Xiaojiang Du is the Anson Wood Burchard Endowed Professor at Stevens Institute of Technology, directing research in IoT security, AI security, and wireless networks. An IEEE Fellow and ACM Distinguished Member, he leads NSF-funded projects on secure IoT systems and cross-platform security vulnerabilities. Education PhD in Electrical Engineering, University of Maryland MS in Electrical Engineering, Tsinghua University BE in Electrical Engineering, Tsinghua University Research Focus: Develops security frameworks for IoT ecosystems and adversarial machine learning, with recent breakthroughs in smart home security anomaly detection. Honors: IEEE Fellow, ACM Distinguished Member, multiple best paper awards at IEEE conferences. Graduated PhD students hold faculty positions at UNC Charlotte, UL Lafayette, and ShanXi University. Professional Service: IEEE ComSoc Distinguished Lecturer, Associate Editor for IEEE Transactions, and General Co-Chair for IEEE/ACM IWQoS 2023. Secured $9M+ in research funding from NSF, NSA, and DOD.
Mehmet Esat Belviranli is an Assistant Professor in the Computer Science Department at the Colorado School of Mines, where he directs the High Performance Systems and Software Lab (HyperSys). His research focuses on increasing resource utilization in heterogeneous architectures through runtime systems, scheduling algorithms, and performance modeling, with publications in top venues including MICRO, PPoPP, and SC. Education: Ph.D. in Computer Science, University of California, Riverside (2016) M.S. in Computer Science, Bilkent University (2009) B.S. in Computer Science, Bilkent University (2006) Belviranli's research spans heterogeneous architectures, runtime systems, performance modeling, parallel programming, autonomous computing, deep learning acceleration, cyber-physical systems, and edge-cloud platforms. His work develops analytical models and programming abstractions to address resource management, scheduling, and security challenges in diversely heterogeneous systems, with applications in edge computing, autonomous systems, and machine learning acceleration. Recent projects emphasize real-world constraints and security implications. His publication trends reveal increasing focus on edge-cloud resource management (e.g., HARNESS), security vulnerabilities in heterogeneous systems (e.g., MC3), and deep learning acceleration under resource constraints. Key themes include memory contention modeling, scheduling for cyber-physical systems, and concurrent DNN execution, reflecting a shift toward practical deployment in security-sensitive edge environments. Scientific Awards: U.S. Air Force Research Lab Summer Faculty Fellowship Award (2022) U.S. Air Force Research Lab Summer Faculty Fellowship Award (2021) Oak Ridge National Laboratory Significant Event Award (2019) Best Paper Finalist, IEEE HPEC 2018 Outstanding Paper Award, DATE 2024 Belviranli mentors Ph.D. students Ismet Dagli (MLCommons Rising Star 2024, CGO'24 SRC finalist) and Justin Davis (DATE'24 Outstanding Paper Award winner). He has secured $2M+ in funding from NSF, DoE, and SRC, including an NSF-SaTC grant on mobile security (2024), a DoE grant on superconductive systems (2023), and an NSF FuSe grant on graphene nanoribbons (2023), often leading multi-institutional teams from Rochester, Virginia, Arizona, and Minnesota. The HyperSys Lab develops ecosystems for high-performance heterogeneous systems, with recent projects including HARNESS for edge-cloud resource management and MC3 for mobile SoC security. The lab has received equipment donations from Google Coral.ai and Xilinx, and collaborates with national labs on security challenges and next-generation semiconductor technologies.
