جستجوی استاد راهنمای دانشگاهی

Alex Mironenkoمشاهده پروفایل

استادیار

• Catalysis
• Computational Chemistry
• Quantum Mechanics
• +۷ مورد دیگر

Dr. Alex Mironenko is an Assistant Professor in the Department of Chemical and Biomolecular Engineering at the University of Illinois at Urbana-Champaign. His research focuses on developing quantum mechanical methods to predict catalytic behaviors for renewable energy and chemical production. He leads the Mironenko Lab, which emphasizes computational models for heterogeneous catalysis, reactive force fields, and nanozyme design. Education: PhD in Chemical Engineering, University of Delaware (2018) Kadanoff-Rice Postdoctoral Scholar, University of Chicago (2018-2020) MS in Chemical Engineering, University of Kansas (2012) Diploma of Engineer, Omsk F.M. Dostoevsky State University, Russia (2009) Research Interests: Computational heterogeneous catalysis Reactive force fields derived from first principles Low-dimensional metal oxide catalysts Nanozymes and biomimetic catalysis Selective C-C coupling for CO₂ valorization Improving density functional theory accuracy Awards: ACS Petroleum Research Fund Doctoral Investigator Award (2021) Allan P. Colburn Outstanding Dissertation Prize (2019) Kadanoff-Rice Postdoctoral Fellowship (2018-2020) Advising and Grants: Advised PhD student Neil Tran (publication on methanol carbonylation mechanisms) Funded by NSF, ACS, and industry partnerships Labs/Teams: Mironenko Virtual Catalysis and Quantum Chemistry Lab Collaborations with institutions like University of Chicago and industry partners

• Hardware Security
• Side-Channel Attacks
• Cryptography
• +۳ مورد دیگر

Martin Brisfors is a part-time researcher at KTH Royal Institute of Technology since 2019 and a PhD student in the Department of Electrical Engineering and Computer Science (EECS) since 2022. He is affiliated with the Division of Electronics and Embedded Systems and works in Kista. His research focuses on hardware security and side-channel attacks, with a particular emphasis on cryptographic implementations and countermeasure design. His work spans topics such as post-quantum cryptography (e.g., CRYSTALS-Kyber), AES vulnerability analysis, and the application of deep learning in side-channel attacks. He has contributed to evaluating the efficacy of countermeasures like clock randomization and duplication, uncovering fundamental flaws in their implementation. Brisfors has collaborated on courses such as Hardware Security (IL1333) and Hardware Security (FIL3030) , demonstrating his involvement in both research and education. His publications (2019–2024) reflect a consistent focus on advancing hardware security through empirical analysis and novel attack methodologies.

• Mobile and cloud computing
• Energy-efficient computing
• Image and video processing
• +۲ مورد دیگر

Yung-Hsiang Lu is a Professor of Electrical and Computer Engineering at Purdue University's Elmore Family School of Electrical and Computer Engineering. His research focuses on mobile/cloud computing, energy-efficient computing, and image/video processing. He holds a BSEE from National Taiwan University (1992), an MSEE (1996), and a PhD (2002) from Stanford University. Dr. Lu's academic background includes significant contributions to VLSI and circuit design, with primary emphasis on computer engineering. His work spans theoretical and applied domains, including optimizing neural networks for edge devices, securing deep learning models, and leveraging large language models for software development. Recent research trends in his articles emphasize energy efficiency in AI systems, interdisciplinary applications of transformers (e.g., music analysis), and challenges in model interoperability and security. His publications also highlight innovations in global camera networks and real-time visual data analysis. While no specific grants or awards are explicitly mentioned, his extensive list of publications reflects sustained academic engagement. His educational contributions include developing C programming resources and teaching large-scale image processing using global camera networks. Dr. Lu's professional address is at Purdue's Materials and Electrical Engineering Building in West Lafayette, Indiana, where he maintains an active research lab focused on embedded systems and low-power computing innovations.

