Antonio González is a full Professor at the Barcelona School of Informatics (FIB), Universitat Politècnica de Catalunya (UPC), where he is affiliated with the Department of Computer Architecture. He leads the Microarchitecture and Compilers (ARCO) research group, focusing on robust and energy-efficient computing systems, including general-purpose processors, GPUs, and cognitive computing architectures. His research spans computer architecture, microarchitecture, compilers, GPU design, and deep learning acceleration, with a strong emphasis on energy efficiency and memory optimization. His work integrates hardware and compiler techniques to enhance performance in modern computing systems. The recent publications highlight a strong trend in energy-efficient DNN acceleration, GPU microarchitecture, memory systems, and near-data processing. His team explores novel quantization methods, adaptive caching, and architectural extensions for vision and AI workloads, published in top-tier venues such as MICRO, ISCA, and IEEE/ACM journals. ACM Fellow (2020) ICREA Academia Award (2014, 2019, 2024) UPC Duran Farell Award (2008) HiPEAC 2024 Paper Award (twice) González has supervised several PhD students and leads competitive R&D+i projects, including those funded by ICREA and the European Research Council. His research group collaborates extensively within UPC and with international institutions. He is actively involved in advancing computer architecture through innovation in simulation, hardware design, and AI acceleration. He is a member of IEEE and ACM, and his work continues to influence both academic and industrial developments in high-performance and energy-efficient computing.
Professor Tulika Mitra is the Dean of the School of Computing and Vice Provost (Special Projects) at the National University of Singapore (NUS). She holds the Provost’s Chair Professor in the Department of Computer Science and has been instrumental in shaping academic policies and strategic initiatives at NUS since joining in 2001. PhD in Computer Science, Stony Brook University (2000) M.E. in Computer Science, Indian Institute of Science (1997) B.E. in Computer Science, Jadavpur University (1995) Her research focuses on hardware-software co-design for energy-efficient computing systems, particularly in real-time embedded systems, heterogeneous architectures, and AI accelerators. She leads major research programs such as the NRF Competitive Research Programme on Low-Power Edge Accelerators and the MOE Tier-3 Programme on Green AI , collaborating with industry leaders like ARM, AMD, and Meta. Her recent publications highlight innovations in CGRA optimization , sparse attention mechanisms , photonic-digital hybrid architectures , and low-power ML inference . These works often integrate compiler techniques, architectural design, and real-time constraints for edge computing applications. Scientific Awards : ESWEEK Test-of-Time Award (2022), ACM SIGDA Distinguished Service Award, IEEE CEDA Outstanding Service Recognition Award, Teaching Excellence Award (2006), and multiple best paper recognitions. Education Leadership : Spearheaded the Computer Engineering (CEG) Programme at NUS, a joint initiative between Engineering and Computing. As a mentor , she has supervised over 25 PhD students , many now in prominent academic or industrial roles. Her research group eCO Lab focuses on embedded computing challenges, while her grant collaborations include projects on 5G base stations, reconfigurable architectures, and IoT-optimized SoCs.
Dr Bahareh Zaghari (MSc, PhD, CEng, FHEA) is a Lecturer in the Electrical Power Engineering group at the University of Southampton's School of Electronics and Computer Science. Her research focuses on electrified aircraft systems, sensors with machine learning applications, electrical power systems, and nonlinear dynamics modeling. Current projects include acoustic sensing for temperature/flow measurement Co-design of electrical machines for aircraft electrification Research activities span hybrid-electric aircraft design (FutPrint50 Horizon project), fully electric aircraft development (EnabEl Innovate UK), and smart sensing systems for aerospace components. Industrial collaborations include KISTLER, iNetic, PALL Aerospace, Safran, ARUP, Embraer, and BAE Systems. Conference coordinator for IEEE Transportation Electrification Council's Electrified Aircraft committee Chair of IEEE/AIAA Electrified Aircraft Technology Symposium (2023) Panel moderator at AIAA Propulsion and Energy (2021) Her work demonstrates innovative applications of acoustic transducers in harsh environments, with contributions to temperature mapping, fault analysis, and energy harvesting systems. She currently supervises PhD student Shikhar Singh.
