جست‌وجوی استاد و پژوهشگر

• Artificial Intelligence
• Machine Learning
• Computational Biology
• +۷ مورد دیگر

Dr. Antony McCabe is a Lecturer in Computer Science who divides his time between academia and the Computational Biology Facility. His work focuses on bridging artificial intelligence with biomedical challenges through software development, data analysis, and user interface design. Lecturer in Computer Science Member of Computational Biology Facility Research Interests McCabe specializes in applying AI techniques like neural networks and large language models to biomedical problems. His contributions include: Developing the lcmsWorld 3D visualization software for mass spectrometry Advancing the Allele Frequency Net Database for HLA diversity analysis Creating immunoinformatics tools for ethnicity-specific vaccine design Building infrastructure for biomedical data processing and storage Research Trends His publications reveal a consistent focus on computational biology infrastructure (4/6 papers), AI applications in immunology (3/6), and software development for proteomics (2/6). Key themes include data standardization, ethnic diversity considerations, and visualization techniques. Current Projects He is currently tuning large language models to analyze biological literature through a Biotechnology & Biological Science Research Council (BBSRC) grant (2024-2026). Teaching McCabe co-ordinates the COMP222 module on computer game design while also teaching algorithmic game theory, programming languages, and human-centric computing.

Wai Kiong Oswald Chongمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Engineering Systems
• Optimization
• +۱۰ مورد دیگر

Dr. Wai Kiong Oswald Chong is an Associate Professor at Arizona State University's School of Sustainable Engineering and the Built Environment, with a dual affiliation as Senior Global Futures Scientist at the Global Futures Scientists and Scholars program. He holds a PhD in Civil Engineering from the University of Texas-Austin, MSc and BSc in Building from the National University of Singapore, and focuses on integrating artificial intelligence with sustainable engineering systems. PhD (2005): Civil Engineering, University of Texas-Austin MSc (1999) & BSc (1997): National University of Singapore His research bridges lunar construction with Earth-bound sustainable systems, covering topics like: Space habitat modularization Resource circularity systems AI-enhanced building codes Climate-resilient infrastructure Advanced energy modeling Construction supply chain optimization Publications demonstrate consistent focus on: Semiconductor facility HVAC optimization Building energy consumption anomalies Life cycle assessment frameworks Construction risk management Deconstruction and material reuse AI-driven system modeling Current research projects include: Lunar MVI (Moon Village Initiative) Semiconductor fab design optimization Human-AI knowledge interfaces Thermal insulation systems for extreme environments Smart grid energy modeling

Arnab Nandiمشاهده پروفایل

استاد

• Database Systems
• Human-in-the-Loop Data Analytics
• Next-Generation Query Interfaces
• +۱۰ مورد دیگر

Arnab Nandi is a Professor in the Department of Computer Science & Engineering at The Ohio State University. His work bridges human interaction with data infrastructure, focusing on database systems, LLM-augmented analytics, and immersive query interfaces. Education: PhD in Computer Science & Engineering from the University of Michigan Leadership: Co-founder of OHI/O Hackathon Program and STEAM Factory interdisciplinary network Research spans human-in-the-loop data analytics , vibe querying (natural language + gestural interfaces), LLM integration into education, and climate response systems . Key projects include Omni (multimodal exploration), GestureDB , and Icarus (clinical pipelines). Recent publications analyze LLM-driven query stacks (HILDA 2025), video analytics (SIGMOD 2022), and data sunglasses for cognitive limits (HILDA 2025). Awards include NSF CAREER Google Faculty Research Award IEEE TCDE Early Career Award ACM Distinguished Member Advises students in database innovation , with alumni at Amazon, AWS, Roblox, and Meta. Teaches CSE 3241 (Database Systems), CSE 5889 (Software Startups), and CSE 5242 (Advanced Databases).

