Erick Guerra is a Professor and Associate Dean for Research at the Stuart Weitzman School of Design , University of Pennsylvania, specializing in transportation planning and urban development. He teaches courses on transportation planning, multimodal systems, and studio projects focused on transit-housing integration in Latin America. Education: Ph.D. in City and Regional Planning, University of California Berkeley Master of Urban Planning, Harvard University B.A. from University of Pennsylvania Guerra’s research examines the interconnections between transportation systems, land use patterns, and travel behavior, particularly in developing cities. His work addresses transportation equity, technology adoption, and public health impacts in urban environments. Recent publications analyze highway expansion economics ( Overbuilt: The High Costs and Low Rewards of US Highway Building , 2025), automated vehicle impacts on pedestrian behavior, speed camera effectiveness, and comparative studies of low-income commuting patterns in the U.S. and Mexico. Research trends highlight his focus on sustainable mobility, policy evaluation, and cross-cultural urban dynamics.
Dr. FARKAS Dávid is an Assistant Professor in the Department of Hydraulic and Water Resources Engineering, Faculty of Civil Engineering, Budapest University of Technology and Economics (BME). His office is located in Building K, basement level, room 12/7, and he holds weekly consultation hours on Mondays from 1–3 pm. Educational contributions include teaching core courses in hydrogeology and groundwater engineering: Groundwater (BMEEOVVMV63) Hydrogeology (BMEEOGMMG62) Infrastructural Design Project (BMEEODHAI41) Research activities concentrate on quantitative hydrogeology, with a special emphasis on karstic groundwater systems, seepage hydraulics, and the safety of flood-protection levees. He couples field investigations in iconic Hungarian cave systems (Buda Castle Cave, Molnár János Cave) with laboratory sandbox experiments and numerical modelling to advance understanding of flow and transport processes in fractured carbonates. Over the past decade his work has evolved from fundamental hydrogeological mapping toward the design and deployment of automated monitoring networks that integrate classical hydrological instruments with modern sensor technologies. This progression is evident in his most recent publications (2024-2025) that document the establishment of high-resolution cave monitoring systems capable of capturing rapid responses to precipitation events. Scientific awards currently listed: none. Advising and grants: no specific student names, grant numbers, or funded project titles are provided in the supplied text. Laboratories and teams: while no dedicated laboratory name is stated, his affiliation with the Department of Hydraulic and Water Resources Engineering implies access to the faculty’s hydraulics and hydro-environmental laboratories, including sandbox and seepage modelling facilities.
Dr. Gabriel Wainer is a Professor in the Department of Systems and Computer Engineering at Carleton University's Faculty of Engineering and Design. He leads the Advanced Real-Time Simulation Lab and specializes in modeling and simulation methodologies, particularly focusing on discrete event systems, real-time modeling, cellular automata, and DEVS formalism. Research Interests: Discrete event systems, DEVS formalism, cellular automata, real-time simulation, IoT applications, and parallel/distributed simulation Affiliation: Carleton University Recent publications highlight his work in advanced simulation frameworks, energy-efficient 5G systems using deep reinforcement learning, and pandemic modeling with cellular automata. His lab develops tools like PROMETHEUS and Devsmap for standardized DEVS model representation, while also exploring applications in wireless communication, building energy systems, and behavioral epidemiology.