Ashwani K. Gupta is a Distinguished University Professor at the University of Maryland, holding the Minta Martin Professorship in Engineering. He serves as Professor in the Department of Mechanical Engineering, Professor at the Institute of Physical Science and Technology, and Affiliate Professor in the Department of Aerospace Engineering. With over 45 years of experience in combustion engineering since graduating from Southampton University in 1970, Gupta has established himself as a leading authority in advanced combustion technologies. Dr. Gupta earned his Ph.D. from the University of Sheffield in 1973, followed by a D.Sc. from the same institution in 1986 and another D.Sc. from Southampton University in 2013. His academic journey includes six years at MIT as a research staff member and three years at Sheffield University as an independent research worker before joining the University of Maryland in 1983. Gupta's research focuses on revolutionizing combustion technology through innovations in swirl flows, high-temperature air combustion (HiTAC), and distributed combustion systems. His pioneering work on 'colorless distributed combustion' has enabled ultra-low emission combustion processes with significant applications in gas turbine engines and waste-to-energy conversion. His research spans biofuels, CO2 utilization, sulfur chemistry, waste conversion, and advanced laser diagnostics, addressing critical challenges in sustainable energy and environmental protection. Analyzing his recent publications reveals a strong emphasis on waste-to-energy conversion, biomass processing, and CO2-assisted technologies. Gupta's work demonstrates a clear trajectory toward sustainable energy solutions, with increasing integration of artificial intelligence for combustion optimization and emission control. His research bridges fundamental combustion science with practical engineering applications for cleaner energy systems. Among Gupta's numerous accolades are: Election to Fellowship of the Royal Academy of Engineering (2023) Honorary Fellowship of the Royal Aeronautical Society (2020) Recognition as one of the top 2% of scientists worldwide by Stanford University (2022-2024) Multiple prestigious medals from ASME and AIAA including the Soichiro Honda Medal (2018) and AIAA Air Breathing Propulsion Award (2014) Honorary doctorates from three international universities Gupta has secured substantial research funding throughout his career, resulting in over 850 technical papers, three books, 18 edited books, and 22 book chapters. He has delivered over 100 plenary/keynote/invited presentations at international conferences. His mentorship has shaped numerous graduate students who continue to contribute to the field of combustion engineering. Gupta directs the Combustion Laboratory at the University of Maryland, which serves as a hub for cutting-edge research in sustainable combustion technologies. The Combustion Laboratory, under Gupta's leadership, has become a center of excellence for advanced combustion research, particularly in distributed combustion systems, waste-to-energy conversion, and alternative fuels. The lab maintains strong collaborations with industry partners and international research institutions, facilitating technology transfer and practical implementation of research findings. Gupta's team employs state-of-the-art diagnostics and computational tools to advance fundamental understanding while developing practical engineering solutions for cleaner energy systems.
Martin Willis Monroe is an Assistant Professor in the Department of Classics and Ancient History at the University of New Brunswick. His research focuses on the ancient Middle East, particularly cuneiform cultures, with an emphasis on the history of scholarly knowledge in Babylonian and Assyrian societies. He specializes in Mesopotamian astronomy and astrology, as well as quantitative approaches to historical data. Dr. Monroe holds a PhD in Assyriology from Brown University (2016), an MPhil and BA in Ancient Near Eastern Studies from the School of Oriental and African Studies (2008, 2007). Previously, he served as a postdoctoral fellow and research associate at the University of British Columbia (2016–2023). His current projects include the publication of his Hellenistic astrology research under contract with Brill, titled Celestial Schemata: A Series of Astrological Tables from Seleucid Babylonia , and his role as associate director of the Database of Religious History , a global initiative to quantitatively analyze religious and cultural data. He has contributed to excavations at the Neo-Assyrian site of Tušhan in southeastern Turkey and advocates for responsible qualitative-to-quantitative data conversion in historical scholarship. Dr. Monroe’s research bridges traditional philological approaches with digital humanities, focusing on topics such as cuneiform astral diagrams, the intersection of ‘scientific’ and ‘religious’ texts in antiquity, and the application of computational methods to undeciphered scripts. He teaches courses on ancient civilizations, Near Eastern history, and archaeology.
Nam Sung Kim is the W. J. "Jerry" Sanders III-Advanced Micro Devices Inc. Endowed Chair and holds a Professorship in Electrical and Computer Engineering at the University of Illinois. He is also affiliated with the Siebel School of Computing and Data Science, Coordinated Science Lab, and National Center for Supercomputing Applications (NCSA). His research focuses on computer architecture, memory systems, chiplet integration, and hardware security. Key areas include energy-efficient computing, processing-in-memory (PIM), and mitigating hardware vulnerabilities like rowhammer attacks. Kim has received prestigious awards including IEEE Fellow (2016), MICRO Hall of Fame (2018), NAI Fellow (2023), and NSF CAREER Award (2015). His work spans publications in top venues like ASPLOS and IEEE journals, addressing topics such as CXL-based memory systems, DRAM module optimization, and GPU architecture improvements. Collaborations emphasize interdisciplinary research in hardware-software co-design and emerging technologies. His labs and teams at Coordinated Science Lab and NCSA drive innovations in scalable computing, near-memory processing, and cloud infrastructure for AI workloads. Ongoing projects include developing resilient memory hierarchies and accelerating large-scale machine learning models through novel architecture designs.
