Saurabh Bagchi is a Professor at Purdue University, West Lafayette, USA. He holds a PhD in Computer Science from the University of Illinois Urbana-Champaign (2001). His research focuses on distributed systems security, networking, and embedded systems. Key areas include IoT security, cyber-physical systems resilience, and machine learning applications in edge computing. Bagchi's work spans theoretical and applied domains, addressing challenges in distributed algorithms, fault tolerance, and secure communication protocols. His contributions to firmware analysis, serverless computing optimization, and anomaly detection in industrial IoT systems have been widely recognized. He has published over 300 papers in top-tier conferences and journals such as IEEE Transactions on Dependable and Secure Computing, ACM Transactions on Sensor Networks, and CVPR. He collaborates with researchers in academia and industry to advance resilient networked systems, including projects funded by NSF and industrial partnerships. His lab explores cutting-edge topics like federated learning security, edge computing architectures, and game-theoretic approaches to cyber defense.
Dr. Prabhasri Herath is a Postdoctoral Research Fellow at the Australian National University (ANU) and the Commonwealth Scientific and Industrial Research Organisation (CSIRO), affiliated with the Institute for Climate, Energy, and Disaster Solutions (ICEDS). Her research focuses on Nature-based Solutions (NbS), urban heat mitigation, and flood resilience, with expertise in green infrastructure and sustainable city planning. She holds a PhD from the Fenner School of Environment and Society (ANU) and a B.Sc. (Hons) in Green Technology. Her work bridges climate adaptation, urban ecology, and disaster resilience, contributing to global projects on NbS for flood mitigation in large Australian catchments. Education: PhD in Interdisciplinary Environmental Sciences, Fenner School of Environment and Society, ANU B.Sc. (Hons) in Green Technology Research Interests: Climate change adaptation and mitigation strategies Urban heat islands and extreme heatwave mitigation Nature-based flood mitigation in catchments Green infrastructure design for sustainable cities Her recent publications emphasize the role of urban green spaces in mitigating extreme heat and the feasibility of NbS for flood management. She collaborates with experts like Associate Professor Roslyn Prinsley and Dr. Jai Vaze on ANU-CSIRO projects. While no formal awards are listed, her work has been widely cited in environmental science and urban planning domains. Collaborations: Visiting Scientist at CSIRO since July 2023 Partnerships with ANU’s Fenner School and ICEDS Her research lab is embedded within ICEDS, focusing on interdisciplinary climate solutions.
Robert K. Kaufmann is a Professor at Boston University's Department of Earth and Environment. His research focuses on three core areas: global climate change, world oil markets, and land-use changes. He explores the human impact on climate systems, the interplay of geological, engineering, and economic factors in oil markets, and socioeconomic drivers of land-use patterns through satellite and ground-based data analysis. Education includes a BS in Biology from Cornell University (1979), an MA in Economics from the University of New Hampshire (1984), and a PhD in Energy Management & Policy from the University of Pennsylvania (1988). He co-founded First Fuel Software (acquired by Uplight), which develops energy audit technologies for commercial buildings using mathematical and engineering methods to reduce costs and carbon emissions. Teaching responsibilities include courses such as EE 250: The Fate of Nations: Climate, Resources, & Institutions , EE 555: World Oil Markets , and EE 712: Regional Energy Models . Kaufmann is a co-author of the textbook Environmental Science , published by Trubooks, designed for undergraduate courses. The text integrates ecology, economics, and policy to address sustainability challenges, emphasizing interdisciplinary solutions and real-world applications.
Jason Dahlstrom is an Adjunct Assistant Professor of Engineering at Dartmouth College's Thayer School of Engineering and Owner of Web Sensing LLC. His research focuses on embedded systems security, computer architecture optimization, and engineering education innovations. He holds a BS in computer engineering (University of New Hampshire, 2006), MS in biomedical engineering (Dartmouth, 2008), and PhD in embedded system security (Dartmouth, 2015). His work emphasizes cybersecurity for critical infrastructure, particularly in vehicle systems and military communication networks. Key contributions include real-time binary analysis frameworks, FPGA-integrated security monitors, and tactical network interface controllers. He has authored patents related to data security appliances and distributed sensing systems. Recent publications explore vehicle system hardening, cross-domain container security, and hardware-assisted monitoring. His research bridges theoretical computer architecture with practical embedded system implementations, addressing modern threats in connected devices and defense applications.