Sapha Barkati, MD, MSc is an Assistant Professor at the Department of Medicine, Faculty of Medicine and Health Sciences, McGill University , and an Investigator at the RI-MUHC Glen site . Her work bridges clinical practice and research in tropical medicine, focusing on parasitic diseases affecting vulnerable populations. Affiliations: Assistant Professor, McGill University Investigator, Research Institute of the McGill University Health Centre (RI-MUHC) McGill International Tuberculosis Centre Research Focus: Specializes in neglected tropical diseases like strongyloidiasis and tegumentary leishmaniasis, particularly among migrants and immunocompromised individuals. Studies include: Physician awareness of Strongyloides screening Prevalence patterns in non-endemic countries HTLV-1 co-infection treatment response Cost-effective screening strategies Scientific Contributions: Key publications address tropical disease management in non-endemic settings, mpox outbreak dynamics, and SARS-CoV-2 immunity patterns. Her work emphasizes evidence-based guidelines for: Parasite screening in transplant recipients Leishmaniasis treatment protocols Traveler disease prevention Collaborative Networks: Partners with institutions like Universidad Peruana Cayetano Heredia and participates in GeoSentinel surveillance. Leads studies on: Covid-19 health disparities Vaccine effectiveness against variants Remote patient monitoring systems
Timothy Bretl is a Professor of Aerospace Engineering at the University of Illinois at Urbana-Champaign, holding the Severns Faculty Scholar position since 2021. He also serves as Associate Head of the Aerospace Engineering department. His research focuses on robotics, control systems, rehabilitation robotics, and engineering education. Bretl earned his Ph.D. from Stanford University (2005), with prior degrees from Swarthmore College. He holds affiliate roles across multiple departments, including Neuroscience, Coordinated Science Laboratory, and Computer Science. Education: Ph.D. in Aeronautics and Astronautics, Stanford University (2005) B.A. in Mathematics and B.S. in Engineering, Swarthmore College (1999) His research spans engineering education innovations, robotic manipulation, and brain-machine interfaces. Notable awards include the NSF CAREER Award (2010), Best Manipulation Paper (2012), and multiple teaching honors like the Rose Award for Teaching Excellence (2016). Bretl’s work integrates theoretical foundations with practical applications in prosthetics, autonomous systems, and educational technology. He has advised numerous projects on robotics, control systems, and human-robot interaction. His lab explores advanced topics like elastic rod manipulation, magnetic positioning, and curriculum reform in STEM education. Collaborative projects include partnerships with industry and interdisciplinary teams at the Beckman Institute.
Don Towsley is a Distinguished University Professor in the Department of Computer Science at the University of Massachusetts Amherst, within the College of Information and Computer Sciences. He has held visiting positions at AT&T Labs, IBM Research, INRIA, Microsoft Research Cambridge, and the University of Paris 6. He earned a B.A. in Physics and a Ph.D. in Computer Science from the University of Texas. Prof. Towsley's research spans network science, measurement, modeling, and analysis, with recent emphasis on quantum networking and wireless security. His work addresses foundational challenges in network tomography, entanglement distribution, and quantum communication protocols, contributing to efficient and secure next-generation networks. Analysis of his 2022-2025 publications reveals a dominant focus on quantum networking—including quantum internet architecture, entanglement distribution, and tomography—alongside continued contributions in classical networking areas such as DDoS detection and edge computing. His exceptional contributions have been recognized with numerous prestigious awards: 2007 IEEE Koji Kobayashi Computer and Communications Award 2007 ACM SIGMETRICS Achievement Award 2008 ACM SIGCOMM Award 2011 INFOCOM Achievement Award 1999 IEEE Communications Society William Bennett Award 2008 ACM SIGCOMM Test of Time Paper Award 2012 ACM SIGMETRICS Test of Time Award 2018 ACM MOBICOM Test of Time Award UMass Award for Outstanding Accomplishments in Research and Creative Activity University of Massachusetts Chancellor's Medal UMass Amherst Distinguished Graduate Mentor Award Outstanding Research Award from the College of Natural Science and Mathematics IBM Faculty Fellowship Award (twice) Fellow of the IEEE Fellow of the ACM Corresponding member of the Brazilian Academy of Sciences Prof. Towsley has mentored numerous graduate students, as evidenced by his Distinguished Graduate Mentor Award, and his research has been funded by significant grants including an NSF NeTS grant for quantum network design. He leads the Gaia research group at UMass Amherst, which has evolved from traditional networking research to pioneering quantum networking initiatives.
