Find Academic Supervisors

Qun LiView profile

Professor

• Edge Computing
• Operating Systems
• Distributed Systems
• +3 more

Qun Li is a Professor of Computer Science at the College of William and Mary, leading the Edge Computing Laboratory. He holds an IEEE Fellow distinction and has served as Graduate Director (2010-2011). His research focuses on edge computing, operating systems, distributed systems, and security & privacy, with over 100 publications in top venues like ACM CCS, ICSE, and NSDI. Li has advised numerous PhD students, including Zhengrui Qin and Ed Novak, who now hold academic positions. He chairs conferences including ACM/IEEE Symposium on Edge Computing (SEC'22) and has editorial roles at IEEE Internet Computing and Transactions on Computers. Key awards include an NSF Career Award. His work emphasizes building prototype systems and addressing real-world challenges in edge computing and quantum networks. Education: PhD from Dartmouth College under Daniela Rus Research interests span edge computing architecture, secure deep learning, federated learning, and quantum computing applications. His Edge Computing Group explores scalable solutions for distributed systems and privacy-preserving technologies. Recent publications (2022-2024) focus on quantum networks, federated learning robustness, and privacy-preserving algorithms. A notable trend is integrating quantum computing with edge systems for enhanced security and efficiency. Awards: NSF Career Award (year unspecified), IEEE Fellow (year unspecified) Advised students have transitioned to academia and industry roles, reflecting Li's mentorship impact. Active in conference organization, he has led program committees for ACM SEC and IEEE ICDCS, while steering editorial boards in computer networks and systems. Current projects include quantum network routing and Byzantine-tolerant federated learning.

Sina VafiView profile

Senior Lecturer

• Wireless Communication
• Error Control Coding
• Forward Error Correction Codes
• +4 more

Dr Sina Vafi is a Senior Lecturer in the Department of Engineering at Charles Darwin University's Faculty of Science and Technology. His research focuses on advancing forward error correction (FEC) codes and their applications in wireless transmission systems, particularly for high-speed broadband and video compression. He leads the Wireless Research Group, developing codes optimized for transmission delay and error correction in noisy environments. Key research projects include the 'Maximum Power Extraction from Hybrid Solar-Wind System by Using Fuzzy Logic Approach' (2021–present). His work addresses sustainable energy systems alongside wireless communication innovations. Research interests span error engineering, FEC code design, video bitstream protection, and low-density parity check codes. His recent publications explore braided block codes, convolutional interleavers, and adaptive error protection schemes for HEVC videos. Dr Vafi has supervised 5 Higher Degree by Research (HDR) projects, including work by student investigator V.S. Borra on hybrid renewable energy systems. He is actively involved in mentoring postgraduate researchers and contributes to CDU’s wireless communication initiatives.

Apurva NarayanView profile

Adjunct Professor

• Artificial Intelligence
• Machine Learning
• Data Mining
• +6 more

Dr. Apurva Narayan is an Affiliate Professor in Computer Science and Data Science, and an Associate Member in Mechanical Engineering at the University of British Columbia's Irving K. Barber Faculty of Science. His research focuses on artificial intelligence, machine learning (particularly explainable AI and quantum ML), data mining, cybersecurity of cyber-physical systems, and decision-making under uncertainty. He holds a PhD from the University of Waterloo (Systems Design Engineering) and a Bachelor's in Electrical Engineering from Dayalbagh Educational Institute. Education: PhD in Systems Design Engineering, University of Waterloo (2015) Bachelor of Engineering in Electrical Engineering, Dayalbagh Educational Institute (2008) Research Interests: Explainable AI/ML and quantum machine learning Data analytics and mining Safety/security of cyber-physical systems Graph-theoretic analysis of complex systems Decision-making under uncertainty Reverse engineering complex software systems Awards: Systems Society of India Young Scientist Award (under 40) MITACS Accelerate Award (2013) Dr. T.E. Unny Memorial Award (2011) Multiple teaching nominations at University of Waterloo Advising & Grants: Supervises graduate students in AI/ML and cybersecurity. Secured grants including MITACS Accelerate and Waterloo scholarships. Active in patent filings related to timed regular expressions. Labs/Teams: Engaged in collaborations within the UBC Department of Computer Science and cross-disciplinary projects with Mechanical Engineering on system reliability and quantum computing applications.