Charith Mendisمشاهده پروفایل

استادیار

• Compilers
• Programming Languages
• Machine Learning for Systems
• +۳ مورد دیگر

Charith Mendis is an Assistant Professor in the Siebel School of Computing and Data Science at the University of Illinois at Urbana-Champaign, with joint appointments in the Department of Computer Science, Electrical and Computer Engineering, and the Coordinated Science Lab. His research focuses on the intersection of compilers, program optimization, and machine learning systems. Dr. Mendis received his educational background from prestigious institutions: Ph.D. in Computer Science from Massachusetts Institute of Technology (2020) S.M. in Computer Science from Massachusetts Institute of Technology (2015) B.Sc. in Electronics and Telecommunication Engineering from University of Moratuwa (2013) His primary research interests center around compiler technology and machine learning systems. Mendis leads the ADAPT lab at UIUC, where his team works on creating high-performance ML optimization techniques and automated compiler construction using machine learning and formal methods. His work bridges the gap between traditional compiler design and modern machine learning approaches, with applications in tensor compilers, graph neural networks, and sparse computation. He has developed novel frameworks for optimizing deep learning workloads, verification of compiler transformations, and performance modeling for emerging hardware architectures. Mendis has established himself as a leading researcher in compiler optimization for machine learning systems, with a particular focus on tensor compilers, graph neural networks, and performance modeling. His recent publications demonstrate increasing sophistication in combining formal methods with machine learning techniques to solve challenging problems in compiler optimization and verification, with multiple papers accepted at top-tier conferences including OOPSLA, PLDI, POPL, and SIGMOD. His notable scientific achievements include: Google ML and Systems Junior Faculty Award (2025) DARPA Young Faculty Award (2024) NSF CAREER Award (2024) Distinguished Paper Award at POPL (2025) William A. Martin Thesis Award for Outstanding SM thesis, MIT (2015) Multiple teaching excellence awards at UIUC (2021-2023) Dr. Mendis actively mentors students through the ADAPT lab, offering research opportunities for undergraduates, master's students, and PhD candidates interested in compiler technology and machine learning systems. His research is supported by significant funding from the ACE center (part of JUMP 2.0), National Science Foundation (NSF), DARPA, IIDAI, and industry partners including Google, Intel, Amazon, and Qualcomm. He teaches advanced courses in compiler construction and machine learning for compilers. He leads the ADAPT lab at UIUC, which focuses on developing advanced compiler technologies for modern machine learning workloads. The lab maintains active collaborations with industry partners and has established itself as a leading research group in compiler optimization for AI systems. Current projects include tensor compilers, graph neural network optimization, and automated verification of deep learning systems.

Shweta Singhمشاهده پروفایل

استادیار

• Artificial Intelligence
• Responsible AI
• Explainable AI
• +۷ مورد دیگر

Dr. Shweta Singh serves as an Assistant Professor of Information Systems and Management at Warwick Business School, University of Warwick. She concurrently holds prestigious appointments as a Fellow at the Warwick Institute for Global Sustainability Development (IGSD) and a Behavioral Data Science researcher at The Alan Turing Institute in London. Her academic journey includes a Ph.D. in Information and Decision Sciences from the Carlson School of Management at the University of Minnesota, complemented by dual Master's degrees in Computer Science and Applied Economics from the same institution. Ph.D. in Information and Decision Sciences, University of Minnesota Master's in Computer Science, University of Minnesota Master's in Applied Economics, University of Minnesota Dr. Singh's research centers on developing ethical and responsible artificial intelligence systems that address societal challenges. Her work specifically targets mitigating AI bias, creating explainable AI frameworks, and leveraging technology to combat societal injustice. She investigates how digital platforms, sharing economy models, and IT outsourcing create business value while ensuring these technologies promote sustainability and reduce inequalities. Her innovative approach combines technical AI expertise with deep social awareness, particularly focusing on gender equality and child protection in digital spaces. Her publication record demonstrates consistent high-impact contributions to Information Systems Research, International Conference on Information Systems, and related venues. The trajectory of her work shows increasing focus on practical applications of responsible AI, with recent projects addressing online child safety and human trafficking prevention. Her research increasingly intersects with policy development, as evidenced by her contributions to UK Parliamentary Office of Science and Technology briefs. Doctoral Dissertation Fellowship, University of Minnesota McNamara Fellowship, University of Minnesota Social Impact Project of the Year shortlist (2023) Asian Women of Achievement Award finalist (2023) British Indian Awards finalist (2019) Top 5 Women in Tech for Good Award shortlist (2022) Inspiring 50 UK recognition (2025) Dr. Singh actively mentors students and has been recognized with the Staff Social Inclusion Award (2024) for her teaching excellence. Her advisory roles extend beyond academia to include the UN Women UK delegation for the Commission on the Status of Women and the Advisory Board of AI retail company 'Love the Sales'. She serves as an external collaborator for Boston Consulting Group's Henderson Institute, bridging academic research with industry applications. Through her leadership in the ISM-Analytics (ISMA) Group at Warwick, Dr. Singh fosters interdisciplinary collaboration focused on creating socially responsible technological solutions. Her work with the IGSD specifically targets UN sustainability goals related to reducing inequalities and promoting inclusive societies through responsible AI implementation.