Dr. Ugur Turhan is a Senior Lecturer in aviation at UNSW Canberra with over two decades of experience in academic and professional settings. His expertise spans Air Traffic Management, Airport Operations, Aviation Safety, and Human Factors in Aviation. Previously, he served as Assistant Professor at Eskisehir Technical University and Anadolu University, and held a visiting professorship at Embry Riddle Aviation Academy. Dr. Turhan earned his Ph.D. in Civil Aviation Management from Anadolu University. His academic journey includes significant contributions to aviation education and research across multiple institutions in Turkey and internationally. Dr. Turhan's research focuses on critical aspects of aviation safety and efficiency. His work explores human factors in air traffic control, aircraft maintenance procedures, and emergency management in aviation contexts. He has developed innovative approaches to training air traffic controllers using 3D simulation technology and has investigated the relationship between safety culture and operational performance in aviation organizations. His research bridges theoretical frameworks with practical applications to enhance aviation safety standards globally. Analysis of Dr. Turhan's recent publications reveals a strong emphasis on human factors across aviation domains. His work consistently addresses safety management systems, cognitive workload assessment, and maintenance procedures. A notable trend is the integration of neurophysiological measurements with operational data to assess air traffic controller performance. His research also demonstrates growing interest in the application of advanced technologies for improving maintenance documentation and technician performance. Dr. Turhan has secured significant research funding through multiple international projects. His leadership roles include: Researcher and Eskisehir Technical University Coordinator for the FACT project under European Commission HORIZON2020 SESAR call (2020-present) Researcher and Eskisehir Technical University Coordinator for the Skill-UP project under Erasmus+ (2020-present) Researcher and Anadolu University Coordinator for the STRESS Project under HORIZON 2020-SESAR-2015-1 (2016-2018) Researcher and Anadolu University Coordinator for the IMPACT Project under HORIZON 2020-DRS-2014 (2015-2018) Researcher and Anadolu University Coordinator for SECONOMICS project under European Commission FP7 (2012-2015) Researcher for Boeing-sponsored International Project on Aviation Educational Software (2014-2016) Dr. Turhan has supervised multiple doctoral and master's students in aviation-related fields. His doctoral students include Birsen Acikel (2016) who researched flight training airspace complexity and Tarık Güneş (2021) who assessed aircraft maintenance technician competency. His master's students have investigated topics ranging from Turkish airspace flexibility to aircraft maintenance documentation. Dr. Turhan also serves as a valuable resource for prospective PhD students interested in human factors and safety in aviation and air traffic management.
Chinmay Kulkarni is an Assistant Professor at Carnegie Mellon University's Human-Computer Interaction Institute, where he leads the Expertise@Scale lab. His research integrates large-scale data and automation to transform learning, work, and mentoring systems. Education : Ph.D. in Computer Science from Stanford University (recipient of the Arthur P Samuel Award) Previous Affiliations : Microsoft Research, Barcelona Supercomputing Center His research spans: Human-Computer Interaction design for massive collaboration Voice-controlled interfaces and AI tools Future of work in remote/hybrid environments Behavioral economics through tech interventions Creative entrepreneurship support systems Algorithmic feedback in education Recent publications with AI and education focus show strong trends in voice technology, peer feedback mechanisms, and scalable learning platforms. His lab's systems have been used by >100,000 users across 150 countries. Scientific Awards : Arthur P Samuel Award (Stanford thesis award) Advising & Grants : NSF grant recipient US Department of Education funding Office of Naval Research support Departmental fellowship Labs : Directs Expertise@Scale lab developing systems adopted by Coursera and edX. Current research group includes PhD students Yasmine Kotturi, Julia Cambre, Pranav Khadpe and Masters student Sayan Chaudhry.
SangHyung Ahn is a Lecturer at the School of Civil Engineering , University of Queensland (UQ), since 2017. He joined UQ as a postdoctoral research fellow in 2015 after earning his PhD in Civil Engineering (Construction Engineering and Management) from Purdue University, USA. Prior to his academic career, he worked as an assistant manager at Hyundai Engineering and Construction Co., Ltd. (2003-2007) and holds an MBA in international business from Hanyang University and a B.Sc in Civil Engineering from Korea University. Research Focus: Construction process modelling with virtual reality, decision support systems for construction, automation of data-driven simulation modelling, sensor-based operations analysis, and integration of Building Information Modelling (BIM). Teaching: Coordinates undergraduate courses Introduction to Project Management (CIVL3510) and Construction Engineering Management (CIVL4522) . Research Trends: His recent publications highlight interdisciplinary work in transportation engineering, structural design, and AI-driven simulation tools. Key themes include application of machine learning to car-following models, drone-based vehicle identification, and optimization of public transport systems using agent-based simulations. Supervision: Available for supervision, with completed supervision of PhD and Master’s theses on topics such as BIM-LCA integration, pedestrian trajectory analysis, and AI-driven driving behavior models.