Kevin Lynchمشاهده پروفایل

استاد

• Robotic Manipulation
• Robot Locomotion
• Physical Human-Robot Interaction
• +۴ مورد دیگر

Kevin Lynch is a Professor of Mechanical Engineering and Director of the Center for Robotics and Biosystems at Northwestern University. He holds a Ph.D. in Robotics from Carnegie Mellon University and a B.S.E. in Electrical Engineering (with honors) from Princeton University. His research focuses on robotic manipulation, robot locomotion, physical human-robot interaction, and distributed control of robot swarms. He has pioneered advancements in exoskeleton control, swarm formation algorithms, and haptic interaction frameworks. Professor Lynch has received significant recognition, including the IEEE Fellow distinction (2010), the Harashima Award (2017), and the Charles Deering McCormick Professor of Teaching Excellence award (2007–2010). He serves as Editor-in-Chief of the IEEE Transactions on Robotics and has authored over 150 peer-reviewed publications. Key contributions include the development of safety-aware human-robot collaboration systems and self-healing swarm control algorithms. He created the ME 333 Introduction to Mechatronics course and the Mechatronics Design Laboratory, fostering interdisciplinary robotics education. His lab, the Center for Robotics and Biosystems, integrates biomechanics with advanced robotics to address challenges in rehabilitation and autonomous systems.

• Antennas and Propagation
• Electromagnetics
• Wireless Networks
• +۴ مورد دیگر

Can Ding is an Associate Professor in the School of Electrical and Data Engineering at the University of Technology Sydney (UTS), affiliated with the Faculty of Engineering and IT. He is a core member of the Global Big Data Technologies Centre (GBDTC). Ding holds a BEng in Microelectronics from Xidian University (2009) and a joint PhD in Electromagnetic Fields and Microwave Technology from Xidian University and Macquarie University (2016). His research focuses on engineering electromagnetics, particularly in base station antennas for 5G/6G networks, cross-band interference mitigation, and antenna array design. He has led numerous industry-collaborative projects, including ARC-funded initiatives, and has over 120 publications in top-tier journals/conferences, featured in IEEE's 'What’s Hot in Antennas and Propagation.' Teaching highlights include coordinating foundational electrical engineering courses and studio subjects, recognized with UTS's 2023 'Mid-Career Educator of the Year' award. He actively contributes to professional societies like IEEE AP-S, serving as an editor and conference organizer. His awards include the ARC DECRA grant (2020), Top 2% World Scientist (2023), and multiple outstanding reviewer distinctions. His grants include 'Advancing Millimeter-Wave Base Station for 6G' (ARC DP, 2025–2027) and 'Maximizing 5G Signal Transparency' (UTS Bluesky, 2024). Ding supervises students in antenna design and has mentored over a dozen researchers, many of whom have won international conference awards.

Joshua Marshallمشاهده پروفایل

استاد

• Field Robotics
• Autonomous Vehicles
• Control Systems Engineering
• +۷ مورد دیگر

Joshua Marshall is a Professor of Electrical & Computer Engineering at Queen’s University, Canada, and Director of the Offroad Robotics research group. He holds a PhD from the University of Toronto and has cross-appointments in Mechanical & Materials Engineering and the Robert M. Buchan Department of Mining. His expertise spans field robotics, autonomous systems, control engineering, and harsh-environment applications in mining, space, and marine domains. He led the Ingenuity Labs Research Institute (2018–2024) and served as a Visiting Professor at Örebro University (2016–17). Dr. Marshall’s work focuses on autonomous vehicle navigation, robotic excavation, and spatiotemporal mapping. He has received the 2025 OPEA Engineering Medal and has commercialized technologies through partnerships with companies like Epiroc and RockMass Technologies. Education: PhD, Electrical & Computer Engineering, University of Toronto (2005) MSc(Eng), Mechanical Engineering, Queen’s University (2001) BSc (Hons), Engineering, (details not specified) Research Interests: Autonomous robotics in mining, space, and marine environments Data-driven control systems and model predictive control Proprioceptive sensing and terrain classification Multi-robot coordination and task planning Underground navigation and SLAM Professional Activities: Senior Member, IEEE Editorial roles: International Journal of Robotics Research , IEEE Transactions on Mechatronics Co-founded the NSERC Canadian Robotics Network (NCRN) Contributions to the IEEE Medal for Environmental & Safety Technologies Committee Labs/Teams: Offroad Robotics Group (Queen’s University) Ingenuity Labs Research Institute (founding Director) Advisor to Queen’s AutoDrive Challenge II Team and aQuatonomous ASV Design Club

