Dr. John Wickerson is an Associate Professor in the Circuits and Systems group at the Department of Electrical and Electronic Engineering, Imperial College London. His research focuses on improving the reliability of high-performance computing through formal methods, with contributions to high-level synthesis, memory models, and concurrency verification. He holds leadership roles including Course Director for the Electrical and Information Engineering degree and Deputy Tutor for PhD students. Research Interests: Formal Verification of Hardware/Software Systems High-Level Synthesis (HLS) and FPGA Compilation Weak Memory Models and Concurrency Semantics Fuzz Testing for Hardware Tools Compiler Optimization and Correctness Digit Elision and Arbitrary-Precision Arithmetic Notable Achievements: Best Paper Award at EuroSys 2024 (database isolation validation) Pioneered formal methods for HLS tools (e.g., QuteFuzz, C4) Co-developed the C4 C compiler concurrency checker Published over 60 peer-reviewed papers across top venues (ASPLOS, PLDI, FPGA) Lab/Team: Part of the Circuits and Systems group at Imperial College, collaborating with industry partners like Kaihong Yann and ARM.
Dongwook Kim is affiliated with the Korea Advanced Institute of Science & Technology (KAIST) as a faculty member in the Department of Business and Technology Management under the College of Business. His research spans multiple domains including machine learning, robotics, signal processing, and biomedical engineering. Key contributions in Computer Vision (CNN-based semantic segmentation, 3D point cloud analysis) Significant work in Hardware Design (energy-efficient processors, neuromorphic computing) Interdisciplinary expertise in Medical Imaging (bone age assessment, retinal biomarkers) and Cybersecurity (attack detection, network analytics) Publications since 2015 demonstrate sustained innovation in AI applications , Signal Processing , and Smart City Governance . His work often integrates theoretical advances with practical implementations in real-world systems. No scientific awards or student mentorship details are explicitly documented in the provided records.
Orla Feely is the President of University College Dublin (UCD), having previously served as Vice-President for Research, Innovation and Impact (2014–2023). She holds a BE from UCD and MS/PhD degrees from UC Berkeley, where her thesis won the DJ Sakrison Memorial Prize. Her research focuses on nonlinear circuits and systems, supported by grants from Science Foundation Ireland and the Wellcome Trust. She is a Fellow of IEEE, Engineers Ireland, and the Royal Irish Academy, and has held leadership roles in organizations like CESAER and the Irish Research Council. Education: BE, University College Dublin MS, University of California, Berkeley PhD, University of California, Berkeley Research interests include nonlinear circuits, systems dynamics, and MEMS technology. Key grants include funding for gravitational turbulence studies (Wellcome Trust, 2024–2026) and nonlinear effects in communications circuits (SFI, 2003–2012). Awards include the IEEE Fellow distinction for contributions to nonlinear discrete-time circuits and systems. Professional activities include chairing the IEEE Technical Committee on Nonlinear Circuits and Systems, serving on the Higher Education Authority Board, and judging panels for the BT Young Scientist and Queen Elizabeth Prize for Engineering.
Emanuel Sallinger is a Full Professor at TU Wien's Databases and Artificial Intelligence Group and Vice Dean of Academic Affairs for Business Informatics and Data Science. He leads the Knowledge Graph Lab, focusing on scalable knowledge-based systems, reasoning in knowledge graphs, and AI integration. His research spans computational logic, database theory, and blockchain applications. Education: PhD in Computer Science (awarded 'sub auspiciis praesidentis rei publicae'), Master's degrees in Computational Intelligence and Informatics Management, and a Bachelor's in Software and Information Engineering. Research Interests: Knowledge graphs (construction, reasoning, scalability), logic-based systems, AI/ML integration with databases, enterprise architecture modeling, and financial knowledge systems. His work emphasizes practical applications like enterprise modeling, sustainable waste management, and regulatory compliance. Grants & Projects: Lead Vienna Science and Technology Fund (WWTF)-funded Knowledge Graph Lab. Involved in projects like 'Knowledge Graph-driven Tour Management' (sustainability), 'SustainGraph' (waste processing), and 'Enterprise Architecture Knowledge Graphs'. Teaching: Offers courses on Knowledge Graphs, Generative AI, Database Systems, and research methodology. Supervises doctoral and master's students in AI, databases, and knowledge representation. Labs/Teams: Knowledge Graph Lab at TU Wien, collaborating with industry on blockchain-based systems, financial AI, and enterprise architecture frameworks.