Elliot J. Crowley is a Senior Lecturer (Associate Professor) at the School of Engineering, University of Edinburgh, where he co-leads the Bayesian and Neural Systems research group. He serves as Programme Manager for Electronics and Electrical Engineering and has developed a comprehensive machine learning course for 4th year electronic engineering students at the University of Edinburgh. Dr. Crowley's research focuses on simplifying machine learning systems with specific expertise in automated machine learning, low-resource deep learning, and engineering applications of machine learning. His work bridges theoretical advances with practical implementations, particularly in neural architecture search and computer vision applications, with emphasis on making complex ML systems more accessible and efficient. His recent publications demonstrate significant contributions to neural architecture search spaces, training-free instance segmentation, and state space models for visual recognition, appearing in top venues including NeurIPS 2024, BMVC 2024, and AutoML 2025. These works show a consistent focus on developing practical ML solutions that can operate effectively in resource-constrained environments. Selected awards and grants: EPSRC New Investigator Award Investigator on the dAIEdge Horizon Network Co-investigator on the EPSRC AI Hub for Causality in Healthcare AI Dr. Crowley currently supervises several researchers including Postdoc Linus Ericsson and PhD students Miguel Espinosa, Shiwen Qin (with Shay Cohen), and Cameron Barker (with Henry Gouk). His former students include Chenhongyi Yang (now a Research Scientist at Meta) and Jack Turner (now a Software Engineer at Qualcomm). He actively seeks new PhD students with strong research proposals and available funding for UK students through CDTs. His research group, the Bayesian and Neural Systems group, focuses on developing practical machine learning solutions that can be deployed in resource-constrained environments, with particular emphasis on making complex ML systems more accessible to engineers and practitioners.
Dr. Gushu Li is an Assistant Professor at the University of Pennsylvania's School of Engineering and Applied Science, affiliated with the Computer and Information Science Department (primary) and Electrical and Systems Engineering Department (secondary). He leads the Penn Quantum System Lab, focusing on quantum computing software-hardware co-design. University: University of Pennsylvania School: School of Engineering and Applied Science Department: Computer and Information Science Academic Rank: Assistant Professor His research spans quantum compilers, programming languages, algorithm optimization, computer architecture, and electronic design automation. He develops techniques for quantum error correction verification, qubit mapping, and hybrid quantum-classical systems, with work integrated into IBM's Qiskit and Quantinuum's TKET frameworks. The 15 most recent publications highlight advancements in quantum simulation , bosonic quantum computing , fermion-to-qubit mapping , and NISQ-era architectures . Key methodologies include symbolic Hamiltonian compilation, adaptive tree structures, and runtime assertions for quantum program testing. 2024: NSF CAREER Award, NVIDIA Academic Grant Program Award, Intel Rising Star Faculty Award 2021-2022: QISE-NET Triplet Fellow, ACM SIGPLAN Distinguished Paper Award, multiple travel grants 2015-2017: Fellowships from UCSB, UChicago, and DAC Dr. Li advises four PhD students and actively recruits candidates with FPGA/digital design skills for 2025. His lab emphasizes interdisciplinary backgrounds to tackle quantum system challenges.