Stephanie Dodmanمشاهده پروفایل

دانشیار

• Teacher Learning and Leadership
• Critical Reflection and Inquiry
• Equity-Oriented Education
• +۲ مورد دیگر

Dr. Stephanie Dodman is an Associate Professor at George Mason University's College of Education and Human Development, specializing in teacher learning, leadership, and equity-oriented education. She serves as Assistant Dean for Academic Excellence in Student and Academic Affairs and leads the Advanced Studies in Teaching and Learning program. PhD in Curriculum, Teaching, and Teacher Education from the University of Florida Teaches master's and doctoral courses in curriculum and instruction Developed the Critical Data-Driven Decision Making (CDDDM) and Data Use for Equity (DUE) frameworks Her research focuses on leveraging teacher agency and data use to dismantle inequitable schooling systems, with publications in journals like Teaching and Teacher Education and Journal of Educational Change . Recent work emphasizes antiracist pedagogy, collaborative inquiry, and liminal spaces in teacher development. Dr. Dodman received the 2019 George Mason University Online Teaching Excellence Award. She actively engages in school-university partnerships and job-embedded professional development initiatives.

Weiwen Jiangمشاهده پروفایل

استادیار

• Quantum Computing
• AI Accelerators
• Hardware-Software Co-Design
• +۳ مورد دیگر

Weiwen Jiang is a tenure-track Assistant Professor in the Department of Electrical and Computer Engineering at George Mason University (GMU), affiliated with the College of Engineering and Computing (CEC). He leads the JQub lab, focusing on hardware/software co-design for computing systems, spanning classical (FPGAs, ASICs) and quantum computing applications in AI-driven fields like medical imaging and geophysics. Prior to GMU, he held a postdoctoral position at the University of Notre Dame and earned his PhD in Computer Science from Chongqing University with a joint PhD in Electrical and Computer Engineering from the University of Pittsburgh. His research emphasizes quantum computing, AI accelerators, and domain-specific computing. Notable achievements include the 2025 NSF CAREER Award, ACM Sigda Meritorious Service Award (2024), and IEEE QuantumWeek Best Paper Award (2023). His work is funded by NSF, DoE, ARO, Meta, and Leidos. He co-chaired IEEE QuantumWeek (2023–2025) and created workshops like StableQ at ESWEEK 2023. Key contributions include developing frameworks like QuPAD for quantum learning and JQub's AI-driven geophysical and medical imaging tools. His lab graduated Dr. Yi Sheng (now at University of South Florida) and Dr. Zhepeng Wang (Amazon Applied Scientist). Current research explores quantum machine learning, noise mitigation, and fairness in AI for edge devices.

Md. Tahmidul Islam Mollaمشاهده پروفایل

استادیار

• Wearable Technology
• Pervasive/Ubiquitous Computing
• Human-Computer Interaction
• +۱ مورد دیگر

Dr. Md. Tahmidul Islam Molla is an Assistant Professor of Practice and Director of Undergraduate Studies in the Department of Computer Science at Marquette University. He specializes in wearable technology, pervasive computing, human-computer interaction, and data science. Previously, he held a Postdoctoral Researcher position at Cornell University and earned his Ph.D. from the University of Minnesota in 2020. His teaching roles include instructing core and advanced courses in computer science, data science, and embedded systems. He leads the NSF S-STEM project at Marquette, providing scholarships for low-income graduate students transitioning into computing careers. Courses taught include COSC 1000, COSC 2100, COSC 4290/5290, COSC 5500, COSC 6500, and COSC 6510. Research interests focus on wearable systems, soft/flexible electronics, and on-skin interfaces. His work explores manufacturing techniques for e-textiles and user experience in thermal microclimate control. Collaborative projects include the development of SkinKit and WovenProbe for prototyping on-skin interfaces. Dr. Islam’s research has led to innovations in e-textile fabrication, including surface-mount methods and laundering-resistant designs. He actively contributes to conferences like ACM International Symposium on Wearable Computers and ACM Designing Interactive Systems.