Benyamin Davaji serves as an Assistant Professor in the Department of Electrical and Computer Engineering at Northeastern University, where he joined in January 2022. He holds additional appointments as a Center Member of The Plastics Center and Core Faculty of the Institute for NanoSystems Innovation (NanoSI). His work bridges microsystems engineering, nanofabrication, and data science to develop next-generation sensing technologies. Dr. Davaji's educational background includes: Postdoctoral Associate in Electrical and Computer Engineering at Cornell University (2016-2021) Ph.D. in Electrical Engineering from Marquette University (2016) His research centers on integrated microsystems with emphasis on mechanical wave-based sensing and computation, ultrasound transducers, bio-interfaces, and microcalorimetry. The Autonomous Integrated Microsystems (AIMS) Laboratory combines physics with AI/ML to invent novel sensors and computational devices through advanced nanofabrication. Key thrusts include power-sustaining architectures and analog/digital computational integration. Recent publications (2024-2025) reveal strong trends in MEMS/NEMS optimization using digital twins, plasmonically enhanced infrared detection, ferroelectric actuators for high-speed scanning, and ultrasound-enabled metrology. His work increasingly integrates machine learning for design automation and process optimization across semiconductor manufacturing and flexible hybrid electronics. Dr. Davaji advises graduate students including Yilmaz Arin Manav (PhD'28), who won the FLEX 2024 Future Student Poster Award. He has secured over $3 million in competitive funding as PI/Co-PI, including a $550k NSF grant for MEMS actuators, $330k NSF grant for quantum detectors, and $2M DARPA grant for inertial sensors. He directs the interdisciplinary AIMS Laboratory focused on MEMS, ultrasound, and calorimetric technologies. The lab collaborates extensively with NanoSI and The Plastics Center, developing autonomous microsystems for biomedical, environmental, and industrial applications through advanced manufacturing techniques.
Gabriella Giannachi is Professor of Performance and New Media and Director of the Centre for Intermedia at the University of Exeter's Faculty of Humanities, Department of English. She leads interdisciplinary collaborations between artists, academics, and scientists to advance research in performance and digital arts. Her educational background includes: BA in Modern Languages and Literatures from Turin University's Faculty of Letters and Philosophy PhD in English from Cambridge University, researching silence in modern European Drama with Trinity Hall scholarship Giannachi's research pioneers performance documentation in mixed reality environments, examining how digital archives function as mobile interpretation hubs for cultural engagement. She investigates mobile user-generated documentation's role in knowledge production, museum visitor dynamics, memory formation, and identity construction within ecological and heritage contexts, with significant focus on copyright and accessibility implications. Her publication trends reveal consistent exploration of presence theory across physical-digital boundaries, with award-winning CHI conference papers (2009-2013) and books like 'Performing Mixed Reality' (2011) establishing frameworks for understanding mixed reality performance, environmental art, and digital heritage preservation. Her scientific recognition includes: Three consecutive CHI Best Paper Awards (2009, 2012, 2013) Theatre Library Association Book Award nomination for 'Performing Presence' (2012) Royal Society of Arts Fellowship nomination (2012) While specific advisees aren't documented, her research partnerships demonstrate extensive collaborative supervision across institutions including Tate, Imperial War Museum, British Library, and Stanford Libraries, securing projects that integrate artistic practice with scientific research. As Centre for Intermedia Director, she cultivates experimental teams investigating how digital archives transform cultural engagement through mobile platforms, particularly in environmental contexts via partnerships with Met Office Hadley Centre and Ludwig Boltzman Institute.