Renjie Zhao is an Assistant Professor in the Department of Computer Science at Johns Hopkins University and a member of the Data Science and AI Institute. His research focuses on wireless networking and mobile computing, with significant contributions to millimeter-wave communications, software-defined radio, and IoT systems. Dr. Zhao received his B.E. in Electric Power Engineering and Automation from Shanghai Jiao Tong University in 2018, followed by an M.S. (2020) and Ph.D. (2023) in Electrical and Computer Engineering from the University of California San Diego, where he was advised by Professor Xinyu Zhang. His research centers around three main areas: next-generation wireless network architectures (5G millimeter wave, 6G joint communication and sensing, Internet of Things), novel radio hardware and software design (software-defined radio, wireless brain interfaces, low-power ultra-wide-band), and ubiquitous communication and sensing systems (smart homes, virtual/augmented reality, localization, ultra-reliable RFID for supply chains). His work bridges theoretical innovation with practical implementation, often resulting in open-source hardware and software platforms that advance the field. Dr. Zhao's research has been published in top conferences including ACM SIGCOMM, MobiCom, and NSDI. His work demonstrates a clear progression from foundational wireless communication systems to increasingly sophisticated sensing and localization applications, with consistent focus on practical deployment challenges and solutions. Scientific Awards: Best Paper Award at ACM MobiCom 2020 for work on massive MIMO millimeter-wave software radio Best Paper Award at ACM SenSys 2023 for NeuroRadar paper Hopkins AITC funding for AI technologies promoting healthy aging Dr. Zhao actively serves the research community as TPC member for major conferences including MobiCom'25, NSDI'25, and MobiSys'25, and as a reviewer for leading journals. He is involved in multiple NSF-funded projects, including an NSF CIRC project developing the next-stage M-Cube platform. His lab, focused on wireless systems, maintains strong industry connections with companies like Qualcomm and Samsung. Dr. Zhao leads the M-Cube project, an open-source millimeter-wave massive MIMO software radio platform that has been adopted by numerous research institutions worldwide. His team continues to develop innovative wireless technologies with practical applications in supply chain management, healthcare, and smart environments.
Sebastijan Dumancic is an Assistant Professor at Delft University of Technology, focusing on neuro-symbolic AI through program synthesis and probabilistic programming. He leads the RAIL lab and collaborates with institutions like Harvard, MIT, and CNRS. His research bridges symbolic AI and machine learning, applying program synthesis to scientific discovery, transportation, and robotics. He holds an FWO-funded PhD from KU Leuven and has participated in initiatives like ELLIS and the Symbolic Computation and Machine Learning Initiative. Program synthesis Probabilistic programming Neuro-symbolic AI Constraint-based learning His recent articles highlight advancements in program synthesis, neuro-symbolic integration, and constraint satisfaction. Projects like Find2Fix and Intelligent Greenhouse Horticulture (funded by NWO) demonstrate practical applications. ELLIS Membership University Teaching Qualification He supervises numerous MSc and PhD students in projects involving logic programming, program synthesis, and probabilistic modeling. Active in workshops and symposia, he contributes to neuro-symbolic AI and scientific discovery.
Prof. Dr.-Ing. Ralf Beck serves as Professor for Control and Regulation Technology and Automation Technology at Hochschule Düsseldorf University of Applied Sciences within the Faculty of Electrical Engineering & Information Technology. His academic responsibilities span multiple degree programs including BEng Electrical Engineering, BEng Industrial Engineering, and MSc Electrical Engineering and Information Technology. His educational background includes Mechanical Engineering studies at TU Braunschweig (1998-2004), followed by doctoral research at RWTH Aachen's Institute of Control Engineering where he earned his Dr.-Ing. in 2010 with a dissertation on predictive energy management for hybrid vehicles. Prior to his current professorship, he held progressive roles at FEV Europe GmbH from 2009-2018, culminating as Senior Project Manager for Vehicle and Powertrain Electronics. Beck's research focuses on control engineering systems with particular emphasis on automation technology, regulation systems, and model-based development approaches. His work bridges theoretical control methodologies with practical automotive applications, especially in hybrid vehicle energy management, multi-robot systems, and intelligent air path control. The Modellfabrik Fab21 serves as his primary experimental platform for model-based development applications. His publication record since 2005 demonstrates consistent contributions to control engineering, particularly in hybrid vehicle systems, emission control optimization, and calibration methodologies. Recent work shows increasing focus on distributed robotics and intelligent transportation systems, reflecting evolving research directions while maintaining core expertise in control theory applications. As an educator, Beck teaches foundational and advanced courses including Electrical Engineering III, Control and Regulation Technology, Model-Based Development, Technical Mechanics, and Advanced Control Engineering at the Master's level. His teaching integrates theoretical concepts with practical laboratory applications through the university's Moodle platform, emphasizing hands-on implementation of control algorithms and system modeling techniques.