Natalia NikolovaView profile

Professor

• Microwave and millimeter-wave imaging and detection
• Inverse problems
• Computational electrodynamics
• +6 more

Natalia K. Nikolova is a Professor and Canada Research Chair (Tier 2) in High-frequency Electromagnetics at the McMaster University Faculty of Engineering, Department of Electrical and Computer Engineering. Author of Introduction to Microwave Imaging (Cambridge University Press, 2017) Develops cognitive radar systems for concealed weapon detection and microwave scanners for breast cancer screening Commercialization with Patriot One Technologies Ltd. Education: Dipl. Eng. (Radioelectronics), Technical University of Varna, Bulgaria (1989) Ph.D. (Electrical Engineering), University of Electro-Communications, Tokyo, Japan (1997) NSERC Postdoctoral Fellowship (1998-1999) Research Focus: Microwave and millimeter-wave imaging systems for biomedical and security applications through computational electromagnetism and inverse scattering analysis. Her Electromagnetic Vision Laboratory (founded 1999) develops high-speed sensor arrays and computer-aided design tools. Scientific Contributions: Elevated to IEEE Fellow (2011) for sensitivity analysis methods Delivered 50+ international lectures as Distinguished Microwave Lecturer (2010-2013) Holder of 7 patents in microwave imaging technology

Xiaoli MaView profile

Academic

• Advanced Materials Design
• Porous Materials (MOFs, Zeolites, Carbons)
• Polymer-Based Nanocomposites
• +4 more

Xiaoli Ma is an Affiliate Assistant Professor in the School of Freshwater Sciences and an Assistant Professor in the Materials Science & Engineering Department at the University of Wisconsin–Milwaukee (UWM). His research focuses on advanced materials for separation, purification, and sensor technologies, with a strong emphasis on porous materials like metal-organic frameworks (MOFs), zeolites, and carbons, as well as polymer-based nanocomposites and membranes. His work bridges fundamental material science and applied engineering, targeting improvements in water purification, gas separation, and membrane fabrication. Education: PhD in Materials Science and Engineering, Arizona State University (2015) MS in Materials Science and Engineering, Tongji University, China (2009) BS in Materials Science and Engineering, Tongji University, China (2006) Research Interests: Design and characterization of porous materials (MOFs, zeolites, carbons) Development of functional membranes for water/gas separation Nanocomposite materials and their integration into devices Vapor-phase processing techniques like atomic layer deposition (ALD) Publications Trends: Recent work emphasizes covalent organic framework (COF) membranes for ion selectivity (2024), ceramic membranes for PFAS removal (2023), and ZIF-based gas separation systems (2023–2020). His articles span membrane fabrication methods, material synthesis innovations, and applications in environmental and energy sectors. Labs/Teams: Leads a research group exploring novel materials for industrial and environmental applications, focusing on scalable synthesis and real-world deployment of advanced membranes and adsorbents.

Han Mao KiahView profile

Assistant Professor

• Coding Theory
• Combinatorics
• Information Theory
• +1 more

Han Mao Kiah is an Assistant Professor at Nanyang Technological University , specializing in Coding Theory and Combinatorics . He earned his Ph.D. in Mathematics at NTU under Yeow Meng Chee and held a postdoctoral position at the Coordinated Science Lab, University of Illinois at Urbana-Champagne with Olgica Milenkovic . Current Role: Assistant Professor, NTU, Department of Mathematics Education: Ph.D. in Mathematics (NTU), Postdoc (University of Illinois) His research focuses on Coding Theory for applications in DNA-based data storage , Reed-Solomon codes , and combinatorial designs . Recent work includes Private Information Retrieval , Sequence Reconstruction , and Error Correction in distributed systems. Key trends in his publications involve Reed-Solomon codes , Private Information Retrieval , and DNA sequence profiling with a focus on Efficient Algorithms and Constrained Coding for error control in emerging storage systems. ISITA Early Career Researcher Paper Award (2022, Researcher: D. T. Dao) Memorable Paper Award Finalist (2021, Student: J. Chrisnata) Best Student Paper Award (2020, Student: J. Chrisnata) Student Paper Award Finalist (2012)