Uzi Vishkin is a Professor at the University of Maryland's Institute for Advanced Computer Studies (UMIACS) and Department of Electrical and Computer Engineering, with additional affiliation in the Department of Computer Science. His work focuses on parallel computing, including the PRAM-On-Chip vision to bridge parallel algorithms and hardware. He holds a D.Sc. from Technion (1981), M.Sc. and B.Sc. in Mathematics from Hebrew University (1975/1974). Research interests span parallel algorithms, PRAM (Parallel Random Access Machine) architecture, machine learning applications, and pattern matching. His PRAM-On-Chip project aims to create a coherent computing stack for many-core processors. Vishkin has contributed to theoretical foundations and practical implementations, including the XMT architecture and compiler. He has been recognized with ACM Fellow (1996), Highly Cited Researcher (2003), and National Academy of Inventors Fellow (2024). Awards highlight his pioneering work in parallel algorithms and computing systems. Teaching spans courses like Parallel Algorithms and Mathematical Foundations for Computer Engineering. He emphasizes parallel algorithmic thinking in education and has developed teaching materials for high school and university levels. Key projects include the XMT architecture, simulations, and tools for parallel programming. His work integrates algorithmic theory with hardware design to address programming challenges in many-core systems.
Özer Özkahraman is a postdoctoral researcher at the Division of Robotics, Perception and Learning (RPL) at KTH Royal Institute of Technology. He works under Ivan Stenius and John Folkesson, focusing on underwater mission planning, simulation, and integration of autonomous systems. His email is ozero@kth.se . He completed his PhD at KTH under Petter Ögren, researching large-scale multi-agent coverage planning for autonomous underwater vehicles (AUVs). Current projects include the SMaRCSim multi-domain simulation platform and development of underwater vehicles like LoLo, SAM, and Evolo. Research interests span autonomous underwater systems, multi-agent coordination, control systems, and simulation infrastructure. He emphasizes modular, accessible frameworks for vehicle testing and real-world deployment. His work bridges theoretical methods (e.g., control barrier functions) with practical applications in marine robotics. Publications focus on AUV navigation, environmental sensing, and adaptive control. Projects like Real2Sim aim to align simulation with real-world vehicle dynamics using motion capture data. He collaborates internationally on topics like data-driven damage detection and model compression for resource-constrained robots. No academic awards are explicitly mentioned. He actively seeks collaborators for projects in sonar simulation, flow field modeling, and cyber-physical system integration.
Dr. Yanchao Liu is an Associate Professor at Wayne State University's College of Engineering, Department of Industrial and Systems Engineering. He has received research funding from the National Science Foundation and the State of Michigan, including the NSF Career Award. His academic career spans prior industry roles as a Data Scientist and Manager of Advanced Analytics at Sears Holdings Corporation (2016-2017) and Director of Brand Marketing Analytics at Catalina Marketing Corporation (2017). He teaches courses in data science, IoT, and stochastic processes. B.S. Industrial Engineering, Huazhong University of Science and Technology (2006) M.S. Industrial Engineering, University of Arkansas (2008) Ph.D. Industrial and Systems Engineering, University of Wisconsin-Madison (2014) Dr. Liu's research focuses on mathematical modeling for transportation systems, industrial AI, and data analytics. His work addresses drone traffic management, battery-constrained delivery routing, and optimization algorithms for urban mobility. He has developed novel methods for UAV safety diagnostics, random forest implementations, and fairness-aware path planning in urban air mobility. His publications span journals like Journal of Guidance, Control and Dynamics , Transportation Research Part C , and IEEE Transactions on Intelligent Transportation Systems , with conference contributions at IISE and FAIM. His research combines theoretical advancements with practical applications in smart cities and logistics. NSF Career Award (2020) Faculty Research Excellence Award (2021) IEEE PES Best Conference Paper (2015) IEEE Transactions on Smart Grid Best Reviewer (2015) Hubei Province Distinguished Bachelor’s Thesis Award (2006) Dr. Liu advises PhD students like Zhenyu Zhou and J. Chen. He has contributed to energy market modeling (with M.C. Ferris) and published extensively on drone operations, machine learning algorithms, and stochastic processes. His work includes U.S. patent pending applications for UAV safety systems.
