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.
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.
Biresh Kumar Joardar is an Assistant Professor in the Electrical and Computer Engineering Department at the University of Houston's Cullen College of Engineering. He holds a BE from Jadavpur University (2016) and PhD from Washington State University (2020), with postdoctoral training at Duke University as a Computing Innovation Fellow. His research integrates machine learning with hardware design to develop efficient deep learning accelerators, ReRAM-based architectures, and heterogeneous manycore systems. Current projects focus on enhancing reliability, security, and performance of AI hardware through in-memory computing and 3D integration techniques. Research themes include hardware security (e.g., Rowhammer mitigation), fault-tolerant neural network training, and hardware-software co-design for bioinformatics. Recent articles explore energy-efficient architectures for graph neural networks and cross-layer optimization for AI workloads. Awards: Best Paper Award, International Symposium on Networks-on-Chip (NOCS 2019) Joardar leads the Heterogeneous and In-Memory Computing Lab, seeking PhD students with backgrounds in VLSI, computer architecture, or machine learning. His work has been supported by NSF and industry partnerships.
Roman Samulyak is a Professor in the Department of Applied Mathematics and Statistics at Stony Brook University. He holds a Ph.D. from NJIT in Applied and Computational Mathematics with specializations in Hydro- and Electrodynamics. His research develops advanced numerical algorithms for modeling complex physical systems in high-energy physics and fusion energy. Research spans computational methods for magnetohydrodynamics, plasma physics, nuclear fusion/fission systems, and particle accelerator design. Current applications include disruption mitigation in tokamaks and laser-driven particle acceleration. Recent publications demonstrate strong focus on plasma-based accelerators and fusion reactor modeling, particularly pellet ablation dynamics, laser wakefield acceleration, and MHD simulations of tokamak plasmas. Research utilizes high-performance computing resources for large-scale simulations. Office location is Math Tower 1-108 at Stony Brook University.
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.
Dr. Michele Kennerly is an Associate Professor at Pennsylvania State University, holding joint appointments in the Department of Communication Arts and Sciences and the Department of Classics and Ancient Mediterranean Studies. She is affiliated with the College of the Liberal Arts. In addition to her teaching and research, she has held significant leadership roles, including President of the American Society for the History of Rhetoric (2019–2021) and Secretary General of the International Society for the History of Rhetoric (2020–2025). She is also a member of the Leadership Board for the Colloquium for Ancient Rhetoric and the Advisory Board of Brill's book series International Studies in the History of Rhetoric . Alongside Damien Smith Pfister and Casey Boyle, she co-founded and co-edits the University of Alabama Press series Rhetoric + Digitality . Her work bridges classical rhetoric with contemporary digital and media studies. Education: Michele Kennerly received her B.A. from Austin College in 2004, followed by an M.A. and Ph.D. from the University of Pittsburgh in 2006 and 2010, respectively. Her academic journey reflects a deep engagement with classical and rhetorical studies, culminating in her current interdisciplinary research. Research Interests: Dr. Kennerly’s research focuses on rhetorical theory and its historical reception, particularly in the ancient Mediterranean world and their modern resistive interpretations. She explores how classical texts and concepts influence contemporary discourse, including their roles in automation discussions, queer film adaptations, and medieval rhetorical practices. Her current projects include analyzing invocations of ancient Athens in automation discourse and examining the rhetorical strategies in Jane Campion’s film adaptation of The Power of the Dog and 13th-century Italian notary Brunetto Latini’s works. She emphasizes interdisciplinary approaches, integrating rhetoric with poetics, informatics, and media studies. Her scholarly contributions span classical rhetoric, digital humanities, and media studies. Recent work highlights the intersection of ancient rhetorical theories with modern technologies and cultural phenomena, such as automation, digital networks, and film. She critically examines how historical concepts are reinterpreted in contemporary contexts, reflecting her commitment to linking past and present rhetorical practices. Outstanding Teaching Award for Tenure-Track Faculty (2021) At Penn State, she directed the graduation-required communication course for six years and the undergraduate program in Communication Arts and Sciences (CAS) for three years. She mentors students in collaborative and independent research on the history of rhetoric. Her grants and leadership roles underscore her pedagogical and scholarly impact. Labs/Teams: She contributes to projects like Ancient Rhetoric + Digital Networks and collaborates on the Rhetoric + Digitality book series. She actively engages with academic societies and editorial boards to advance interdisciplinary rhetoric studies.
