جستجوی استاد راهنمای دانشگاهی

Ciara Raffertyمشاهده پروفایل

مدرس ارشد

• Applied Cryptography
• Post-Quantum Cryptography
• Homomorphic Encryption
• +۴ مورد دیگر

Dr. Ciara Rafferty is a Senior Lecturer at Queen's University Belfast's School of Electronics, Electrical Engineering and Computer Science, affiliated with the Centre for Secure Information Technologies. She leads research in advanced cryptography, focusing on post-quantum systems, homomorphic encryption, and hardware acceleration. Her work includes quantum-safe cryptography projects like the UK Quantum Communications Hub and AQuASeC (Innovate UK). She co-teaches CSC2056 - Systems Security and Cryptography and actively supervises PhD students. Dr. Rafferty is a Senior Member of IEEE and an EPSRC SPRITE+ Expert Fellow. Research Interests: Homomorphic Encryption Post-Quantum Cryptography Cryptographic Hardware Architectures Privacy-Preserving Technologies Side-Channel Attack Mitigation Key Projects: UK Quantum Communications Hub (Phase 2) SAFEcrypto (H2020 Project) AQuASeC (Toshiba Europe-funded) SEQURED (Rolls Royce-funded) Awards: Senior Member of IEEE EPSRC SPRITE+ Expert Fellow Advising & Grants: PhD Supervision: Shabnam K (Secure Cloud Computation) Funding: EPSRC, Innovate UK, Industry Partners Lab/Teams: Centre for Secure Information Technologies (CSIT), collaborating on hardware-accelerated cryptography and quantum-safe systems.

Abolfazl Hashemiمشاهده پروفایل

استادیار

• Large-Scale Optimization
• Machine Learning
• Artificial Intelligence
• +۶ مورد دیگر

Abolfazl Hashemi is an Assistant Professor in the Elmore Family School of Electrical and Computer Engineering at Purdue University, directing the MINDS Group. He holds a B.Sc. from Sharif University of Technology (2014), and M.S.E. and Ph.D. degrees from The University of Texas at Austin (2016, 2020). His research focuses on Large-Scale Optimization for AI/ML, Learning at the Edge, and Decision-Making under Uncertainty, with applications in Federated Learning, Medical Image Analysis, and Cyber-Physical Systems. He leads the MINDS Group and collaborates with EnCORE and ICON centers. Key research areas include optimizing algorithms for machine learning, robustness in distributed systems, and adversarial learning. He has developed algorithms with mathematical guarantees for efficient deployment under resource constraints. Teaching includes Optimization for Deep Learning (graduate) and undergraduate courses like ECE 20001. He advises the Purdue RoboMaster robotics team and has mentored students through programs like SURF and Summer Stay Scholars. Outreach activities include fostering diversity through robotics competitions and research fellowships. His work bridges theoretical optimization with practical AI applications, emphasizing equitable and robust solutions in federated and decentralized learning.

• Cyber-Physical Systems
• Wireless Communications
• Statistical Signal Processing
• +۴ مورد دیگر

Husheng Li is a Professor of Aero and Astro Engineering at Purdue University's School of Aeronautics and Astronautics. He holds a PhD in Electrical Engineering from Princeton University and bachelor's and master's degrees in Electronic Engineering from Tsinghua University. Education: PhD in Electrical Engineering, Princeton University BS and MS in Electronic Engineering, Tsinghua University Research Interests: Dr. Li's work focuses on autonomous and connected systems , UAV sensing and communications , and joint design of control and communication systems . His research integrates cyber-physical systems , statistical signal processing , and wireless communications , with recent emphases on integrated sensing and communications (ISAC) , MIMO systems , and waveform optimization . His innovations span OTFS modulation , secure ISAC networks , and multi-functional waveform design . Publications: His articles explore cutting-edge topics like waveform sensitivity analysis , spectral efficiency in ISAC , and secure communication protocols . His work bridges theoretical information theory with practical system implementations , often validated through experimental demonstrations. Grants & Advising: While specific grants or student advisees are not detailed here, his research aligns with major trends in autonomous systems and 6G communication technologies . His lab likely contributes to Purdue's broader efforts in smart infrastructure and cyber-physical systems .