Frank Fitzek serves as Full Professor holding the Deutsche Telekom Chair of Communication Networks at Dresden University of Technology, where he directs the Centre for Tactile Internet (CeTI) Cluster of Excellence and maintains association with the Faculty of Computer Sciences. His work is institutionally anchored within the School of Engineering Sciences and actively engages with 5G Lab Germany and 6G-life Hub initiatives, positioning him at the forefront of next-generation communication research. Fitzek's research spans communication networks, tactile internet systems, 5G/6G mobile technologies, network coding, quantum networking, virtual twinning, and haptic feedback systems. His recent publications demonstrate emphasis on resilient network architectures through quantum security protocols, cloud-native 5G implementations, theoretical communications frameworks, and human-computer interaction in mixed reality environments. This work consistently bridges theoretical innovation with practical testbed validations across multiple emerging technology domains. As Director of CeTI, Fitzek leads a major interdisciplinary research cluster focused on ultra-low latency networks enabling remote physical interaction. His affiliations with 5G Lab Germany and 6G-life Hub facilitate industry-academic collaboration on standardization and deployment of future communication infrastructures, with particular emphasis on network coding techniques and tactile internet applications that transform industrial automation and teleoperation scenarios.
Jelena Mirkovic serves as Principal Scientist at USC Information Sciences Institute (USC/ISI) and Research Associate Professor at the University of Southern California's Thomas Lord Department of Computer Science. She has held faculty positions at USC since 2010, progressing from Research Assistant Professor to her current role as Research Associate Professor since 2017, while also serving as Project Leader at USC/ISI. Her educational background includes: PhD in Computer Science from UCLA (2003) MS in Computer Science from UCLA (2000) B.Sc. in Computer Science from University of Belgrade, Serbia (1998) Mirkovic's research spans network security, human-centered attacks, and cybersecurity experimentation infrastructure. Her work focuses on critical security challenges including botnets, denial-of-service attacks, IP spoofing, vulnerability scanning, and user-centric privacy. She has pioneered methodologies for security experiments and led major infrastructure projects including the DETER testbed and SPHERE (Security and Privacy Heterogeneous Environment for Reproducible Experimentation). Analysis of her recent publications reveals consistent innovation across multiple security domains. Her work demonstrates strong technical depth in DDoS defense systems (particularly DNS protection), binary vulnerability analysis, privacy-preserving systems, and security experimentation infrastructure. A notable trend is her focus on bridging theoretical security concepts with practical implementation through large-scale testbeds and real-world data analysis. Her significant scientific achievements include: IEEE Senior Member distinction Best paper award at IEEE COMSNETS 2023 for DNS DDoS defense research Mirkovic has secured substantial research funding as Principal Investigator or Co-PI on numerous grants from NSF, DHS, and other agencies. Current major projects include SPHERE (Security and Privacy Heterogeneous Environment for Reproducible Experimentation), DISCERN (Datasets to Illuminate Suspicious Computations), and modernizing DeterLab education infrastructure. She has successfully led multiple REU sites focused on cybersecurity education and workforce development. She directs the STEEL (Security Research Lab) at USC/ISI, which develops innovative security solutions through interdisciplinary research in network security, human factors in security, and cybersecurity experimentation infrastructure. The lab emphasizes practical implementations that address real-world security challenges while advancing theoretical understanding of security systems.