Dr. Yangjun Chen is a Full Professor in the Department of Applied Computer Science at the University of Winnipeg, Canada. He holds a Ph.D. from the University of Kaiserslautern, Germany (1995). His research focuses on database systems, graph algorithms, computational complexity, and theoretical computer science. Key areas include Federated Databases, Deductive Databases, DNA Databases, and the P vs NP problem. Education: Ph.D. in Computer Science, University of Kaiserslautern, Germany (1995). Research interests span graph query processing, algorithm design, big data optimization, and NP-completeness. Recent work includes polynomial-time solutions for 2-MAXSAT and advancements in string matching algorithms for DNA databases. Publications highlight contributions to graph indexing, efficient reachability queries, and algorithmic efficiency in databases. His work often bridges theoretical foundations with practical database applications. Awards: Excellent Merit Award (2022-2023, 2021-2022) - University of Winnipeg Best Article, ACTA Scientific Computer Sciences (2022) Multiple Best Paper Awards at conferences like DBKDA 2016 and CyberC Summit Teaching includes Advanced Databases, Distributed Database Systems, and Algorithms courses at both undergraduate and graduate levels. Active in supervising research in database systems and theoretical computer science. Laboratory and team focus on database innovation, including projects on graph databases and efficient query processing techniques.
Associate Professor Antonio Peyrache is a Deputy Head of School at the School of Economics, University of Queensland, within the Faculty of Business, Economics and Law. His research focuses on applied economics, econometrics, and productivity/efficiency analysis with particular emphasis on production systems, public sector efficiency, and systemic risk modeling. He leads the Centre for Efficiency and Productivity Analysis (CEPA), driving advancements in efficiency measurement methodologies. Key research interests include judicial system efficiency, banking systemic risk, and multilevel production networks. Recent work explores homothetic production technologies and optimal organizational structures for public institutions. Featured projects include analyzing productivity in Australian horticulture and European judicial systems. His expertise spans both theoretical contributions (e.g., decomposition frameworks) and applied policy analysis (e.g., healthcare delivery efficiency). Publications span journals like European Journal of Operational Research and Omega, with a focus on operational research techniques and their policy applications. He has directed projects funded by the Asian Productivity Organization and collaborated on EU-KLEMS growth accounting initiatives. Professional roles include editorial contributions and leadership in academic productivity analysis.
Vinay Lal is Professor of History and Asian American Studies at the University of California, Los Angeles (UCLA), where he has been teaching since Fall 1993. He holds a joint appointment in the Department of History and the Asian American Studies Department. Born in Delhi and raised across multiple countries including India, Indonesia, Japan, and the United States, Lal brings a global perspective to his scholarship and teaching. His educational journey began at Johns Hopkins University, where he earned both his B.A. (1982) and M.A. (1982) from the Humanities Center with concentrations in literature, history, and philosophy. He then studied film in Australia and India on a Thomas J. Watson Fellowship before pursuing his Ph.D. at the University of Chicago's Department of South Asian Languages and Civilizations, which he completed with Distinction in 1992. His dissertation, 'Committees of Inquiry and Discourses of 'Law and Order' in Twentieth-Century British India', received the Marc Galler Award for the best dissertation in the Division of the Humanities at the University of Chicago. Lal's research spans an extraordinary breadth of intellectual interests, with primary focus on Indian history, historiography, public and popular culture in India, the Indian diaspora, colonialism, human rights, American politics, the architecture of nonviolence, Gandhi studies, and the global politics of knowledge systems. His work consistently challenges conventional disciplinary boundaries, engaging with topics ranging from the politics of religion and ethnicity in South Asia to the moral and political thought of Mohandas Gandhi, from the partition of India to the intersection of history and popular cinema. His scholarship reflects a deep commitment to decolonizing knowledge systems and exploring alternative epistemologies