Lars Nordström is a Professor at the Division of Electric Power and Energy Systems within KTH Royal Institute of Technology, Stockholm, Sweden. His work bridges control systems , communication networks , and power systems , with a focus on future architectures, functionality, and quality aspects of ICT for power grid operations. He has led initiatives such as the Swedish Centre of Electric Power Engineering and served as Thematic Leader for Smartgrids in KIC InnoEnergy. In 2014, he was a Visiting Professor at Washington State University. Education : Ph.D., MSc.EE Nordström's research explores the intersection of smart grids , machine learning , and cybersecurity for power systems. Key areas include: Wide-Area Monitoring and Control (WAMC) systems Decentralized control strategies for DC microgrids Impedance modeling using neural networks Data-driven methods for islanding detection ICT reliability and protocol design for grid operations His recent publications emphasize machine learning applications in power systems, including LSTM networks for EV charging management, graph attention networks for stability monitoring, and digital twin approaches for cyber-attack mitigation. These works span disciplines such as Smart Grids, Power Electronics, and Data Science. Scientific Recognitions : Senior Member, IEEE Senior Member, CIRED Senior Member, Cigre Past Chairman, Swedish IEC TC57 Mirror Committee Nordström actively teaches and examines graduate courses like Communication and Control in Electric Power Systems and Computer Applications and Machine Learning in Electric Power Systems . His work influences industry practices through collaborations on digital substations, energy market analysis, and resilience strategies.
Ping Yang is a Professor and Associate Director for Research and Graduate Programs in the School of Computing at Binghamton University (SUNY). She holds a Ph.D. in Computer Science from Stony Brook University, an ME from the Chinese Academy of Sciences, and a BS from Zhongshan University. Her research focuses on cybersecurity, AI-based security, virtual machine security, privacy policy analysis, and formal methods. She directs the Center for Information Assurance and Cybersecurity and coordinates cybersecurity programs at both undergraduate and graduate levels. Education: BS in Computer Science, Zhongshan University ME in Computer Science, Chinese Academy of Sciences MS and PhD in Computer Science, State University of New York at Stony Brook Research Interests: Dr. Yang's work spans information and systems security, security in virtualized computing, access control mechanisms, privacy policies, and formal methods for security verification. Her projects include blockchain-based provenance storage, real-time anomaly detection in workflows, and privacy-preserving virtual machine migration. She has led NSF-funded initiatives on security in cloud environments and scientific workflows. Awards: Not explicitly listed in the provided materials. Advising & Grants: Advised over 30 PhD/Master’s students and contributed to grants including NSF Scholarship for Service and GenCyber programs. Her team develops tools like RBAC-PAT for access control analysis. Labs/Teams: Leads the Center for Information Assurance and Cybersecurity and collaborates on projects involving secure data workflows and blockchain applications in scientific research.