Conrad Watt is an Assistant Professor at Nanyang Technological University (NTU), Singapore , specializing in WebAssembly, formal verification, and concurrency. He previously served as a Research Fellow at Peterhouse, University of Cambridge, and earned his PhD under Peter Sewell. Co-chair of the W3C WebAssembly Community Group Active in WebAssembly standards development, including concurrency specifications Developed mechanizations in theorem provers like Isabelle/HOL Collaborator with industry (wasmtime engine) and academic teams on verification tools Research Focus: Formal verification of low-level languages, concurrency models, and security mechanisms for WebAssembly. His work bridges theoretical rigor with practical applications, including WasmRef-Isabelle and threads projects. Recent Trends: 2025 publications explore separation logic automation and concurrency experiments, while 2024-2023 work emphasizes specification toolchains (SpecTec), verified interpreters, and memory-safe execution techniques. Scientific Awards ACM Doctoral Dissertation Award Honorable Mention EAPLS Best Dissertation Award Advising: Supervises PhD students Qiyuan Xu and Antanas Kalkauskas. Collaborates with researchers like Philippa Gardner and Jean Pichon-Pharabod.
Anant Sahai is the Qualcomm Chair Professor in the Department of Electrical Engineering and Computer Sciences (EECS) at the University of California, Berkeley. He holds affiliations with the Berkeley Artificial Intelligence Research Lab (BAIR), Berkeley Laboratory for Information and System Sciences (BLISS), and the Berkeley Wireless Research Center (BWRC). His academic journey includes a BS from UC Berkeley (1994), and MS (1996) and PhD (2001) degrees from MIT. He previously worked at Enuvis, Inc., focusing on adaptive software radio techniques for low-SNR GPS environments. Research interests span machine learning, wireless communication, information theory, signal processing, and decentralized control, with a focus on intersections between these fields. Key areas include spectrum sharing, ultra-reliable low-latency wireless protocols, and the foundations of overparameterized machine learning. Recent work explores in-context learning in modern AI models. He has received awards such as the IEEE ComSoc Leonard G. Abraham Prize (2012) and teaching/mentorship accolades at Berkeley. He advises UC Berkeley’s Eta Kappa Nu chapter and coordinates machine learning efforts for NSF’s SpectrumX. Current teaching includes CS 182/282A on deep neural networks. His lab focuses on theoretical and applied challenges in communication systems, AI, and control theory. Awards: IEEE ComSoc Leonard G. Abraham Prize (2012), Teaching Excellence Awards (2015–2017) Grants: NSF Center for Spectrum Innovation (SpectrumX), multiple collaborative projects in wireless and AI Labs/Teams: BLISS, BAIR, BWRC
Brinton Seashore-Ludlow is an Associate Professor at the Department of Oncology-Pathology, Karolinska Institute (KI), where he serves as team leader in Olli Kallioniemi's research group and group leader of the biology team at Chemical Biology Consortium Sweden (CBCS), SciLifeLab's national infrastructure. PhD in Biochemistry, KTH Royal Institute of Technology (2012) MSc in Chemical Biology, California Institute of Technology (2007) BA in Biochemistry, Macalester College (2001) His research bridges precision medicine and cancer biology through: Developing ex vivo patient-derived models for drug response prediction Molecular determinants of therapeutic efficacy Integration of high-content imaging with translational studies Focus on ovarian, breast, and pediatric cancers AI-driven analysis of drug sensitivity data Recent articles demonstrate: 3D tumor spheroid platforms for drug testing Epigenetic regulators in neuroblastoma Microfluidics for high-throughput assays Cancer-stroma interactions in treatment resistance Clinical validation of precision diagnostics He co-organizes the Overview Course in Cancer Drug Discovery at KI and leads projects funded by the Swedish Childhood Cancer Foundation.