Minesh PatelView profile

Assistant Professor

• Computer Architecture
• Memory Systems
• Hardware Security
• +3 more

Minesh Patel is an Assistant Professor at Rutgers, The State University of New Jersey. His research focuses on computer architecture, memory systems, and hardware security, with a particular emphasis on DRAM reliability, RowHammer vulnerabilities, and in-memory computing. He has contributed to frameworks like DRAM Bender and NEON , which explore novel hardware-software co-design approaches. His work bridges theoretical analysis with experimental validation, addressing challenges in modern memory systems such as error mitigation, latency reduction, and security exploits. Recent projects include studying RowHammer under temperature variations and exploring resistive RAM-based neural networks. He has also published in medical informatics, analyzing surgical outcomes during the pandemic, suggesting interdisciplinary collaboration interests. Patel's research has implications for both academic and industry applications, including cloud computing security and embedded systems optimization. His publications span journals and conferences in computer engineering, cybersecurity, and healthcare analytics.

Wei LeView profile

Associate Professor

• AI
• Machine Learning
• Software Engineering
• +5 more

Dr. Wei Le is an Associate Professor in the Department of Computer Science at Iowa State University. His primary affiliations include the Program Analysis & AI Lab and collaborative work with Mayo Clinic. He holds a Ph.D. in Computer Science from the University of Virginia (2010). His research focuses on the intersection of AI and software engineering, particularly in trustworthy AI systems, vulnerability detection, and program analysis. Key areas include AI for medicine, analyzing AI models, and improving software reliability through techniques like dataflow analysis and symbolic execution. Recent work emphasizes efficient vulnerability detection using deep learning (e.g., ICSE 2024), numerical instability in ML applications (FSE 2025), and GPU numerical testing (SC 2024). His research has been supported by NSF, Google, and DARPA. Notable awards include the Distinguished Paper Award at FSE 2016 and Best Presentation at FSE 2008. He has advised over 10 students and collaborates with institutions like Columbia University and UCLA. Teaching responsibilities include courses on program analysis (COM S 413/513), principles of programming languages, and advanced AI topics. He actively contributes to conferences as a PC member and area chair (e.g., ICSE, FSE).

• Electromagnetic Fields
• RFID Technology
• Internet of Things (IoT)
• +3 more

Luca Catarinucci is an Associate Professor in Electromagnetic Fields (ING-INF/02) at the University of Salento's Department of Innovation Engineering. He leads courses in Microwaves and Electromagnetic Solutions for Hi-Tech , focusing on IoT, RFID, and 3D-printed electronic devices. His research spans electromagnetic interactions with biological systems, RFID sensor integration, and additive manufacturing for high-frequency applications. He has co-authored over 200 publications, including 80+ journal articles and 4 book chapters, and holds patents in RFID technology. His work bridges academic research and industry applications, emphasizing practical solutions for wireless communication and environmental monitoring. Education: Laurea in Electrical Engineering from the University of Perugia (1998). Professional roles include Researcher at the University of Salento (2004–2015) and collaboration with ICEMB (Interuniversity Center for Electromagnetic Field Studies). His expertise includes electromagnetic simulation, antenna design, and IoT-enabled systems. Research interests: RFID technology, IoT infrastructure, microwave engineering, 3D-printed antennas, and electromagnetic characterization of novel materials. Projects include smart waste management systems, thermal comfort monitoring, and worker safety solutions using RFID and sensor networks. Labs/Teams: Part of the Department of Innovation Engineering's research groups focused on electromagnetic design, IoT, and additive manufacturing. Collaborates with industry partners on projects involving 3D-printed RF devices and energy-autonomous sensors.