Anil N. Hiraniمشاهده پروفایل

استاد

• Differential Equations
• Numerical Analysis
• Computational Topology
• +۵ مورد دیگر

Anil N. Hirani is a Professor in the Department of Mathematics at the University of Illinois at Urbana-Champaign (UIUC), affiliated with the College of Liberal Arts & Sciences. He holds a PhD from the California Institute of Technology (2003) in Computer Science with minors in Mathematics and Control and Dynamical Systems. His academic journey includes roles as Assistant Professor (Computer Science, UIUC, 2005–2013) and Associate Professor (Mathematics, UIUC, 2013–2022) before becoming a full Professor in 2022. His research focuses on the interplay between geometry/topology and algorithms, with emphasis on structure-preserving discretizations of exterior calculus and differential geometry. Key areas include Discrete Exterior Calculus (DEC), numerical methods for PDEs, computational topology, and machine learning applications. He has organized workshops, such as the 2025 Discrete Exterior Calculus workshop at IMSI, and contributed to software like PyDEC. Education: PhD, Caltech (2003); MS in Computer Science (Stanford); Undergraduate degree in Computer Science (BITS Pilani, India). Awards include the NSF CAREER Award (2007–2012). Teaching includes courses on Differential Geometry (MATH 423), Vector and Tensor Analysis (MATH 481), and Computational Mathematics (MATH 490). He has advised numerous PhD students, notable among them Kaushik Kalyanaraman and Vaibhav Karve. Articles span DEC applications in fluid dynamics, cohomology computations, and machine learning. His work bridges theoretical foundations with practical applications in engineering and computer science.

• 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.

David L. Darmofalمشاهده پروفایل

استاد

• Computational Fluid Dynamics
• Numerical Analysis
• Uncertainty Quantification
• +۳ مورد دیگر

David L. Darmofal is the Vice Chancellor for Undergraduate and Graduate Education and the Jerome C. Hunsaker Professor of Aeronautics and Astronautics at MIT. He leads the Aerospace Computational Science & Engineering (ACSEL) Lab and contributes to the MIT Center for Computational Science & Engineering (CCSE). His research focuses on computational methods for PDEs (especially fluid dynamics) and engineering education innovation. He holds a BS from the University of Michigan and SM/PhD from MIT, with postdoctoral work at the University of Michigan. Notable awards include the MacVicar Faculty Fellow (2004), Earll M. Murman Award (2011), and NSF CAREER Award (1998). Education: B.S.E., University of Michigan, 1989 S.M., MIT, 1991 Ph.D., MIT, 1993 Affiliations: MIT Schwarzman College of Computing Aerospace Computational Design Laboratory (ACSEL) His research emphasizes higher-order adaptive finite element methods, space-time mesh adaptation, and turbulence modeling. He teaches courses in computational methods and fluid dynamics. Recent projects include the Metris open-source meshing software and studies on sonic boom propagation. His work bridges computational science and engineering education, with a focus on evidence-based pedagogy. Awards & Recognition: Michael M. Byram Visiting Professorship (2021) Common Ground Excellence in Teaching Award (2024) AIAA Student Chapter Teaching Awards (2005, 2013) Bisplinghoff Fellow & Alumni Merit Award (2012) Advising & Grants: Over 130 peer-reviewed publications, leadership in MIT’s Common Ground initiative, and mentorship of postdocs/UROPs (e.g., Emily Williams, Lucien Rochery). Active in interdisciplinary collaborations, including DOE projects on physics-informed PDEs and NASA’s CFD Vision 2030 study.

Ang Kok Kengمشاهده پروفایل

دانشیار

• Structural Stability and Vibration
• Smart Adaptive Structures
• Computational Mechanics
• +۵ مورد دیگر

K.K. Ang is an Associate Professor in the Department of Civil and Environmental Engineering at the National University of Singapore (NUS) Faculty of Engineering. He has been affiliated with NUS since 1987 and currently serves as Director of the Centre for IT and Applications (CITA Engineering) within the Faculty of Engineering. Qualifications: BEng (1st Class) from University of Singapore (1977) MEng from National University of Singapore (1980) PhD from University of New South Wales (1987) His research focuses on structural stability and vibration , smart adaptive structures , very large floating structures , computational mechanics , and meshless methods . Recent publications analyze carbon nanotube composites, high-speed rail dynamics, and offshore structural interactions. His awards include the NUS Teaching Excellence Award , Engineering Educator Award , and the IES/IStructE Best Structural Paper Award . He has taught courses in Computing, Structural Mechanics, Steel Design, and Finite Element Methods. Professor Ang is a Singapore-registered Professional Engineer (1991) and serves on the Singapore Structural Steel Society council. His work bridges structural engineering, IT applications, and advanced computational modeling.