Liping Liuمشاهده پروفایل

دانشیار

• Machine Learning
• Data Science
• Deep Learning
• +۳ مورد دیگر

Liping Liu is an Associate Professor in the Department of Computer Science at Tufts University's School of Engineering. He holds a Ph.D. from Oregon State University and has held postdoctoral positions at Columbia University and Tufts. His research focuses on machine learning, generative models, graph learning, and their applications in biochemical data analysis and fluid dynamics simulation. His work on graph generative methods earned the NSF CAREER Award. Education: Ph.D. (Oregon State University, 2016), M.Sc. (Nanjing University, 2009), B.S. (Hebei University of Technology, 2006). Research Interests: Machine Learning, Deep Learning, Generative Models, Time Series, Graph Learning. Dr. Liu's research emphasizes probabilistic modeling and neural networks, addressing challenges in graph generation, data-driven physics simulation, and biochemical analysis. His recent work includes advancements in graph-based recommendation systems, turbulence modeling, and enzymatic reaction prediction. His publications span top AI conferences like NeurIPS, ICML, and ICLR. He has secured grants totaling over $9 million, including the NSF CAREER Award and NIH funding for metabolomics and enzymatic promiscuity studies. His teaching includes courses on generative models, deep learning, and machine learning for graph analytics. Awards: NSF CAREER Award (2023), NIH grants, DARPA ACT-NOW project (2019). Service: NSF panelist, program committee member for AAAI, NeurIPS, and IJCAI.

Lianying Zhaoمشاهده پروفایل

دانشیار

• Trusted Computing
• Hardware/Architectural Security
• Systems Security
• +۳ مورد دیگر

Lianying Zhao is an Associate Professor in the School of Computer Science at Carleton University and serves as a Director of the Carleton Computer Security Lab (CCSL). His research focuses on low-level platform security, including hardware, firmware, hypervisor, and operating systems, with an emphasis on trusted computing, authentication, privacy preservation, and security metrics. He leads the CCSL research group, collaborating with interdisciplinary teams to address critical security challenges in IoT, cloud systems, and web applications. Education: Not explicitly listed in provided texts. Roles: CCSL Director, Research Supervisor, and Graduate Program Advisor. Dr. Zhao’s work spans hardware security improvements, firmware vulnerability analysis, and user-centric security metrics. Recent research highlights include studies on router configuration habits, tracker detection in web browsers, and CVSS score discrepancies. He has supervised numerous graduate students in cybersecurity domains, contributing to over 30 peer-reviewed publications since 2013. His lab affiliations include CCSL and CISL, where he collaborates on projects such as secure deletion frameworks, TLS validation vulnerabilities, and hybrid decision-making models for cloud security. Current research also explores cross-regional login throttling mechanisms and AI-driven vulnerability detection in embedded systems.

Ulas Sunarمشاهده پروفایل

دانشیار

• Biomedical Engineering
• Medical Imaging Technologies
• Optical Imaging
• +۳ مورد دیگر

Ulas Sunar is the SUNY Empire Innovation Associate Professor in the Department of Biomedical Engineering at Stony Brook University, affiliated with the College of Engineering and Applied Sciences. His research focuses on developing quantitative optical imaging tools for neuroimaging and cancer imaging in both preclinical and clinical settings. Key areas include diffuse correlation spectroscopy (DCS), fluorescence imaging, and photodynamic therapy (PDT) monitoring. His work spans optical techniques for cerebral blood flow monitoring in traumatic brain injury (TBI), non-invasive imaging of tumor response to therapy, and device innovation such as FPGA-based real-time DCS systems. Collaborations involve interdisciplinary applications in oncology, neurology, and medical diagnostics. Notable contributions include clinical trials of time-gated DCS systems and studies on light-triggered drug release mechanisms. Research trends highlight advancements in optical imaging sensitivity, integration of therapeutic and diagnostic tools (theranostics), and translational studies linking preclinical models to clinical applications. His lab emphasizes multimodal approaches combining optical, ultrasound, and photoacoustic imaging for comprehensive tissue analysis. Awards and grants are not explicitly listed in the provided text, though his extensive publication record indicates sustained research impact. Advising and mentoring focus on graduate students in biomedical engineering and affiliated programs. He maintains a lab dedicated to optical imaging technologies, contributing to Stony Brook’s interdisciplinary research ecosystem.