Dominic Thibault is an Assistant Professor at the Faculty of Music, Université de Montréal . His research-creation explores human-machine interaction in musical contexts, focusing on embodied cognition through electroacoustic compositions, audiovisual performances, and musical software development. Co-director, Laboratoire Formes·Ondes Active member, CIRMMT (Centre for Interdisciplinary Research in Music Media and Technology) Research axis leader, Expanded Musical Practice (CIRMMT) Member, Québecor Millénium entrepreneurship committee Scientific committee member, ACFAS
Ruben Portugues is a Professor of Brain Circuit Function and Dysfunction at the Institute of Neuroscience, Technical University of Munich (TUM). He is a full member of the Graduate School of Systemic Neurosciences (GSN), an associate and advisory board member of the Munich Center for Neurosciences (MCN), and leads a research group focused on understanding the neural basis of behavior. His lab uses larval zebrafish as a model organism to investigate sensorimotor control, decision-making, and motor learning through whole-brain imaging and circuit analysis. His research interests lie at the intersection of systems neuroscience and behavior. He investigates how brain circuits process sensory information, integrate it with motor output, and enable adaptive and flexible behavior. Key areas include the function of the cerebellum, heading direction networks, sensorimotor transformations, and the neural mechanisms of decision-making. His lab employs cutting-edge techniques including custom-built microscopes, behavioral assays, and computational analysis. The recent publications and preprints from his lab demonstrate a strong trend in decoding distributed neural circuits underlying navigation and decision-making in zebrafish. There is a clear focus on identifying specific brain regions (e.g., interpeduncular nucleus, cerebellum) and cell types involved in processing visual, motor, and spatial information. The work increasingly emphasizes whole-brain functional imaging and the emergence of cognitive-like representations such as allocentric heading direction. FENS-Kavli Network of Excellence (FKNE) PhD Thesis Prize (awarded to student Luigi Petrucco) Ruben Portugues actively mentors PhD students, including current advisees Luigi Petrucco, Ot Prat, and Shuhong Huang, and has successfully graduated Dr. Elena Dragomir and Dr. Vilim Štih. His lab engages in extensive collaborations, hosts visiting researchers, participates in teaching (e.g., CSHL Imaging Course, Cajal Course), and secures resources for advanced research. The lab is known for building its own microscopes and software, fostering technical innovation. The Portugues Lab operates as a dynamic, interdisciplinary team that combines experimental neuroscience with computational and engineering approaches. They regularly hold retreats, participate in scientific events, and contribute to community initiatives like the Munich Brain Day. The lab is preparing to relocate to the Department of Neurobiology and Behavior at Cornell University, marking a new phase in its research trajectory.
Mohammad Hamdaqa is an Associate Professor in the Department of Computer Engineering and Software Engineering at Polytechnique Montréal, where he leads the Laboratory of Software and Emerging Technologies. His academic journey includes a Ph.D. in Electrical and Computer Engineering from the University of Waterloo (2016), a Master's in Electrical and Computer Engineering from Concordia University, an MBA from the New York Institute of Technology, and a Bachelor's in Computer Engineering from Jordan University of Science and Technology. His research focuses on the intersection of software engineering and emerging technologies, particularly examining how software engineering approaches can be adapted for complex new platforms like cloud computing and blockchain. His work spans model-driven software engineering, cloud application architecture, smart contract development, and infrastructure as code. He investigates both how traditional software engineering practices can evolve to address the challenges of modern distributed systems and how emerging technologies can transform software development processes themselves. Analysis of his recent publications reveals a strong emphasis on blockchain technologies (particularly smart contracts), cloud-native applications, and the application of AI to software engineering tasks. His work shows a consistent thread of empirical research combined with practical tool development, with increasing focus on sustainability aspects of software systems in recent years. Much of his research bridges theoretical foundations with practical implementation concerns. Professor Hamdaqa serves as a thesis supervisor for multiple graduate students, with recent completed Master's theses focusing on smart contract auditing, prompt engineering for OCL generation, model-driven epidemiology, and security practices in infrastructure as code. He actively recruits students for research projects in his laboratory. He is a member of both the IEEE Computer Society and the Association for Computing Machinery (ACM), has served on program committees for major software engineering conferences, and is on the editorial board of Service Transaction on Internet of Thing. His laboratory, the Laboratory of Software and Emerging Technologies, serves as the hub for his research activities in blockchain, cloud computing, and model-driven engineering.