• Risk and Governance
• Digital Technology and Evidence
• Legal Regulation of Children and Youth
• +۶ مورد دیگر

Dr. Dale Ballucci is an Associate Professor in the Department of Sociology at Western University. Her research focuses on socio-legal studies, criminology, and policing, emphasizing qualitative methodologies. She examines how authorities use risk tools, digital technologies, and discretionary power in decision-making within criminal justice, immigration, and refugee systems. Education: PhD in Sociology from the University of Alberta Her research interests include risk governance, digital evidence, legal regulation of youth, immigration policy, intimate partner violence, human trafficking, and correctional decision-making. She aims to inform policy reforms to enhance equity in criminal justice practices. Her recent publications analyze crime analysts' expanding power, digital technologies' impact on sex crime policing, police responses to human trafficking, and risk-driven governance in policing strategies. These works highlight intersections between technology, policy, and procedural justice. No scientific awards are listed. No advising/grants details are provided in the text. Her work is associated with the Department of Sociology at Western University's Social Science faculty.

David Del Rey Fernándezمشاهده پروفایل

استادیار

• Numerical Simulation of PDEs
• Summation-by-Parts Methods
• Continuous and Discontinuous Galerkin Schemes
• +۲ مورد دیگر

David Del Rey Fernández is Assistant Professor and Pratt & Whitney Canada Chair in Industrial Artificial Intelligence in the Department of Applied Mathematics at University of Waterloo. His research develops efficient numerical algorithms for solving partial differential equations on high-performance systems. He holds a PhD from University of Toronto and previously worked at NASA Langley Research Center. Research focuses on robust numerical methods, mesh adaptation, and machine learning acceleration. His work includes entropy-stable schemes, summation-by-parts methods, and discretizations for compressible flows. Recent publications address Lyapunov-consistent discretizations and scalable reduced-order modeling.

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.

Mourad Zeghalمشاهده پروفایل

استاد

• Geotechnical Engineering
• Soil Mechanics
• Seismic Response Analysis
• +۳ مورد دیگر

Dr. Mourad Zeghal is a Professor in the Department of Civil and Environmental Engineering at Rensselaer Polytechnic Institute (RPI). His research focuses on computational geomechanics, seismic response monitoring, and geotechnical system identification. He leads projects addressing liquefaction mitigation, multiscale modeling of geosystems, and development of advanced computational tools for geotechnical analysis. Dr. Zeghal collaborates with RPI's Center for Network for Earthquake Engineering Simulation (CEES), Scientific Computation Research Center (SCOREC), and Inverse Problems Center (IPRPI). His work emphasizes reducing risks from natural hazards through improved design tools and model validation. Key projects include the Liquefaction Experiments and Analysis Projects (LEAP), which use centrifuge testing and machine learning to analyze soil behavior under seismic loads. Dr. Zeghal's research integrates experimental data with numerical simulations to enhance understanding of soil-structure interaction and lateral spreading during earthquakes. Research Interests: Soil liquefaction, multiscale modeling, inverse problem methods, computational geomechanics Key Collaborations: CEES, SCOREC, IPRPI, and global research networks Focus Areas: Centrifuge testing, model validation, seismic hazard mitigation His recent publications (2023–2025) highlight advancements in quantifying uncertainty in soil response, analyzing LEAP centrifuge experiments, and developing machine learning approaches for model calibration. Dr. Zeghal actively engages with industry and government labs to translate research into practical engineering solutions.

• Parallel and Distributed Computing
• High-Performance Computing (HPC)
• AI Hardware Acceleration
• +۴ مورد دیگر

Xiaodong Yu is an Assistant Professor in the Department of Computer Science at Stevens Institute of Technology (since 2023), leading the Advanced Parallel and distributEd Computing and Systems (APECS) lab. Previously, he served as an Assistant Computer Scientist at Argonne National Laboratory (2019–2023) and a Scientist-at-Large at the University of Chicago’s Consortium for Advanced Science and Engineering (2022–2023). He holds a Ph.D. in Computer Science from Virginia Tech (2019). His research focuses on parallel/distributed computing systems, next-generation AI hardware, high-performance MLSys for large language models (LLMs), and federated learning communication/privacy. Over 50 peer-reviewed publications appear in top-tier venues like HPDC, ICS, and SC. He leads NSF and DOE-funded projects, including an NSF CRII award (2024–2026) and Argonne LDRD initiatives. Technical leadership roles include serving on conference committees (ICS, SC, IPDPS) and review boards (IEEE TPDS). Key contributions include compressor frameworks for AI accelerators (e.g., DCT-based), MPI collective communication optimizations, and GPU-based ptychographic reconstruction. His work bridges hardware-software co-design for HPC and AI systems. Current advising includes five Ph.D. students at Stevens and prior mentorship of over 10 researchers at Argonne. Professional activities include institutional service (Stevens CS faculty search committee) and roles as finance chair (ISPASS), technical program committee member (DRBSD, IWBDR), and reviewer for journals like Future Generation Computer Systems.