• Software Engineering
• Artificial Intelligence
• AI Ethics
• +۳ مورد دیگر

Pekka Abrahamsson is a Professor at the Faculty of Information Technology and Communication Sciences at Tampere University , Finland. He actively contributes to research in Software Engineering , Artificial Intelligence , and AI Ethics , with recent work focusing on generative AI, multi-agent systems, and ethical software design. Published over 42 research outputs (2016–2025) Editorial roles in multiple international conferences (2016, 2019, 2022–2024) His research emphasizes practical applications of AI in software development, including tools like ChatGPT for full-stack coding, multi-agent systems for requirements engineering, and frameworks for AI ethics in software practices. He also explores challenges in continuous software engineering and quantum computing architecture. Key publication trends (2024–2025) include: Agile methodologies enhanced by AI Ethical alignment in AI systems Autonomous software development platforms AI tool adoption in programming education Quantum software architecture reviews Technical debt in embedded systems Awards and recognitions : PlumX Metrics highlight 1 scientific prize (unspecified) High readership on platforms like Mendeley (up to 211 readers) Multiple citations in Scopus (up to 53 citations for quantum computing work) Grants and collaborations include global studies on work-from-home impacts, AI tool usage in programming courses, and projects like CodePori for autonomous development. His work influences policy and industry practices, particularly in AI ethics and multi-robot systems.

Sean Ehrlichمشاهده پروفایل

دانشیار

• Political Economy
• Globalization
• European Union Studies
• +۳ مورد دیگر

Sean Ehrlich is an Associate Professor of Political Science at Florida State University's Department of Political Science, part of the College of Social Sciences and Public Policy. He earned his Ph.D. from the University of Michigan (2004) and a B.A. from the University of Chicago (1998). His research focuses on political economy, globalization, democratic institutions, and trade policy, particularly in the context of the European Union. His notable works include Access Points: An Institutional Theory of Policy Bias and Policy Complexity (2011), which won the APSA Gladys M. Kammerer Award, and The Politics of Fair Trade (2018). His research examines how institutional structures influence trade policy, interest group lobbying, and public perceptions of trade agreements. He has published in journals like International Organization , European Union Politics , and Business and Politics . Ehrlich's service roles include editorial positions at International Interactions and Global Studies Quarterly , and leadership in academic committees such as the APSA's International Collaboration Section. He has advised over a dozen doctoral students, many now in academic or policy roles. His recent work explores populism's impact on trade policies and human rights advocacy in democracies. His awards include the Gladys M. Kammerer Award for groundbreaking contributions to U.S. national policy analysis. His research spans empirical studies on EU trade policy, comparative political economy, and experimental analyses of public opinion on trade compensation.

Bashir M. Al-Hashimiمشاهده پروفایل

استاد

• Energy-efficient mobile computing systems
• Low-power test and test-data compression of digital integrated circuits
• Energy-harvesting computing
• +۱ مورد دیگر

Professor Sir Bashir M. Al-Hashimi is currently Vice President (Research & Innovation) at King’s College London and holds the ARM Professorship in Computer Engineering there. He is also a Visiting Professor in Electronics and Computer Science at the University of Southampton. Prior to academia, he worked in the electronics design industry for eight years before joining the University of Southampton in 1999, where he became a personal Chair holder in 2004. His research focuses on energy-efficient computing systems, low-power testing, and energy-harvesting technologies, with a strong emphasis on smart city applications and wearable computing. He has led numerous interdisciplinary projects funded by the EPSRC and industry, including the PRiME Programme Grant and the EPSRC-funded Spatial Computational Learning consortium. He has supervised 45 PhD students and authored/co-authored nearly 400 technical papers, earning eight best paper awards and contributing to five books. His honors include a CBE (2018), knighthood (2025), Fellowship of the Royal Society (2023), and roles on the Research Excellence Framework panels. He founded the Arm-ECS industry-academia center in 2008, promoting energy-efficient computing research.