from the Global South. His publications reveal a scholar deeply engaged with both historical analysis and contemporary political issues. The 15 most recent articles demonstrate his consistent focus on South Asian politics, historical memory, nonviolence, and the politics of knowledge. His writing spans academic journals, major newspapers, and public intellectual platforms, with a distinctive voice that bridges scholarly rigor and public accessibility. His work on Gandhi, colonialism, and contemporary Indian politics forms a particularly strong thread throughout his recent publications. Fellow of the World Academy of Art and Science (elected February 2000) William R. Kenan Fellow, Society of Fellows in the Humanities, Columbia University (1992-93) Senior Fellowship from the American Institute of Indian Studies National Endowment for the Humanities Fellowship for University Teachers Fellowship from the Society for the Promotion of Science/Japan Area Studies Center Listed among the '101 Most Dangerous Professors in America' in David Horowitz's book Fulbright-Nehru Fellowship for Academic and Professional Excellence Fellow at the Stellenbosch Institute for Advanced Study (STIAS), South Africa (2024) Oxford University Press India Academic (Humanities) Delegate (2022-2028) As a dedicated mentor, Lal has supervised numerous PhD students who have gone on to prominent academic careers at institutions including CSU-Sacramento, UNC-Charlotte, O.P. Jindal University, UC Irvine, and the University of Pittsburgh. His teaching portfolio at UCLA is exceptionally broad, encompassing undergraduate courses on Indian Civilization, British India, contemporary South Asia, and world history, along with graduate seminars on Indian politics and religion, historiography of modern India, nationalism and colonialism, Indian cinema, and postcolonial theory. His lecture courses are available in their entirety on his academic YouTube channel, which has garnered over 3 million views and 36,000 subscribers. Lal has also served as University of California's Director of the Education Abroad Program in India and as Professor of History at the University of Delhi during 2010-11. Lal is a founding member of the Backwaters Collective on Metaphysics and Politics (2010-2020), which met annually in Kerala, and was associated with Multiversity, a group of scholars focused on decolonizing Western knowledge systems. His current work includes a four-book project titled 'The Genocide and Hope Quartet: Studies in the Architecture of Oppression and the Redemptive Possibilities of Nonviolence', examining Dandi, Auschwitz, Hiroshima, and Robben Island. He maintains an active public intellectual presence through his blog 'LAL SALAAM' and his academic YouTube channel, making scholarly content accessible to wider audiences.
Bhuvana Srinivasan is a Professor in the Department of Aeronautics and Astronautics at the University of Washington, directing the PLASMAWISE Laboratory. Previously, she held the rank of Associate Professor and served as Director of the Plasma Dynamics Computational Laboratory at Virginia Tech, supported by the Crofton Faculty Fellowship. Her research focuses on fusion energy, plasma-based propulsion, and computational plasma physics, with an emphasis on plasma-material interactions and instabilities across diverse plasma regimes. She has authored over 30 peer-reviewed publications and secured grants from the NSF, DOE, and AFOSR. Education: Ph.D. in Aeronautics and Astronautics, University of Washington (specializing in computational plasma physics) M.S. in Aeronautics and Astronautics, University of Washington B.S. in Aerospace Engineering and Mechanical Engineering, Illinois Institute of Technology Research Interests: Her work spans fusion energy concepts, plasma propulsion systems, high-energy-density plasma instabilities, and ionospheric dynamics. Key areas include plasma-surface interactions in fusion devices, magnetic field effects on plasma mixing, and algorithm development for fluid-kinetic models. She emphasizes high-fidelity multi-fluid simulations using discontinuous Galerkin methods. Awards & Recognition: NSF CAREER Award (2019-2024) Crofton Faculty Fellow (Virginia Tech, 2021-2023) Dean’s Outstanding Assistant Professor (Virginia Tech, 2017) Amelia Earhart Fellowship (Zonta International, 2007-2009) Advocacy & Leadership: She chairs DEI initiatives in academic departments and serves on national committees including the DOE Fusion Energy Sciences Advisory Committee and the APS Division of Plasma Physics Executive Board. Her work bridges computational plasma physics with societal impact, including fusion energy democratization and space exploration propulsion systems.