Carmen Gillمشاهده پروفایل

استاد

• Domestic Violence
• Intimate Partner Violence
• Domestic Homicide
• +۶ مورد دیگر

Dr. Carmen Gill is a Professor in the Department of Sociology at the University of New Brunswick (UNB), specializing in domestic violence research. She joined UNB full-time in 2014 after a decade as Director of the Muriel McQueen Fergusson Centre for Family Violence Research. Her work focuses on police intervention in intimate partner violence (IPV), domestic homicide, and systemic justice responses to victims and perpetrators. She leads a national project on coercive control and police protocols with the Canadian Association of Chiefs of Police. Previously, she directed a 10-year observatory analyzing justice system responses to IPV. Her research employs mixed methods, including surveys, judicial file analysis, interviews, and focus groups with survivors and police. Key areas include IPV risk assessment, domestic homicide trends in New Brunswick (1999–2018), and police cultural barriers to effective intervention. She collaborates with community organizations and law enforcement agencies to inform policy and practice reforms. Her publications span policing strategies, risk assessment tools, and systemic reforms, with a focus on gendered violence dynamics. Current projects emphasize coercive control frameworks and improving criminal justice system responses. She advises students in criminology, gender relations, and family violence studies. Dr. Gill’s work has directly influenced national police training protocols and policy frameworks through her leadership in developing the Canadian IPV risk assessment framework and collaborative police action guidelines.

Han Yeمشاهده پروفایل

استادیار

• Labor Economics
• Public Policy
• Economics of Aging
• +۵ مورد دیگر

Prof. Han Ye is an Assistant Professor of Applied Public Economics at the University of Mannheim's Department of Economics since 2018. She holds affiliations with IZA, ZEW, Netspar, and the DFG-funded Collaborative Research Center TR 224. Her research focuses on labor economics, public policy, and the economics of aging, particularly examining pension reforms, retirement policies, and their impacts on labor supply, savings, health, and family dynamics. Education: Ph.D. in Economics (Boston University, 2018). Affiliations: IZA Research Fellow, ZEW Research Associate, Netspar Fellow, CRC TR 224 Member. Current Visiting Position: ETH Zurich (2024/2025 academic year). Research Interests: Her work analyzes how pension policies affect retirement timing, unemployment insurance utilization, household savings, mortality, and intergenerational effects such as child outcomes. Recent projects include studying spillover effects of pensions on family labor supply and the relationship between delayed retirement and health outcomes. Key Contributions: Her research highlights behavioral responses to pension subsidies (e.g., retirement timing adjustments), mortality consequences of delayed retirement, and gender disparities in pension awareness. She has also examined how social pensions correlate with intimate partner violence among older women in Mexico. Awards: Program Chair Award at 2024 ASHEcon. Grants: 2024 Netspar Comparative Grant, Inter-American Development Bank GD Lab Grant.

Susan D. Rozelleمشاهده پروفایل

استاد

• Criminal Law
• Criminal Responsibility
• Death Penalty Jurisprudence
• +۵ مورد دیگر

Susan D. Rozelle is a Professor of Law at Stetson University College of Law , where she has taught since 2009. She holds a B.A. from the University of Central Florida and a J.D. from Duke University , and her expertise lies in criminal responsibility, death penalty jurisprudence , and legal reform . Her courses include Criminal Law, Evidence, Criminal Adjudication , and the Criminal Responsibility Seminar . Prior academic appointments: University of Oregon, Seattle University, Capital University Clerkships: Massachusetts Appeals Court, Supreme Judicial Court of Massachusetts Pro bono work: Co-authoring amicus briefs in Uttecht v. Brown , Flores-Figueroa v. US , and Blueford v. Arkansas Leadership roles: Past chair of AALS Criminal Justice Section, current chair of AALS New Law Professors Teaching Materials Network Her research focuses on cognitive bias in intentional homicide law , gender dynamics in criminal cases , and structural flaws in capital punishment . Her work has been cited by the New York Governor's Council on Capital Punishment and the Law Commission for England and Wales . Five of her articles were among the top 10 downloads from SSRN in Criminal Law, Criminal Procedure , and Evidence Law categories. She has presented at conferences at Georgetown University Law Center , University of California at Berkeley , and others. Media appearances include ABC, CBS, NBC, FOX news and NPR , where she discusses legal issues as a commentator.