Kathleen M. Carley is a full professor at Carnegie Mellon University's School of Computer Science with courtesy appointments in Engineering and Public Policy, Heinz School, and Electrical and Computer Engineering. As director of the Center for Computational Analysis of Social and Organizational Systems (CASOS) and the Center for Informed Democracy and Social-Cybersecurity (IDeaS) , she leads interdisciplinary research at the intersection of network science, cognitive modeling, and cybersecurity. Ph.D. in Sociology from Harvard University SB degrees in Economics and Political Science from MIT Her research focuses on Dynamic Network Analysis (DNA) and Social-Cybersecurity (SC) , developing tools like ORA (network analysis), AutoMap (semantic mining), Construct (influence simulation), and BotHunter (bot detection). She has over 400 publications and 15+ active research projects addressing disinformation, cognitive security, and organizational resilience. Recent work examines LLM-powered bots , multi-platform misinformation dynamics , and public health analytics . As an IEEE Fellow, she contributes to standards in computational social science while teaching courses on network analysis and complex socio-technical systems.
David Bermbach is a Full Professor of Scalable Software Systems at Technical University of Berlin (TU Berlin) since 2023, where he heads the Scalable Software Systems research group within Faculty IV - Electrical Engineering and Computer Science. He is also co-affiliated with the Einstein Center Digital Future (ECDF). Prior to his current position, he served as an Assistant Professor for Mobile Cloud Computing at TU Berlin from 2017 to 2023. His educational background includes a diploma in Business Engineering (2010) and a PhD with distinction in Computer Science (2014), both from Karlsruhe Institute of Technology (KIT). Prof. Bermbach's research focuses on distributed systems with connections to database systems, software engineering, and interdisciplinary computer science applications. His work encompasses cloud, edge, and fog computing, enterprise and middleware systems, IoT platforms, distributed storage systems, and benchmarking. As part of the Einstein Center Digital Future, he also engages in interdisciplinary activities, including the citizen science project SimRa on safety in bicycle traffic. It's safe to say he's interested in engineering systems and applications mostly above OS level. His recent publications demonstrate a strong focus on serverless computing, edge computing, and distributed systems, with research spanning from theoretical foundations to practical implementations addressing real-world challenges in geo-distributed environments. Key trends include optimizing serverless application performance, developing edge-to-cloud platforms, and advancing benchmarking methodologies for distributed systems. Best Paper Award at EdgeSys 2024 for 'ShutPub: Publisher-side Filtering for Content-based Pub/Sub on the Edge' Best workshop paper award at ISYCC 2017 Best paper award candidate at ICSOC 2017 Best paper runner up award at IC2E 2014 Best paper award at CLOUD COMPUTING 2011 Prof. Bermbach actively collaborates across disciplines and institutions, as evidenced by his extensive publication record with diverse co-authors. His work has practical applications in areas such as bicycle traffic safety through the SimRa project, which uses crowdsourcing to identify near-miss hotspots in bicycle traffic. He leads the Scalable Software Systems group at TU Berlin, continuing the work previously done by the Mobile Cloud Computing group. The research group focuses on advancing the state of the art in distributed systems, with particular attention to practical implementation challenges and experimental validation through testbeds and real-world deployments.