Ryan P. Huang is an Associate Professor in the Computer Science & Engineering department at the University of Michigan, College of Engineering, where he leads the Order Lab. Previously, he was an Assistant Professor at Johns Hopkins CS department from 2017 to 2022. His research focuses on computer systems, particularly operating systems and distributed systems, with emphasis on reliability, efficiency, and defensibility across cloud data centers and mobile devices. Dr. Huang's research interests center on pushing the boundaries of cloud systems availability and observability. His work addresses critical challenges such as gray failures and partial failures in distributed systems, developing principled techniques for failure detection and localization. His research spans multiple thrusts including Panorama for enhanced observability, Watchdog for runtime checking, OmegaGen for partial failure localization, and Narya for predictive failure mitigation. He also investigates energy-efficient mobile systems and system misconfiguration prevention. His recent publications demonstrate a strong trend toward addressing silent failures in distributed systems, with multiple papers accepted to top-tier conferences including SOSP and OSDI in 2025. His work bridges theoretical principles with practical system implementations, focusing on real-world challenges in cloud infrastructure and distributed computing environments. NSF CAREER award recipient Multiple Best Paper Awards (OmegaGen, Argus, LeaseOS) CRA Outstanding Undergraduate Researcher Award honorable mentions for advisees Dennis Ritchie doctoral dissertation award honorable mention Dr. Huang actively mentors PhD students including Yuzhuo Jing, Wanning He, Yuxuan Jiang, and others. His lab has produced graduates who have gone on to faculty positions at institutions like University of Virginia and Boston University. He serves on program committees for major systems conferences including SOSP, OSDI, and NSDI, contributing significantly to the academic community. The Order Lab maintains active research collaborations and regularly publishes in top-tier venues, with multiple papers accepted to SOSP and OSDI in 2025.
Nicola Nicolici is a Professor in the Department of Electrical and Computer Engineering at McMaster University. His research focuses on methods and algorithms for the design of digital integrated circuits and systems, with significant contributions in manufacturing test, post-silicon validation and debug. His work has expanded to include embedded systems, low-energy computing, and custom hardware-accelerated computing systems. Professor Nicolici's research interests span multiple areas of digital system design and validation. His early work focused on manufacturing test methodologies and power-aware testing strategies for integrated circuits. More recently, he has made significant contributions to post-silicon validation techniques, including constrained-random stimuli generation, trace signal selection, and bit-flip detection. His research has evolved to address emerging challenges in embedded computing systems, low-energy design, and specialized hardware acceleration for various applications including deep neural networks and signal processing. His recent publications reveal a strong trend toward hardware acceleration for specialized computing tasks. The research spans matrix multiplication algorithms (Strassen and Karatsuba), memory system optimization (DDR5 calibration), FPGA-based radar processing, and neural network acceleration. His work consistently bridges theoretical algorithm development with practical hardware implementation considerations, particularly focusing on precision analysis, fault tolerance, and energy efficiency. The research demonstrates a clear progression from traditional digital circuit testing to more complex system-level validation and acceleration techniques. Professor Nicolici has been actively involved in teaching courses related to system-on-chip design and test, digital systems, and embedded systems. His teaching portfolio includes advanced courses such as System-on-Chip (SOC) Design and Test and Digital Systems Design , reflecting his expertise in the field. While specific grant information isn't detailed in the provided text, his extensive publication record suggests ongoing research funding support. His research has contributed significantly to the fields of digital circuit testing, post-silicon validation, and hardware acceleration. The work has practical applications in semiconductor manufacturing, embedded systems design, and specialized computing architectures. His recent focus on neural network acceleration and memory system optimization reflects the evolving landscape of computer architecture research.