Sarath Chandar is an Associate Professor at Polytechnique Montréal and Core Faculty Member at Mila, the Quebec AI Institute. He holds a Canada CIFAR AI Chair and Canada Research Chair in Lifelong Machine Learning. His research focuses on developing interactive learning algorithms for continual and lifelong learning, with expertise in deep learning, reinforcement learning, and natural language processing. Education: Ph.D. in Computer Science, University of Montreal (advisor: Yoshua Bengio) M.S. in Computer Science, Indian Institute of Technology Madras (advisor: Balaraman Ravindran) Research Themes: Continual Learning and Lifelong Learning Deep Reinforcement Learning Optimization for Deep Networks Natural Language Processing AI for Scientific Discovery Notable Contributions: Founder of the Conference on Lifelong Learning Agents (CoLLAs) Developed Chandar Research Lab (CRL), focusing on adaptive learning algorithms Contributions to model-based reinforcement learning and bias mitigation in AI systems Awards & Grants: Canada CIFAR AI Chair Canada Research Chair Tier 2 MITACS-funded projects on reinforcement learning applications Lab & Collaboration: CRL collaborates with academic/industrial partners (e.g., IBM, Samsung) Hosts annual symposium showcasing research in AI, optimization, and multi-agent systems
Arya Mazumdar is a tenured Professor of Data Science and Computer Science at the Halıcıoğlu Data Science Institute (HDSI) , part of the School of Computing, Information and Data Sciences at the University of California San Diego (UCSD). He also holds affiliations with the Computer Science and Engineering and Electrical and Computer Engineering departments at UCSD. Previously, he was an Assistant and Associate Professor at the University of Massachusetts Amherst (2015–2021), and held a postdoctoral position at MIT (2011–2012). He is an IEEE Distinguished Lecturer (2023–2024) and recipient of the NSF CAREER Award (2015–2020). Education : PhD in 2011 from the University of Maryland, College Park (advisor: Alexander Barg) Postdoctoral scholar at MIT (2011–2012, advisor: Greg Wornell) Internships at IBM Almaden (2010) and HP Labs (2008) Research Interests : Focus on algorithmic and statistical aspects of machine learning, error-correcting codes, optimization, signal processing, and distributed systems. Key areas include clustering algorithms, compressed sensing, federated learning, and information-theoretic foundations of data science. He has contributed to theoretical guarantees for learning mixtures, distributed optimization, and robust coding schemes. Recent Articles Trends : Recent work emphasizes distributed optimization (e.g., vqSGD, Byzantine-resilient algorithms), sparse recovery in high-dimensional models, and theoretical foundations of learning (e.g., support recovery, parameter estimation). His research bridges information theory and machine learning, with applications in storage systems and large-scale data processing. Awards & Roles : 2020 EURASIP JASP Best Paper Award Co-PI and co-leader of the NSF AI Institute for Learning-Enabled Optimization at Scale Editorships: IEEE Transactions on Information Theory and Foundations and Trends in Communications Grants & Labs : Leads the EnCORE Institute as UCSD Site Lead, focusing on theoretical perspectives of large language models and computational-statistical gaps. Active in organizing workshops on topics like LLMs, clustering, and distributed optimization. His research is funded by NSF and industry collaborations. Teaching : Courses include Algorithms for Data Science , Probability and Statistics for Data Science , and Coding Theory , emphasizing foundational theory and scalable methods.
Viktor Prasanna is the Charles Lee Powell Chair in Engineering and Professor of Electrical and Computer Engineering and Computer Science at the University of Southern California. He holds courtesy appointments in Computer Science and leads the Center for Energy Informatics, focusing on interdisciplinary research linking energy technologies, computer science, and engineering. Education: BE in Electronics (Bangalore University), ME (Indian Institute of Science), PhD in Computer Science (Pennsylvania State University) His research spans reconfigurable computing, FPGA accelerators, parallel and distributed systems, and big data applications. He has pioneered high-performance architectures and algorithms using FPGAs, impacting domains like networking, security, HPC, and machine learning. Prasanna has published over 600 papers, received 22 best paper awards, and secured >$50M in grants. His work emphasizes energy-efficient computing, with recent grants totaling $12.9M (2016–2021). His h-index is 73, with 23,454 total citations. Scientific Awards: IEEE Fellow, ACM Fellow, AAAS Fellow, W. Wallace McDowell Award, multiple Distinguished Alumnus Awards He has advised over 70 doctoral students and led major centers including CiSoft (Big Data in oilfield tech) and CAST. His editorial roles include Editor-in-Chief of IEEE Transactions on Computers and Journal of Parallel and Distributed Computing.
Dr. Tamás Koltai is a Professor and Dean at the Faculty of Economics and Social Sciences of Budapest University of Technology and Economics (BME). He leads the doctoral school's Specialization Group in Production Management. His roles include overseeing academic programs and research in production management, operations research, and efficiency analysis. Education: Doctor of the Hungarian Academy of Sciences (2016) Dr. habil. (2000), Budapest University of Technology and Economics Candidate of Technical Sciences (1987), Hungarian Academy of Sciences M.Sc. in Mechanical Engineering (1983), BME Faculty of Mechanical Engineering Research Interests: Dr. Koltai focuses on production management optimization, including the application of Data Envelopment Analysis (DEA), sensitivity analysis in mathematical models, and the integration of robotics in assembly lines. His work bridges theoretical models (e.g., MILP/CP optimization) with practical industrial challenges, particularly in healthcare efficiency and educational management. Notable Awards: IEOM Society Teaching Excellence Award (2021) BME GTK Faculty Memorial Medal (2016) János Susánszki Award (2013) Széchenyi Professorship Scholarship (1999–) Teaching & Leadership: He has held visiting roles at the University of Seville (1990–1992) and the University of Michigan (1988/89). His teaching excellence is recognized through awards and his contributions to business simulation education. His research often collaborates with industry partners to address real-world operational challenges. Labs/Teams: Leads the Production Management Specialization Group and contributes to interdisciplinary teams focusing on manufacturing efficiency and healthcare operations within BME.