Hailong Jiao is an Assistant Professor in the Department of Electrical Engineering at Eindhoven University of Technology (TU/e) and an Associate Professor at Peking University Shenzhen Graduate School's School of Electronic and Computer Engineering. He is also a Visiting Assistant Professor with TU/e's Electronic Systems group. His research focuses on low-power and variations-resilient VLSI circuit and system design , including error-resilient systems, approximate computing, machine learning in VLSI, ultra-low voltage circuits, and emerging devices like 3D integration and carbon electronics. Education : BSc (highest honor, 2004, Shandong University), MSc (2008, Institute of Microelectronics, Chinese Academy of Sciences), PhD (2012, HKUST). Collaborations : BrainWave project (TU/e and Radboud University Nijmegen) developing wearable brainwave processing for epilepsy/Parkinson's healthcare. Editorial Roles : Associate Editor for Elsevier Microelectronics Journal and World Scientific Journal of Circuits, Systems, and Computers. Committee Memberships : HiPEAC, MemoCiS, ACM/SIGDA, and six IEEE committees. Research Trends : Recent articles emphasize energy-efficient IoT networks , voltage stacking , sensitivity control , and scan flip-flop design , aligning with UN SDGs for energy engineering and healthcare innovation. Scientific awards include highest honor at BSc .
Dr. Daniel Roxbury is an Associate Professor and Graduate Director at the Department of Chemical, Biomolecular and Materials Engineering within the University of Rhode Island's College of Engineering. With expertise in nanoscience and carbon nanomaterials, his research focuses on nano-bio interactions, developing functionalized nanotubes for biomedical applications and environmental monitoring through his NanoBio Engineering Laboratory. His work spans multiple disciplines including: Biomedical nanosensors Smart wearable biomaterials Targeted drug delivery systems Environmental nanotechnology Single-molecule imaging Nanotoxicology Recent publications emphasize machine learning-enhanced spectral analysis, coral reef conservation nanotechnology, and wearable stress monitoring textiles. His 2024 ACS Nano study introduces AI-driven macrophage phenotyping, while 2023 Nature Nanotechnology work explores coral reef restoration strategies using nanomaterials. Awarded the 2019 NSF CAREER grant for cellular nanometrology, he leads multiple NIH-funded projects including: $820,000 NSF CAREER: Spectral Imaging for Sub-Cellular Nanometrology $140,000 Miriam Hospital COBRE: Cortisol Detection Textiles $700,000 NSF EAGER: Multiplexed Wound Biomarker Detection His laboratory houses state-of-the-art equipment including: Near Infrared Hyperspectral Microscope Custom NIR Fluorescence Spectrometer Jasco UV/VIS/NIR Spectrophotometer Biosafety Cabinet Cell Culture Incubator Cryo-Storage System
Oliver S. Cossairt is an Adjunct Associate Professor at Northwestern University's departments of Computer Science and Electrical and Computer Engineering. He leads the Computational Photography Lab , focusing on computational imaging, optics, and display technologies. His work bridges computer vision, graphics, and optical engineering to design novel imaging systems with applications in medical, astronomical, and scientific domains. Education: Ph.D. Computer Science, Columbia University (2011) M.S. Media Arts and Sciences, MIT Media Lab (2003) B.S. Physics, Evergreen State College (2003) Research Interests: Cossairt develops imaging systems that combine optical innovations with computational methods to enhance performance and functionality. Key areas include computational displays, depth sensing, and high-precision 3D imaging. His work emphasizes practical applications like medical imaging, holography, and non-line-of-sight sensing. Awards: NSF CAREER Award (2015–2020) Best Paper Award at ICCP 2011 NSF Graduate Research Fellowship (2008–2011) Teaching & Funding: Taught courses on computational photography and computer vision. Secured grants from NSF, NIH, and industry partners (e.g., Samsung, Omron) for projects like Coherent Computational Imaging and Snapshot 3D Holographic Microscope . Labs & Teams: Directs the Computational Photography Lab, collaborating with institutions like Argonne National Labs and museums for projects in cultural heritage imaging.