Miloš Rackovićمشاهده پروفایل

استاد

• Artificial Intelligence
• Machine Learning
• Databases
• +۴ مورد دیگر

Miloš Racković serves as a full Professor in the Department of Mathematics and Informatics at the University of Novi Sad, Serbia. He maintains active academic engagement through the Laboratory for the development of information systems, with his office located in the Information technologies and systems office (DMI&DF) on the second floor, room 49. Contact is available via telephone (485)-2868 or email rackovic@dmi.uns.ac.rs, and his personal website (http://www.is.pmf.uns.ac.rs/rackovicm/) provides additional resources. His research spans foundational and applied computer science, with seminal contributions in fuzzy database systems including PFSQL query language development and prioritized fuzzy logic for relational databases and XML. He has pioneered deep learning methodologies through innovative classification techniques using negative and missing features in convolutional neural networks. Additional expertise includes high-performance computing implementations of Lattice Boltzmann methods using OpenCL, robotics (symbolic modeling and trajectory planning), and blockchain applications for Industry 4.0 production processes. His sports analytics work applies neural networks to basketball player and referee movement analysis. Analysis of his 2012-2025 publications reveals a strategic evolution toward interdisciplinary applications, particularly in industrial transformation (blockchain-enabled traceability) and sports analytics. His work consistently bridges theoretical computer science with practical implementations, demonstrating increasing focus on real-world problem solving while maintaining strong foundations in database theory and computational methods. Professor Racković leads the Laboratory for the development of information systems, which focuses on advancing information system methodologies through formal modeling extensions (including Petri net innovations) and practical implementations for uncertainty management. The laboratory's work spans from foundational research in fuzzy logic systems to applied projects in high-performance computing and blockchain integration, fostering innovation in information technology development.

• Experimental Seismology
• Seismic Tomography
• Seismic Anisotropy
• +۷ مورد دیگر

Joachim Ritter is apl. Professor of Geophysics at the Karlsruhe Institute of Technology (KIT) , Geophysical Institute (GPI). He has been with KIT since 2002, after completing his habilitation at the University of Göttingen. His research integrates experimental seismology with field experiments across Europe and Africa. Education Diplom in Geophysics, University of Karlsruhe (TH), 1985–1991 Doctorate (Dr. rer. nat.), Faculty of Physics, University of Karlsruhe, 1996 Habilitation, Faculty of Physics, University of Göttingen, 2002 Research Interests Ritter’s work spans experimental seismology , seismic tomography , seismic anisotropy , and induced seismicity . He operates mobile broadband arrays to image Earth’s interior, studies deformation in the mantle and lithosphere, and monitors volcanic regions such as the Eifel volcanic field and the East African Rift. Additional foci include wind-turbine-induced ground motion and urban seismology . Publication Trends Recent publications (2022–2025) concentrate on volcano-seismic monitoring in Germany and Greece, wind-energy seismic emissions , shear-wave splitting beneath Central Europe, and fault imaging of active tectonic zones. The breadth reflects both methodological advances and targeted regional studies. Scientific Awards 2017 Faculty Teaching Award, KIT Advising & Committees Ritter has supervised numerous master theses and PhD projects, and he leads the KArlsruhe BroadBand Array (KABBA). He has served on national and international committees including the European Seismological Commission, AlpArray Science Council, and the German Geophysical Society Board. Labs & Teams He heads the Working Group on Analysis of Wind Turbines and previously acted as Spokesperson for the KIT Competence Field "Geosphere and Risk Management". His team operates dense seismological networks across Germany and Europe.

