliable communication systems Biomedical applications of digital signal processing Quantum-enabled secure communications Internet of Things communication protocols Her publications primarily focus on information theory, wireless communication systems, and biomedical engineering. Recent work shows strong emphasis on index coding optimizations, quantum cryptography implementations, and biomedical signal processing techniques for neuroimaging applications. Significant awards include: NSW Premier's Prize for Excellence (2017) Pro Vice-Chancellor's Research Excellence Award (2007) Professor Johnson has secured multiple ARC Discovery grants and industry-sponsored projects, including collaborations with Quintessence Laboratories on quantum key distribution. She co-founded HunterWISE to promote women in STEM fields and has supervised numerous graduate students across engineering disciplines. She leads interdisciplinary collaborations with biomedical researchers on rehabilitation technologies and neuroimaging analysis, developing systems to monitor recovery processes and brain activity patterns.
Dr. Vera Miloslavskaya is a Lecturer in Information Technology at the University of New England's School of Science and Technology. She holds a PhD from Peter the Great St. Petersburg Polytechnic University and specializes in error-correction coding and AI applications for telecommunications. Research Focus: Miloslavskaya develops machine learning-enhanced coding schemes for next-generation wireless systems. Her work on neural network-based polar coding and graph neural network applications in MIMO detection aims to improve reliability and efficiency in 6G networks. She maintains collaborations with the University of Sydney where she previously worked as a Postdoctoral Research Associate. Recognition: Awarded the IEEE Transactions on Communications Exemplary Reviewer (2022) and multiple Russian academic awards including the Gold Medal of the Russian Academy of Science (2012).
Xiaoyu Ai is a Researcher at the School of Electrical Engineering and Telecommunications at the University of New South Wales (UNSW Kensington). His work bridges telecommunications engineering with quantum communication technologies. Bachelor of Engineering (Xidian University, 2013) Master of Engineering Science (UNSW, 2015) PhD in Telecommunications (UNSW, 2022) A specialist in quantum key distribution (QKD), Xiaoyu Ai focuses on channel coding for satellite-based QKD systems, including the development of LDPC codes and multithreaded reconciliation algorithms. His research extends to wireless communication protocols for mining IoT applications and scalable LoRa mesh networks. Recent work includes quantum emitter integration in hexagonal boron nitride for secure communication hardware. Key publications highlight his contributions to quantum cryptography, satellite communication, and industrial IoT. Notable projects include the CRC-P initiative for LoRa-based backup systems in the mining industry and collaborations in quantum networking with institutions like University of Technology Sydney. His technical expertise spans secure communication protocols, photonic device optimization, and low-light multimedia algorithms, as evidenced by recent conference presentations.