Taylor Johnson is an Associate Professor of Computer Science and Electrical and Computer Engineering at Vanderbilt University's School of Engineering. He directs the Verification and Validation for Intelligent and Trustworthy Autonomy Laboratory (VeriVITAL) and serves as a Senior Research Scientist in the Institute for Software Integrated Systems. Previously, he was an Assistant Professor at the University of Texas at Arlington from 2013 to 2016. His research focuses on formal verification techniques for cyber-physical systems (CPS), emphasizing safety, reliability, and security through hybrid systems, formal methods, and control theory. He has published extensively on neural network verification, earning best paper awards and recognition from IEEE, IFIP, and ACM. Education: Ph.D., Electrical and Computer Engineering (University of Illinois at Urbana-Champaign, 2013) M.Sc., Electrical and Computer Engineering (University of Illinois at Urbana-Champaign, 2010) B.S.E.E., Electrical and Computer Engineering (Rice University, 2008) Research Interests: Formal verification of neural networks and CPS, safety-critical systems, autonomous systems, and AI/ML security. His work bridges theoretical foundations (e.g., hybrid systems) with practical applications in aerospace, energy systems, and robotics. Key Contributions: Developed the NNV tool for neural network verification, led the Verification of Neural Networks Competition (VNN-COMP), and pioneered techniques for robust federated learning and malware detection. Awards: AFOSR YIP Award (2016), NSF CRII Award (2015), and multiple best paper honors. His research is funded by AFRL, NSF, Intel, NVIDIA, and industry partners. Labs & Collaborations: VeriVITAL Lab (Vanderbilt), collaborations with United Technologies Research Center, Boeing, and Toyota.
Naratip Santitissadeekorn is a Senior Lecturer in Data Assimilation at the School of Mathematics and Physics, University of Surrey, where he is affiliated with the Mathematics at the Interface Group. His work bridges mathematics, data science, and real-world applications in urban planning, crime analysis, and geophysical fluid dynamics. Dr. Santitissadeekorn received his PhD from Clarkson University in 2008, with a dissertation titled "Transport Analysis and Motion Estimation of Dynamical Systems of Time-Series data." His doctoral research was supervised by Professor Erik Bollt. Following his PhD, he completed two significant postdoctoral positions: from 2008-2011 at the University of New South Wales, Sydney, Australia, working with Professor Gary Froyland on numerical techniques for finite-time Lagrangian coherent set identification, with applications to delimiting the polar vortex and Agulhas rings; and from 2011-2014 at the University of North Carolina-Chapel Hill, working with Professor Chris Jones on data assimilation projects. Dr. Santitissadeekorn's research focuses on inverse problems and data assimilation in geophysical fluid dynamics, the applications of Lagrangian Coherent Structures (LCS), and computational ergodic theory. His work combines theoretical mathematics with practical applications, particularly in urban growth modeling and crime analysis. He has developed innovative methods for identifying coherent structures in fluid flows, estimating transition probabilities from spatiotemporal data, and creating data-driven frameworks for urban expansion scenarios. His research demonstrates how mathematical techniques can be applied to solve real-world problems in environmental science, urban planning, and public safety. An analysis of Dr. Santitissadeekorn's recent publications (2020-2023) reveals a strong focus on urban expansion modeling and network analysis. His work on urban growth has evolved from basic cellular automata models to sophisticated frameworks that manage uncertainty through parameter clustering and growth mode identification. His research on Hawkes processes has advanced ensemble-based filtering techniques for analyzing count data in large networks. These publications demonstrate a consistent pattern of applying mathematical rigor to complex spatiotemporal phenomena, with increasing emphasis on data-driven approaches and practical applications. Dr. Santitissadeekorn has made significant contributions to data assimilation methods, particularly through the development of the extended Poisson-Kalman filter (ExPKF) for urban crime modeling. His teaching includes courses in Algebra and Bayesian Statistics, reflecting his expertise in both theoretical and applied mathematics. While specific awards are not mentioned in the available information, his extensive publication record in high-impact journals demonstrates recognition within his field. Dr. Santitissadeekorn's research has practical implications for urban planning and law enforcement. His work on urban expansion models helps planners understand different growth trajectories, while his crime modeling research contributes to improved police patrolling strategies. His interdisciplinary approach, combining mathematics, computer science, and domain-specific knowledge, positions him at the forefront of applying data science to societal challenges.