Peter Longمشاهده پروفایل

مدرس ارشد

• Ecology
• Conservation Biology
• Remote Sensing
• +۷ مورد دیگر

Peter Long is a Senior Lecturer in Ecology and Conservation at the University of Oxford Brookes, School of Biological and Medical Sciences . His research integrates satellite remote sensing, environmental modeling, and biodiversity assessment to address ecological and conservation challenges at landscape and global scales. Key research themes include: Developing algorithms for satellite data analysis Quantifying biodiversity and ecosystem services Building web-based ecological assessment tools Studying climate-agriculture interactions Assessing deforestation drivers in Madagascar Recent publications (2023–2025) focus on regenerative agriculture carbon impacts , Madagascar deforestation policy , and climate-induced habitat changes . He specializes in GIS, high-performance computing, and stakeholder engagement for environmental monitoring. Collaborations span Guatemala , Madagascar , and Europe , with tools like LEFT (web-based ecological value estimator) and BioTIME 2.0 (biodiversity time series database).

Jing Yangمشاهده پروفایل

استاد

• Data Visualization
• Visual Analytics
• High Dimensional Data Analysis
• +۷ مورد دیگر

Jing Yang is a full Professor and Director of MS CS Program in the Computer Science Department at the University of North Carolina at Charlotte (UNCC). She has been actively involved in data visualization and visual analytics research since joining UNCC in 2005 after completing her PhD at Worcester Polytechnic Institute. Dr. Yang earned her Bachelor's degrees in Engineering Mechanics and Computer Science from TsingHua University in 1997 and completed her Ph.D. in Computer Science from Worcester Polytechnic Institute in May 2005 under advisors Matthew O. Ward and Elke A. Rundensteiner. Her research focuses on developing visual analytics techniques for abstract data including multidimensional data, time-oriented data, networks, hierarchies, text documents, and trajectory data. She conducts design studies for application domains such as sports, bioinformatics, finance, network security, and health, while exploring fundamental visualization topics like interactions, insight management, clustering-based approaches, and animations. Her recent work emphasizes sports analytics, urban data, and multivariate time series visual analytics. Analysis of Dr. Yang's publication record reveals a strong focus on practical applications of visualization techniques across diverse domains. Her work consistently bridges theoretical visualization frameworks with real-world data challenges, particularly in transportation (taxi trajectories), sports (tennis match analysis), financial transactions, and bioinformatics. The publications demonstrate an evolution from foundational visualization techniques to increasingly sophisticated domain-specific applications. Dr. Yang has secured substantial research funding from NSF, EPA, DHS, and industry partners including Google and Bank of America. Her grants portfolio includes significant projects like TrajAnalytics (NSF, $200,950), Visualizing Event Dynamics (NSF EAGER, $75,317), and Visualizing High Dimensional Categorical Datasets (Google Faculty Research Award, $60,000), among others totaling over $4 million in research support. As an educator, Dr. Yang has taught numerous courses including Visual Analytics, Information Visualization, and Database Design. She directs the Charlotte Visualization Center and has mentored numerous students through research projects. Her collaborative approach is evident in her extensive co-authorship network spanning multiple institutions and disciplines. Current research directions include narrative animation for streaming text visualization and advanced techniques for exploring high-dimensional categorical datasets.

• Photonics
• Optical Communications
• Integrated Photonics
• +۴ مورد دیگر

Stephen E. Ralph is Professor and Glen Robinson Chair in Electro-Optics within Georgia Tech's School of Electrical and Computer Engineering, serving as Director of the Georgia Electronic Design Center (GEDC) and founder of the Terabit Optical Networking Consortium. His leadership spans cross-disciplinary research in electronics, photonics, and signal processing for revolutionary system performance. Educational background includes a BEE with highest honors from Georgia Tech (1980) and PhD in Electrical Engineering from Cornell University (1988), followed by postdoctoral work at AT&T Bell Laboratories and IBM Watson Research Center. His research integrates integrated photonics , machine learning , and aerospace applications to develop ultra-high-capacity optical communication systems. Current focus areas include photonic topology optimization, radiation-hardened space systems, and converged optical/mm-wave technologies, emphasizing the synergistic development of electronic-photonic components for next-generation interconnects. Analysis of 2024-2025 publications reveals dominant themes in foundry-compatible photonic design (topology optimization, inverse design), aerospace photonics (radiation testing, analog/digital signal transport), and machine learning applications for nonlinear equalization. The work bridges fundamental device engineering (grating couplers, waveguide bends) with system-level implementations for 5G/6G networks and space communications. Key recognition includes: Fellow of the Optical Society (OSA) Professor Ralph has mentored over 20 PhD students and secured significant research funding including the IUCRC Phase I EPICA project (2021) for aerospace photonic integration. His industry partnerships through the Terabit Optical Networking Consortium drive translational research in high-speed communications. He leads the Georgia Electronic Design Center's multidisciplinary team developing photonic-electronic co-design methodologies, with recent emphasis on topology-optimized devices for commercial foundries and radiation-tolerant systems for space applications.