Robert RandView profile

Assistant Professor

• Quantum Computing
• Formal Verification
• Quantum Programming
• +3 more

Robert Rand is an Assistant Professor of Computer Science at the University of Chicago, affiliated with the Programming Languages Research Group and the Chicago Quantum Exchange . His research bridges programming languages, formal verification, and quantum computation. Dr. Rand focuses on Quantum Computing , Formal Verification , and Quantum Programming . He develops tools like QWIRE for quantum circuit representation and VOQC for verified quantum compilers. Current work includes a textbook on verified quantum programming. His publications span quantum compiler verification, algebraic quantum languages, and formal methods in quantum computing. Recent projects involve error-correction, type systems, and quantum-classical interoperability through Qunity . Scientific Awards 2023 AFOSR Young Investigator Research Program Award France and Chicago Collaborating in the Sciences Award 2022 Keynote Speaker, Compiler Construction Distinguished paper awards: PLDI 2021, POPL 2019 Victor Basili Postdoctoral Fellowship (UMD) Dr. Rand actively collaborates on NSF-funded EPiQC (Enabling Practical-Scale Quantum Computing) and teaches advanced topics in quantum programming languages. He is currently working on a textbook on verified quantum programming and maintains active research groups in both Programming Languages and Quantum Computing.

Gavrilovska LiljanaView profile

Associate Professor

• Telecommunications
• Mobile Edge Computing (MEC)
• Blockchain Technology
• +8 more

Liljana Gavrilovska is an Associate Professor at the Faculty of Electrical Engineering and Information Technologies (FEIT) of Ss. Cyril and Methodius University of Skopje (UKIM), specializing in the Department of Telecommunications. Her work focuses on advanced telecommunications systems, including 5G/Beyond 5G networks, mobile edge computing (MEC), blockchain applications in healthcare and IoT, cognitive radio networks, and network virtualization. She leads research groups addressing challenges in wireless resource management, energy efficiency, and distributed consensus mechanisms. Her research interests span telecommunications infrastructure , blockchain for healthcare systems , IoT optimization , and network slicing . Recent work includes developing the BloHeS consensus mechanism for blockchain systems and the Shapeshifter framework for MEC latency optimization. She also investigates dynamic spectrum allocation strategies and energy-efficient WuR-based IoT protocols. Publications emphasize practical implementations like the CHEST COPD e-Health platform and the FALCON project for virtualized network resource allocation. While no specific awards are listed, her contributions to open-source solutions like eWALL and SmartWine reflect industry engagement. Advising activities and grants are not explicitly detailed in the provided texts, though her involvement in EU projects like 5G-MEC and cognitive radio initiatives suggests significant collaborative work. Current projects include system design for blockchain-based public healthcare systems and analysis of heterogeneous network performance in LTE and DVB-T coexistence scenarios. She is actively involved in the FEIT Telecommunications Institute, contributing to both academic and applied research in telecommunications engineering.

• Computer Architecture
• Reliable Computer Design
• Fault Detection and Recovery
• +3 more

Gülay YALÇIN is an Assistant Professor at Abdullah Gul University since 2016. Prior to this, she held a post-doctoral position at the Barcelona Supercomputing Center (BSC) from 2014-2015 and was a researcher there from 2009-2014. She obtained her Ph.D. from Universitat Politècnica de Catalunya in 2014, focusing on Computer Architecture. Her academic background also includes an M.S. from TOBB University (2007) and a B.S. from Hacettepe University (2003), both in Computer Engineering. Education: Ph.D.: Universitat Politècnica de Catalunya, Department of Computer Architecture (2008-2014) M.S.: TOBB University of Economics and Technology, Computer Engineering (2007) B.S.: Hacettepe University, Computer Engineering (2003) Research Interests: Computer Architecture Reliable Computer Design Fault Detection and Recovery Parallel Computer Architectures Hardware Transactional Memory Low-Power Designs Her work emphasizes improving system reliability through innovative fault tolerance mechanisms and energy-efficient computing solutions. Scientific Awards: ParaDIME Project Shortlisted for the 2016 Innovation Radar Prize Advising and Projects: Supervised: Albert Njoroge Kahira (M.S. Candidate) on "Designing Reliable Microarchitectures According to Application Requirements" Project Roles: Researcher in ParaDIME (2012-2015) and Velox (2008-2011)