Dr. Werner Bauer is a Lecturer in Mathematics at the University of Surrey, affiliated with the Mathematics at the Interface Group within the School of Mathematics and Physics. His research focuses on numerical analysis and scientific computing, particularly in the Mathematics of Planet Earth. Key areas include parallel-in-time methods for oscillatory PDEs, structure-preserving discretizations for fluid dynamics, stochastic flow models for ensemble prediction, and geometric formulations of fluid and magnetohydrodynamic systems. He also explores finite difference and finite element methods, with prior work on grid adaptation in weather and climate models. His research interests span numerical methods for geophysical flows, stochastic modeling of oceanic and atmospheric dynamics, and energy-conserving computational frameworks. Bauer’s recent work emphasizes uncertainty quantification, ensemble forecasting, and the development of compatible finite element schemes to ensure physical conservation laws in simulations. Bauer’s publications highlight advancements in structure-preserving discretizations, stochastic parameterization of mesoscale eddies, and variational integrators for geophysical equations. His work bridges applied mathematics and computational science with applications in climate modeling and environmental fluid dynamics.
Mahdi Boloursaz Mashhadi is a Lecturer in Communications and AI at the Institute for Communication Systems (ICS), part of the School of Computer Science and Electronic Engineering at the University of Surrey, UK. He is a Surrey AI Fellow and an IEEE Senior Member, with a focus on advancing AI-driven wireless communication systems. He holds B.S., M.S., and Ph.D. degrees in mobile telecommunications from Sharif University of Technology, Tehran, Iran. Prior to joining Surrey, he served as a postdoctoral research associate at Imperial College London’s Intelligent Systems and Networks (ISN) Research Group (2019–2021). His research interests span AI/ML integration with wireless systems, including semantic communications, federated learning, generative AI for telecom, and beamforming optimization in massive MIMO architectures. He also explores edge computing, distributed deep learning frameworks, and energy-efficient communication designs using reconfigurable intelligent surfaces (RIS). Mahdi has been recognized with the IEEE EWDTS Best Paper Award and IEEE ComSoc Exemplary Reviewer Awards (2021–2022). He leads the UKTIN/DSIT 12M£ national project TUDOR and collaborates with industry on cutting-edge 5G/6G innovations. He has contributed to the ITU’s AI/ML in 5G challenge as a panel judge and serves as an editor for Springer’s Wireless Personal Communications Journal. His roles include advising on government/industry projects and advancing interdisciplinary research at the 5G/6G Innovation Centre. He emphasizes practical implementations of AI in telecommunications, aiming to bridge theoretical advancements with real-world applications.
Prof. Dan Olteanu is a full professor at the Department of Informatics, University of Zurich, leading the Data Systems and Theory (DaST) group. He holds visiting professorships at the University of Oxford and is an emeritus fellow of St Cross College. His academic journey includes a PhD from Ludwig Maximilian University (2005), postdoctoral roles at Saarland University and Cornell University, and prior faculty positions at Oxford (2007–2020). He has also worked in industry with companies like LogicBlox and RelationalAI, focusing on database systems and AI. Education: Bachelor’s in Computer Science, Politehnica University of Bucharest (2000) PhD in Computer Science, Ludwig Maximilian University (2005) Professional Roles: Full Professor, University of Zurich (since 2020) Visiting Professor, University of Oxford Emeritus Fellow, St Cross College Editorial Roles: ACM TODS, VLDBJ, SIGMOD Conference Chair: ICDT Council (since 2022) His research focuses on data systems theory, including query optimization, probabilistic databases, factorized databases, and in-database machine learning. He co-authored the seminal book Probabilistic Databases (2011) and has pioneered algorithms for efficient machine learning over relational data and incremental maintenance of analytical workloads. His work emphasizes scalable, theoretically grounded solutions for real-world data challenges. Awards: ICDT 2019 Best Paper Award ACM SIGMOD 2018 Distinguished PC Member Award ERC Consolidator Grant (2016) Oxford Outstanding Teaching Award (2009) Grants & Funding: Supported by Google, Microsoft Azure, Amazon AWS, EPSRC, and the European Commission. His research bridges academia and industry, with contributions to commercial systems like LogicBlox and RelationalAI. Labs & Teams: Heads the DaST group at Zurich, focusing on data systems theory and applications. Collaborates widely in the database and AI communities.