Geraint Jewellمشاهده پروفایل

استاد

• Electrical Machines
• Electromagnetic Modeling
• Aerospace Applications
• +۱۰ مورد دیگر

Professor Geraint Jewell is affiliated with the University of Sheffield , serving as Director of the Rolls-Royce University Technology Centre in Advanced Electrical Machines (since 2006) and Director of the EPSRC Future Electrical Machines Manufacturing Hub (since 2019). He is a graduate of the university (BEng 1988, PhD 1992) and has held academic roles since 1994. EPSRC Advanced Research Fellowship (2000-2005) Royal Society Industry Fellowship at Rolls-Royce (2006-2008) Former Faculty Director of Research and Innovation (2008-2011) Former Head of Department (2013-2019) His research focuses on power-dense electrical machines for aerospace applications , including permanent magnet machines , switched reluctance machines , and linear actuators . He has supervised ~20 PhD students and led collaborations with Rolls-Royce on high-temperature devices (up to 800°C) and aero-engine starter-generators. Recent publications analyze stator insulation thermal degradation , eddy current control in additively manufactured materials , and magnetic loss prediction in silicon steel. His work spans electromagnetic modeling , core loss calculation , and advanced manufacturing techniques for electrical machines. EPSRC Advanced Research Fellowship (2000-2005) Royal Society Industry Fellowship (2006-2008) He has advised PhD students across topics like consequent-pole PM machines , doubly salient SynRMs , and core loss characterization . His Electrical Machines and Drives Research Group explores modular motor design and magnetic material optimization for aerospace and electric vehicles.

• Metallurgical Process Engineering
• Metal Recycling
• Extractive Metallurgy
• +۷ مورد دیگر

Professor Karl Bernhard Friedrich serves as Universitätsprofessor and Chair of Metallurgical Process Engineering and Metal Recycling at RWTH Aachen University's Faculty of Georesources and Materials Engineering. He leads the Institute for Metallurgical Science and Electrometallurgy (IME), with his office located in Building 1401, Room 108 at Intzestraße 3 in Aachen. His leadership extends to numerous EU-funded research initiatives focused on sustainable metallurgy and circular economy principles. Professor Friedrich's research interests span metallurgical process engineering, metal recycling, extractive metallurgy (pyrometallurgy and hydrometallurgy), battery recycling technologies, lithium recovery processes, and vacuum metallurgy. His work emphasizes resource efficiency and sustainable practices in metal production and recycling, with particular focus on developing environmentally sound processes for electronic waste and battery recycling. The institute under his leadership has pioneered several innovative recycling concepts for lithium-ion batteries and electronic scrap. Analysis of his recent publications reveals a strong focus on battery recycling technologies, particularly lithium recovery from spent batteries through both pyrometallurgical and hydrometallurgical routes. His research group has developed advanced processes for black mass treatment, slag valorization, and metal recovery optimization. The work demonstrates increasing integration of digital technologies and multi-objective modeling in metallurgical process development. Honorary doctorate from Montanuniversität Leoben (2025) recognizing outstanding scientific achievements and commitment to promoting young scientists Long-standing collaboration with Montanuniversität Leoben through the Aachen-Leoben Workshop for non-ferrous metallurgists Professor Friedrich actively supervises numerous doctoral students and has established several collaborative research programs including the DFG priority program 'engineered artificial minerals,' and doctoral programs 'circular electronics' and 'circular e-cars.' His institute maintains strong industry connections, with growing demand for TBRC and VAR trial campaigns. The institute recently commissioned a new large-scale arc furnace and is preparing for leadership transition in early 2027. The IME under Professor Friedrich's leadership operates extensive research facilities focused on vacuum metallurgy, pyrometallurgy, and hydrometallurgy. The institute collaborates with industry partners through the GDMB Zinc & Lead Technical Committee and participates in numerous European research networks. Current research activities focus on developing sustainable processes for battery recycling, electronic waste treatment, and critical metal recovery with emphasis on circular economy principles.