Mithuna S. Thottethodi is a Professor and Interim Associate Head of Teaching and Learning at the Elmore Family School of Electrical and Computer Engineering at Purdue University. He holds a B.Tech. from the Indian Institute of Technology, Kharagpur (1996), and a Ph.D. in Computer Science from Duke University (2002). His research focuses on computer architecture, interconnection networks, distributed systems, and security, with notable work on sparse tensor accelerators and processing-near-memory architectures. His work has been funded by the NSF, AT&T, and SK Hynix. Research interests include security, interconnection networks in multicores, storage performance optimization, and memory hierarchies. Notable contributions span hardware accelerators for machine learning, secure speculative execution, and datacenter network congestion control. He has advised over 20 graduate students, many of whom have joined top tech firms like Google, Microsoft, and Intel. Awards: NSF CAREER Award (2007) Wilfred Hesselberth Teaching Excellence Award (2021) Multiple Eta Kappa Nu Outstanding Professor Awards Teaching includes undergraduate courses like EE 437 (Computer Design) and graduate courses such as ECE 666 (Advanced Computer Architecture). He also advises VIP and EPICS student teams.
Professor Nicole Metje is a Professor of Infrastructure Monitoring at the Department of Civil Engineering, University of Birmingham, and Director of the National Buried Infrastructure Facility. She also serves as Co-director of the Institute of Quantum Technology. Her research focuses on quantum sensing, geotechnical engineering, and infrastructure monitoring, with a particular emphasis on buried infrastructure detection and sustainable urban development. Education: PhD in Civil Engineering (University of Birmingham, 2001); Dipl.-Ing. in Civil Engineering (Hannover University, Germany, 1998). Key roles and affiliations include membership in EPSRC Infrastructure Strategic Advisory Team, Chartered Institution of Civil Engineering Surveyors, and international advisory boards for Hong Kong Polytechnic University. She has authored/co-authored over 50 journal papers and a textbook on tunnel construction. Research areas include quantum sensor applications for buried asset detection, geophysical soil properties, and sensor development for infrastructure monitoring. She leads projects such as UKCRIC National Buried Infrastructure Facility and Quantum Technology Hub in Sensors and Metrology. Awards and fellowships include FICE, FCInstCES, CEng, FHEA, and multiple committee memberships in national/international bodies. Teaching includes MSc courses on underground construction and geotechnical engineering. She supervises doctoral research on quantum sensors, soil-structure interactions, and sustainable infrastructure.
Hakwan Lau is a tenured Professor of Psychology at the University of California, Los Angeles (UCLA), where he is also a member of the Brain Research Institute. Additionally, he serves as Co-Director of the IBS Center for Neuroscience Imaging Research in South Korea, leading the Systems and Intervention Neuroscience (SIN) group. His work spans consciousness, metacognition, and perceptual reality monitoring, employing advanced neuroimaging and computational techniques. Education: Born and raised in Hong Kong, Hakwan Lau pursued graduate studies in England. He was previously an Associate Professor at Columbia University in New York before moving to UCLA, where he is now tenured. From 2017-2020, he was primarily based at the University of Hong Kong. Research Interests: Lau's lab investigates why we have subjective experiences , focusing on visual awareness, spatial attention, and metacognition. They use fMRI, decoded neurofeedback (DecNef), psychophysics, and computational modeling to explore how conscious perception arises and its clinical applications, such as treating phobias and PTSD. Research Trends: His recent work emphasizes decoded neurofeedback interventions for clinical conditions like phobias and PTSD, metacognitive mechanisms underlying confidence judgments, and neural correlates of subjective experience . The research bridges theoretical neuroscience with practical therapeutic applications, often using innovative techniques like closed-loop fMRI. Scientific Awards: While specific awards are not listed in the provided text, Lau has mentored 15 former trainees who are now independent PIs , reflecting his significant impact on the field. Advising and Grants: Lau actively advises numerous PhD students and postdocs across UCLA, the University of Hong Kong, and collaborative institutions. His lab supports projects ranging from AI-driven fMRI analysis to clinical neurofeedback trials . Labs and Teams: Lau leads the Metacognition and Consciousness Lab at UCLA, now relocated to the RIKEN Center for Brain Science near Tokyo. His team includes researchers from diverse backgrounds, focusing on interdisciplinary approaches to consciousness and metacognition.