Olaf Steinbach is a University Professor (Univ.-Prof.) at the Institute of Applied Mathematics at Graz University of Technology. His academic career spans over three decades with continuous research activity from 1992 to the present, including publications scheduled for 2026. He serves as a project manager for several research initiatives including the Special Research Area (SFB) F90 Computational Electric Machine Laboratory, which runs from 2022 to 2026. Professor Steinbach's research interests primarily focus on Numerical Analysis and Computational Mathematics . His work centers around developing and analyzing advanced numerical methods, particularly Finite Element Methods (FEM) and Boundary Element Methods (BEM), for solving partial differential equations (PDEs) and optimal control problems. His research spans both theoretical aspects (such as error analysis, stability, and convergence) and practical applications (including electric machines, electromagnetics, and biomechanics). He has made significant contributions to space-time finite element methods, which treat time as an additional dimension in the discretization process, leading to more robust and efficient solvers for time-dependent problems. Analysis of his recent publications (2021-2026) reveals a strong focus on optimal control problems governed by partial differential equations, with particular emphasis on elliptic, parabolic, and hyperbolic PDEs. His work demonstrates a consistent pattern of developing robust numerical methods with rigorous error analysis, often incorporating regularization techniques to handle challenging constraints. The applications span computational electromagnetics (particularly electric machines), fluid dynamics, and wave propagation problems. His research increasingly incorporates advanced computational techniques including parallel computing and isogeometric analysis. Professor Steinbach has supervised numerous doctoral students and has been actively involved in organizing academic events, including summer schools on Boundary Element Methods. His collaborative network extends across multiple disciplines and institutions, reflecting the interdisciplinary nature of his work in computational mathematics. His research has been supported through multiple significant projects including DK-W1244 Doctoral Program on Partial Differential Equations, the EU CASOPT project on optimization of industrial devices, and the ongoing Special Research Area on Computational Electric Machine Laboratory. These projects demonstrate his leadership in establishing research frameworks that bridge theoretical mathematics with practical engineering applications. Professor Steinbach maintains an active research group within the Institute of Applied Mathematics, collaborating closely with researchers in computational engineering, electrical engineering, and biomechanics. His work on the Computational Electric Machine Laboratory represents a particularly strong interdisciplinary effort combining mathematical theory with electrical engineering applications.
Stephanie Gil is an Assistant Professor of Computer Science at the Harvard John A. Paulson School of Engineering and Applied Sciences. Her research focuses on artificial intelligence, robotics, and distributed systems, particularly addressing challenges in multi-agent coordination, resilience to adversarial attacks, and wireless communication for autonomous systems. She leads the REACT Lab, advancing research in resilient multi-robot networks and cyber-physical systems. Her work integrates machine learning, control theory, and wireless sensing to solve problems such as whale tracking via autonomous robots, proactive multi-robot routing, and decentralized exploration without explicit information exchange. She has received prestigious awards, including the DARPA Young Faculty Award (2024) and the Amazon Research Award (2021). Key research areas include resilient distributed optimization, trust-centered coordination in multi-agent systems, and leveraging wireless signals (e.g., WiFi-CSI) for sensing and bearing estimation. Her contributions span both theoretical frameworks and practical implementations, with a focus on real-world applications like autonomous rideshare routing and environmental monitoring. Dr. Gil’s research also explores trust and cybersecurity in dynamic networks, with publications on crowd vetting, malicious robot detection, and adaptive communication strategies. She collaborates on interdisciplinary projects, such as Project CETI, combining AI and robotics for ecological studies.
Clyde Kruskal is an Associate Professor in the Department of Computer Science at the University of Maryland, College Park. His research focuses on parallel architectures, models, and algorithms. He earned a Ph.D. from New York University in 1981 and a bachelor’s degree from Brandeis University in 1976. His work includes foundational contributions to parallel computing, such as the read–modify–write concept in distributed systems. Kruskal’s research spans topics like interconnection networks, synchronization mechanisms, and algorithm design for parallel systems. Education: Bachelor’s Degree: Brandeis University, 1976 Master’s Degree: New York University (Courant Institute), 1978 Ph.D.: New York University (Courant Institute), 1981 Research Interests: Parallel computing architectures, parallel algorithms design, multiprocessor synchronization, interconnection networks, and computational geometry problems like graph coloring and visibility analysis. His work emphasizes theoretical foundations and practical implementations in parallel systems. Notable Contributions: Kruskal co-authored the book Problems With A Point: Exploring Math And Computer Science (2019), and his research includes foundational papers on parallel prefix operations, sparse matrix algorithms, and synchronization protocols. His publications span over three decades, reflecting sustained contributions to parallel computing theory and practice. Advising & Outreach: He has mentored students through programs like the Summer Combinatorial Algorithms REU at UMD, fostering undergraduate research in algorithm design and parallel computing.