Kyprianos Papadimitriou is a Researcher at the Microprocessor and Hardware Laboratory within the School of Electrical and Computer Engineering at the Technical University of Crete . He holds a PhD in Electronic and Computer Engineering (2012) and has been involved in teaching laboratory courses such as Logic Design , Computer Architecture , and VLSI/ASIC Circuit Design . Research Areas : His work spans Reconfigurable Systems , Hardware Design , Computer Architecture , RFID Systems , and Real-Time Systems . He has developed innovative approaches in FPGA-based dynamic reconfiguration, MPSoC security, and 3D stereo vision for surveillance. Key Trends : Runtime reconfiguration for FPGAs Security frameworks for NoC-based MPSoCs Low-cost embedded vision systems Optimization of reconfiguration overhead Hardware task scheduling methodologies Genetic algorithm implementations on FPGAs Scientific Contributions : 1 USA patent (2005) Co-author of VLSI-SoC 2013 paper nominated for 1st Prize Active member of scientific committees (FPL, ReConFig) Peer reviewer for IEEE, Elsevier, and Springer journals Session chair at IEEE CNS and HPCC conferences Grants & Projects : Participated in competitive European and national programs, serving as scientific manager, coordinator, and technical coordinator. Developed spin-off company (2003-2005) to commercialize master's thesis research. Laboratory & Teaching : Affiliated with the Microprocessor and Hardware Laboratory , focusing on practical training in digital systems, processor-based systems, and VLSI design.
Daniele Caramani is a Full Professor of Comparative Politics at the University of Zurich's Faculty of Philosophy, Institute of Political Science, where he holds the Chair of Comparative Politics since 2014. He also serves as the Ernst B. Haas Chair at the European University Institute in Florence, directing the European Governance and Politics Programme at the Robert Schuman Centre for Advanced Studies (currently on leave from UZH). His teaching includes courses on Comparative Politics, Political Systems and Theories, Political Representation, and Reforming Representative Democracy. His educational background includes a baccalauréat from the Lycée International de Saint-Germain-en-Laye, followed by BA and MA degrees from the University of Geneva, and a Ph.D. from the European University Institute in Florence. He attended methods summer schools at Essex and Michigan. Caramani's research focuses on comparative and historical political science with emphasis on political cleavages, electoral geography, party systems, European integration, and globalization. His work often employs quantitative time series reaching back to the 19th century, examining mass democratization, state formation, nationalism, and industrialization. He is particularly known for analyzing the interplay between territorial and functional cleavages at national, European, and global levels. His recent publications reveal a clear trajectory from national party systems (The Nationalization of Politics, 2004) to European integration (The Europeanization of Politics, 2015) and now to global cleavages (with his ERC Advanced Grant project GLOBAL). His current work examines technocratic representation, populist challenges, and the evolution of global political alignments using automated text analysis of historical documents dating back to 1843. Stein Rokkan Prize for Comparative Social Science Research (2004) Lijphart-Przeworski-Verba Dataset Award from Comparative Politics section of the American Political Science Association (2012) Vincent Wright Memorial Prize for best article in West European Politics (2006) Caramani has directed major research projects including the ERC Advanced Grant project GLOBAL analyzing global cleavages. He has been instrumental in developing significant datasets like the Constituency-Level Elections Archive (CLEA), which received the APSA award in 2012 and now covers over 2,025 elections from 180 countries with GeoReferenced Electoral Districts. His academic leadership extends to editing the comprehensive textbook Comparative Politics (Oxford University Press, sixth edition, 2023). As Director of the European Governance and Politics Programme at the European University Institute, Caramani leads research on European integration and governance. He also co-directs the Constituency-Level Elections Archive (CLEA), a major resource for electoral studies that includes historical maps from 74 countries. His work continues Stein Rokkan's legacy in comparative social science, as evidenced by his 2023 Stein Rokkan Memorial Lecture.