Dr. Jing Li is an Associate Professor and Eduardo D. Glandt Faculty Fellow at the University of Pennsylvania , holding dual appointments in the Electrical and Systems Engineering and Computer and Information Science departments. As co-director of the CyberSavvy nationwide security research center and director of the Penn Computational Intelligence Lab (PennCIL) , she pioneers innovations in non-von Neumann computing paradigms. Her research spans post-CMOS technologies, in-memory computing, and hardware-software co-design for security and AI applications. PhD in Computer Engineering, Purdue University (2009) BSc in Electrical Engineering, Shanghai Jiaotong University (2004) Research Focus: Dr. Li's work addresses fundamental challenges in computer systems across the stack. Key areas include: In-Memory Computing: Liquid Silicon architecture combining RRAM with silicon CMOS through monolithic 3D integration Security Engineering: Transforming computer security from "Art" to formal "Engineering" discipline within CyberSavvy Virtualization: Cloud FPGA abstraction layers decoupling compilation from runtime resource management Graph Analytics: Degree-aware optimization techniques for massive-scale graph processing Deep Learning Systems: Roofline model extensions for FPGA-based CNN acceleration Scientific Impact: Awarded DARPA Young Faculty Award , NSF CAREER Award , and IBM CEO Milestone Award , her team has achieved world records in energy-efficient computing (ENIAD supercomputer). With 46 U.S. patents and over 80 publications, she leads ecosystem development for emerging computing architectures through initiatives like the open-source MEG simulation platform . Community Leadership: Dr. Li serves on program committees for flagship conferences ( ISCA , FPGA Symposium ), chairs the International Memory Workshop , and contributes to the MLsys conference's inaugural committee. She actively mentors through multiple PhD openings and industry collaborations.
Jason Cong is the Volgenau Chair for Engineering Excellence and Distinguished Chancellor's Professor in the Computer Science Department at UCLA's Samueli School of Engineering. He directs the Center for Domain-Specific Computing (CDSC) and the VLSI Architecture, Synthesis, and Technology (VAST) Laboratory, and serves as Associate Vice Provost for Internationalization and Co-Director of UCLA/PKU Student and Scholar Program. Dr. Cong's research spans electronic design automation, customizable computing for machine learning and big-data applications, quantum computing, and highly scalable algorithms. His work has produced over 500 publications with more than 41,000 citations and an H-index of 106. His recent work focuses on quantum computing compilation, domain-specific acceleration for AI workloads, and high-level synthesis optimization techniques that leverage machine learning. His publication trend shows a strong emphasis on quantum computing and machine learning acceleration in recent years, with numerous papers on quantum layout synthesis, LLM acceleration, and high-performance FPGA implementations. His team has developed frameworks like TAPA for task-parallel dataflow programming and RapidStream for automated parallel implementation of FPGA designs. Member of National Academy of Engineering (2017) IEEE Robert N. Noyce Medal recipient (2022) Phil Kaufman Award recipient (2024) ACM Chuck Thacker Breakthrough Award recipient (2024) 18 Best Paper Awards across major conferences Multiple 10-Year Retrospective Most Influential Paper Awards Dr. Cong has graduated 50 PhD students, many of whom are now faculty at major research universities or hold key positions at leading tech companies. He has led over 100 research projects funded by DARPA, NSF, SRC, and industry sponsors. His entrepreneurial activities include founding three successful companies (Aplus Design Technologies, AutoESL, and Falcon Computing Solutions), all acquired by major EDA players. His VAST Laboratory continues to push boundaries in domain-specific computing, with active research in quantum computing, AI acceleration, and high-performance FPGA implementations.
Professor Eero Vaara, currently at Saïd Business School, University of Oxford, is a globally recognized expert in organizational theory, strategic change, and institutional dynamics. With 39 publications in Financial Times top 50 journals between 2008-2022, his work explores historical perspectives, discursive processes, and paradoxes in organizational transformations. Affiliation: Saïd Business School, University of Oxford Research Focus: Strategic change, institutional work, narrative theory, and historical embeddedness Eero’s research bridges macro-institutional and micro-practice approaches, emphasizing how unmaterialized decisions, discursive struggles, and temporal dynamics shape organizational trajectories. His work spans multinational corporations, public sector governance, and extreme contexts, with a growing interest in historical analysis and critical discourse studies. His recent publications highlight themes such as strategy-as-practice , national identity , and temporal intentionality . Articles like Near-histories and strategy emergence and Discursive legitimation demonstrate his interdisciplinary approach combining institutional theory, paradox theory, and narrative analysis. Scientific Awards: Academy of Management fellowship Ranked 11th most published management scholar in FT top 50 journals (2008-2022) Eero’s collaborative research style and resilience in the publication process have led to influential contributions in strategic management and organizational studies. His colleague Eric Zhao notes that his work “opens up new ways of thinking about organizations, strategy, and change,” reflecting Oxford Saïd’s commitment to research excellence.