Amro Awad is an Associate Professor in the Department of Electrical and Computer Engineering (ECE) at North Carolina State University's College of Engineering. He previously served as an Assistant Professor at the University of Central Florida and as a Senior Member of Technical Staff at Sandia National Laboratories. Dr. Awad earned his Ph.D. and Master's in Computer Engineering from NC State and a Bachelor's from Jordan University of Science and Technology. Research Focus His research spans computer architecture and security, emphasizing secure hardware systems , memory security , and integration of emerging technologies . Key contributions include novel approaches to secure and efficient GPU memory management, FPGA resource scheduling, and DRAM simulation. Publications & Awards Dr. Awad's work appears in top-tier venues like ISCA, MICRO, ASPLOS, and HPCA. He holds six U.S. patents and received the prestigious R. Ray Bennett Faculty Fellow Award and recognition as a Goodnight Early Career Innovator . Funding & Collaborations His research group has been supported by DARPA , Sandia National Laboratories , NSF , Naval Surface Warfare Center , and Air Force Research Lab . Collaborations include AMD Research, Los Alamos National Lab, HP Labs, and Air Force Research Laboratory.
Stefano Galelli is a tenured Associate Professor in the School of Civil and Environmental Engineering at Cornell University, where he leads the Critical Infrastructure Systems Lab. He also holds an adjunct position as a Research Scientist at the Lamont-Doherty Earth Observatory, Columbia University. His career spans roles in Singapore, including a Postdoctoral Research Fellow at NUS (2011–2013) and faculty at the Singapore University of Technology and Design (2013–2023). Dr. Galelli earned his B.Sc. (2004), M.Sc. (2007), and Ph.D. (2011) in Environmental and Land Planning Engineering and Information Technology from Politecnico di Milano, Italy. His research focuses on the interactions between critical infrastructure systems and natural environments, emphasizing adaptive management solutions for water-energy systems. Techniques include process-based modeling, climatology, statistical learning, control theory, and optimization. He explores topics like hydro-climatic variability impacts, dam re-operation for environmental flows, and cyber-physical security in infrastructure. His contributions to journals such as Nature Sustainability, Earth’s Future, and Environmental Modelling & Software have earned him multiple awards, including the Early Career Research Excellence Award (2014) and SUTD Excellence in Research Award (2017). He has served as an editor for several journals and is recognized for advancing interdisciplinary approaches to water-energy nexus challenges. Teaching highlights include foundational mathematics courses and advanced topics in data analytics, optimization, and water-energy management. He is developing new courses on data-driven control of coupled human-natural systems and risk management for interconnected systems.
Tianzheng Wang is an Associate Professor and Director of the Dual-Degree and Partnerships Programs at the School of Computing Science, Simon Fraser University. His research focuses on database systems, transaction processing, parallel and distributed computing, and embedded systems. He holds a PhD in Computer Science from the University of Toronto (2017) and a BSc in Computing from Hong Kong Polytechnic University (2012). Research Interests: Database systems optimized for modern hardware, parallel programming, synchronization, and distributed architectures. His work emphasizes high-performance transaction processing and efficient indexing techniques, with applications in cloud and embedded systems. Awards: ACM SIGMOD Best Paper Award (2025), IEEE TCSC Early Career Award (2019), and multiple distinguished reviewing recognitions (SIGMOD/VLDB 2021-2024). His research has been integrated into systems like Amazon Redshift and DragonflyDB. Teaching: Leads courses such as CMPT 454 (Database Systems II), CMPT 300 (Operating Systems), and special topics in databases. Actively mentors graduate and undergraduate students in research projects. Labs & Collaborations: Heads the Data-Intensive Systems Lab, part of SFU's Data Science and Systems groups. Collaborates on tools like PiBench for persistent memory benchmarking and contributes to open-source projects like CoroBase and Tabular.