• Mechanical Engineering
• Metrology
• Biomedical Engineering
• +5 more

Roman Szewczyk is a Professor at the Institute of Metrology and Biomedical Engineering within the Faculty of Mechatronics at Warsaw University of Technology (Politechnika Warszawska). He also maintains an affiliation with the Łukasiewicz Research Network – Industrial Research Institute for Automation and Measurements PIAP. His academic career spans over two decades since earning his doctorate in 2003. Professor Szewczyk's research interests are highly interdisciplinary, focusing on the intersection of mechanical engineering, materials science, and biomedical applications. His primary expertise lies in magnetic sensors, metrology, and the development of measurement systems. He has made significant contributions to understanding magnetostrictive effects, magnetic permeability in electrical steels, and the application of finite element methods for sensor development. His work bridges theoretical physics with practical engineering applications, particularly in the fields of automation and biomedical instrumentation. An analysis of his recent publications reveals a strong focus on precision measurement systems, magnetic sensor development, and materials characterization. His work spans from fundamental physics of magnetoelastic effects to practical applications in robotics, biomedical devices, and environmental sustainability. The consistent publication output across multiple domains demonstrates his ability to integrate knowledge from diverse fields to solve complex engineering problems. With an impressive record of 342 publications and an h-index of 18 (Scopus) and 17 (Web of Science), Professor Szewczyk has established himself as a significant contributor to his fields of expertise. His work has practical applications across various industries including medical technology, power systems, and precision manufacturing. Professor Szewczyk has supervised 120 promoted theses, indicating his substantial contribution to academic mentoring and the development of future engineers. His involvement in 4 research projects demonstrates his ability to secure funding and lead research initiatives. While specific grant details aren't provided in the available information, his publication record suggests successful acquisition of research funding to support his extensive work. His laboratory work appears to focus on precision measurement systems, particularly those involving magnetic phenomena. The research group likely maintains facilities for materials testing, sensor development, and computational modeling, given the nature of his publications. The connection to the Institute of Metrology and Biomedical Engineering suggests strong capabilities in precision instrumentation and biomedical applications of engineering principles.

• Power Electronics
• Wireless Power Transfer
• Electric Vehicle Technology
• +4 more

Nikolay Dimitrov Madzharov is a Professor at the Department of Electronics, Faculty of Electrical Engineering and Electronics, Technical University of Gabrovo. His work focuses on power electronics, wireless power transfer systems, and electric vehicle charging infrastructure. He has led and participated in numerous international and national projects, including modernization of educational institutions and development of energy-efficient systems. Research Interests: Wireless power transfer, inductive resonance systems, electric vehicle technology, energy storage systems, and control systems in energy. Projects: Over 7 projects, including 'Optimal Design and Management of Electrical Energy Storage Systems' and 'Intelligent Mechatronic, Eco- and Energy-Saving Systems and Technologies.' His research emphasizes practical applications, such as contactless charging stations and high-efficiency energy converters. Madzharov has authored 4 books and over 96 publications, including journal articles and conference papers on topics like resonant inverters and battery management systems. He has advised 6 doctoral students, contributing to advancements in power electronics and energy systems. His work has been presented at international conferences such as PCIM, ICEST, and SIELA, showcasing innovations in wireless energy transfer and system reliability.

Paulius RaubaView profile

Lecturer

• Machine Learning
• Data Science
• Artificial Intelligence
• +3 more

Paulius Rauba is a Visiting Lecturer at ISM University of Management and Economics and a PhD candidate in Machine Learning at the University of Cambridge. He holds a BSc from ISM and an MSc from the University of Oxford, where he is also an Oxford Shirley Scholar. His research focuses on fundamental machine learning, model evaluation, robustness, and quantitative social science. He teaches courses in Econometrics, Data Science, and Elements of Artificial Intelligence. Paulius leads Gauss, a company specializing in deploying machine learning models, and has advised the European Commission on AI systems. His work spans academia, industry, and international organizations, emphasizing data-driven solutions for business and social challenges. Education: BSc, ISM University of Management and Economics MSc, University of Oxford His research explores model robustness, AI applications in healthcare, and conflict analysis through statistical and neural methods. Recent articles address topics like self-healing ML frameworks and context-aware model testing. Paulius is committed to advancing AI ethics and practical deployment. Awards: Oxford Shirley Scholar As a leader in Gauss, he bridges academic innovation with industry needs, focusing on scalable AI solutions. His advisory roles and grants underscore his interdisciplinary impact.