Francine Battaglia is a Professor and Chair of the Department of Mechanical and Aerospace Engineering at the University at Buffalo, part of the School of Engineering and Applied Sciences. She directs the Advanced Simulations for Computing ENergy Transport (ASCENT) Laboratory. Her research focuses on computational fluid dynamics (CFD) applications in building energy systems, renewable energy, turbulent multiphase flows, and combustion. She holds a PhD in Mechanical Engineering from Pennsylvania State University (1997), and MS/BS degrees from SUNY Buffalo (1992, 1991). Research interests include CFD modeling for HVAC optimization, natural ventilation design, pathogen dispersion mitigation, and biomimetic aerodynamics inspired by insect flight. Her work bridges engineering, biology, and environmental science, addressing challenges in energy efficiency, public health, and sustainable architecture. Key contributions include developing predictive models for hydroplaning safety, solar chimney systems, and microbial fuel cells. She has received accolades such as the ASME Fellow distinction (2009), MAC Academic Leadership Fellowship (2019-2020), and Virginia Tech’s Teaching Excellence Award (2016). Her articles span CFD advancements in fluidization, combustion, and ventilation strategies, emphasizing practical applications in energy systems and public health. The ASCENT Lab collaborates on adaptive HVAC technologies and eco-friendly building designs, reflecting her dedication to interdisciplinary innovation. Awards: MAC Leadership Fellow, ASTFE Fellow, ASME Dedicated Service Award Education: PhD (Penn State), MS/BS (SUNY Buffalo) Labs: ASCENT Lab (focusing on CFD and energy transport)
Rajeev Balasubramonian is a Professor and Associate Director at the School of Computing, University of Utah. He specializes in computer architecture, with a focus on memory systems, emerging technologies, and energy-efficient computing. His research addresses challenges in DRAM/NVM architectures, security, and acceleration for big data and machine learning workloads. Education: PhD in Computer Science (University of Rochester, 2003), M.S. (University of Rochester, 2000), B.Tech in Computer Science (IIT Bombay, 1998). Research Interests: Memory reliability, near-data processing, cache hierarchies, transactional memory, and hardware-software co-design for emerging technologies. He has led projects on crossbar accelerators, secure memory systems, and resistive memory architectures. Recent Trends in Publications: Focus on encrypted inference (Hyena), data prefetching (PATHFINDER), and neuromorphic computing (SpinalFlow). His work bridges hardware and software, emphasizing practical acceleration and security solutions. Awards: IEEE Fellow (2021), Google Faculty Awards (2019/2020), Intel Research Award (2017), and multiple best paper awards (ISCA, ISPASS, PACT). Grants & Students: Over $4M in NSF/industry funding. Advised 15+ PhD students (e.g., Ali Shafiee, Karl Taht) and currently mentors researchers in resistive memory and security accelerators. His lab includes teams like Utah Arch Research Group. Labs & Teams: Leads the Utah Arch Research Group , organizing workshops on near-data processing and memory systems (e.g., ISCA, HPCA).
Professor Jonathan Murray is a Personal Chair of Film Theory, History, and Criticism at the School of Design , University of Edinburgh . As a renowned scholar in Scottish and British cinemas, he co-edits the Journal of British Cinema and Television and contributes to Cineaste . Active in film festivals as a host and curator, he has influenced both academic and public engagement with cinema. PhD and MA in Film and Television Studies and Scottish History, University of Glasgow Research Interests : Jonathan specializes in contemporary Scottish and British cinemas, focusing on cultural identity, adaptation, and espionage themes. His work bridges academic criticism with public discourse, emphasizing animation, documentary, and historical analysis. He explores intersections of film with popular music, design, and societal narratives. Article Trends : His recent publications highlight European cinematic duality, American adaptations, and Scottish cultural heritage. Themes span from Martin Scorsese’s ethical storytelling to Agnieszka Holland’s political narratives and Scottish film’s evolution from Whisky Galore! to Trainspotting . Scientific Awards : 2016 BAFTSS Best Monograph Award 2017 BAFTSS Best Journal Article Award (Shortlisted) 2018 BAFTSS Best Journal Article Award 2019 BAFTSS Best Journal Article Award Supervision : He supervises PhD students Dan Castro and Nelson Correia. His editorial leadership and festival involvement underscore his commitment to advancing film scholarship and practice.