Goran Avlijas serves as an Assistant Professor at Singidunum University's Faculty of Business in Belgrade, Serbia. His academic profile spans project management, operational research, and retail logistics with significant industry experience at Delta Holding, Strabag AG, and Efektus Consulting Group. His research interests focus on project management methodologies including Agile and Earned Value Management, retail operations optimization through automatic replenishment systems, and sustainable project control . Current work examines gig economy impacts on well-being and pandemic business resilience. Recent publications demonstrate strong emphasis on Quantitative project risk analysis using Monte Carlo simulation Retail inventory management and stock-out reduction Agile methodology implementation in Serbian business context Sustainable infrastructure project valuation Professional recognitions include: Project Management Professional (PMP) Professional in Business Analysis (PMI-PBA) Agile Certified Practitioner (PMI-ACP) He actively participates in Erasmus+ programs as both teacher and mentor, notably guiding Serbia's championship-winning team at the 2020 International Project Management Championships. His academic contributions include two textbooks on Project Management and Entrepreneurship, along with numerous international conference participations as scientific committee member and reviewer. Avlijas maintains strong industry-academia connections through PMI membership and consulting engagements, while contributing to higher education accreditation processes as a National Accreditation Body delegate.
Luca Iocchi is a Full Professor at Sapienza University of Rome, where he teaches in the Master in Artificial Intelligence and Robotics program. He is affiliated with the Department of Computer, Control, and Management Engineering and the Faculty of Engineering of Information, Computer Science and Statistics. Iocchi serves as an Associate Editor for Artificial Intelligence Journal and has been the scientific coordinator of Spoke of PNRR project FAIR (Future AI Research). His educational background includes: Master in Engineering in Computer Science (Laurea in Ingegneria Informatica) cum Laude, Sapienza Università di Roma, 1995 PhD in Engineering in Computer Science (Dottorato in Ingegneria Informatica), Sapienza Università di Roma, 1999 Professor Iocchi's research focuses on cognitive robotics, task planning, multi-robot coordination, robot perception, robot learning, human-robot interaction, and social robotics. His work has significant applications in security, surveillance, and environmental monitoring. He has published over 200 referred papers with an h-index of 46 (Google Scholar). His research bridges theoretical AI with practical robotic systems operating in real-world environments, with a particular emphasis on developing intelligent systems that can interact effectively with humans. His recent publications show a strong trend toward multi-agent reinforcement learning, trust modeling in human-AI teams, UAV coordination, and planning systems. There's a clear focus on making robotic systems more reliable, efficient, and capable of operating in complex real-world scenarios like healthcare facilities and smart cities. His work increasingly integrates formal planning approaches with machine learning techniques. Professor Iocchi has received numerous scientific awards: 1999 Top Paper Award WebNet'99 2006 Best Paper Award RoboCup 2006 2008 Best Robotics Demo Award AAMAS 2008 2014 Best Paper Award For Engineering Contribution RoboCup 2014 2017 RoboCup@Home SSPL 2017 - 3rd place 2018 Canada-Italy Innovation Award 2019 Best Paper Award For Engineering Contribution RoboCup 2019 As an academic advisor, Iocchi has directed the PhD Program in Engineering in Computer Science from 2020 to 2023. He has been Principal Investigator for numerous research projects including SciRoc (European Robotics League), AI4EU (European AI project), BUBBLES, AIPlan4EU, ROSITA, Trust Your Agents, and FAIR. His research has been supported by EU H2020 programs, national grants, and industry collaborations, demonstrating strong connections between academia and practical applications. Professor Iocchi is actively involved with the Cognitive Cooperating Robots Lab (LabRoCoCo) and is a key member of the RoboCup Federation, having served as Vice-President from 2019 to 2024. He has played a significant role in benchmarking domestic service robots through RoboCup@Home and the European Robotics League Service Robots (ERL-SR), which he helped establish. His leadership in organizing international scientific robot competitions has been instrumental in advancing the field of service robotics.