Rana Adhikariمشاهده پروفایل

استاد

• Gravitational Waves
• Dark Matter Detection
• Quantum Metrology
• +۶ مورد دیگر

Rana Adhikari is a Professor of Physics at the California Institute of Technology (Caltech). Holding a B.S. from the University of Florida (1998) and a Ph.D. from MIT (2004), he has been at Caltech since 2006, progressing from Assistant Professor to full Professor in 2012. His research focuses on advancing detector technologies for fundamental physics experiments in gravitational waves, dark matter, and near-field gravity studies. Education: B.S. in Physics, University of Florida (1998); Ph.D. in Physics, MIT (2004) Caltech Faculty: Assistant Professor (2006-12), Professor (2012-present) Adhikari's group specializes in precision measurements at the intersection of classical and quantum physics. Key research areas include: Mechanical oscillators and their thermodynamic limits Nonlinear optics for interferometric applications Quantum information constraints in classical sensors Adaptive optics using thermal actuation Cryogenic silicon interferometers for cosmological observations High-quality silicon opto-mechanical systems for LIGO applications Laser gyroscope technology for rotation sensing The group's work on gravitational wave detection has produced numerous publications in leading journals like Physical Review X , Physical Review D , and Optics Express . Their research often combines experimental physics with machine learning techniques for noise cancellation in laser interferometers. Adhikari's team also engages with undergraduate researchers through programs like the International LIGO SURF students, creating opportunities for young scientists in gravitational physics. His publications reveal a consistent focus on gravitational wave detector optimization, quantum metrology, and cosmological observations through advanced instrumentation.

Dimitris Papanikolaouمشاهده پروفایل

استاد

• Asset Pricing
• Macroeconomics
• Innovation
• +۲ مورد دیگر

Dimitris Papanikolaou serves as the John L. & Helen Kellogg Professor of Finance at Northwestern University's Kellogg School of Management and is a Research Associate of the National Bureau of Economic Research (NBER). His research critically examines the nexus between technological innovation and financial markets, with recent contributions spanning intangible capital measurement, innovation's impact on labor dynamics, executive markets, and financial frictions. Education: PhD in Financial Economics, Massachusetts Institute of Technology (2007) MS in Finance and Economics, London School of Economics (2001) BA in Economics and Finance, University of Piraeus (2000) Papanikolaou's research program centers on Asset Pricing , Macroeconomics , Innovation , Economic Growth , and Intangible Capital . He pioneers methodologies for quantifying innovation through textual analysis of patents while investigating how technological advances reshape financial markets and labor outcomes. His work reveals critical insights into human capital displacement, the economic value of intangibles, and the causal mechanisms linking financial constraints to innovation efficiency, employing rigorous empirical designs including natural experiments and administrative datasets. Analysis of his recent publications shows a pronounced interdisciplinary trajectory, merging finance, labor economics, and innovation studies through cutting-edge techniques like NLP and big data analytics. Key thematic clusters include AI's labor market effects (examining task exposure and wage dynamics), creative destruction measurement (using text-based innovation displacement metrics), and intangible capital's macroeconomic role (exploring firm scope, concentration, and growth implications). These works consistently establish causal relationships through exogenous variation in innovation shocks and patent data. Scientific recognition includes: Kellogg Research Mentorship Award Best Paper Award, London Business School Finance Symposium (2018) Best Paper Award, Red Rock Finance Conference (2017) Crowell Memorial Prize (second place), Panagora Asset Management Amundi Smith Breeden Prize, American Finance Association (2014 and 2013) Roger F. Murray Prize (second place), The Q Group (2011) As Co-Editor of the Journal of Financial Economics and former editorial board member for Management Science, the Journal of Finance, and the Review of Financial Studies, Papanikolaou shapes scholarly discourse in finance. His mentorship excellence—recognized by the Kellogg Research Mentorship Award—demonstrates commitment to developing next-generation scholars, though specific grant details remain undisclosed in available materials. Collaborative research networks with leading economists like Kogan, Schmidt, and Eisfeldt drive his high-impact publications. Papanikolaou's research ecosystem involves extensive collaboration with interdisciplinary teams leveraging computational methods for innovation measurement. Current projects focus on AI-labor market interactions and intangible capital dynamics, often utilizing proprietary patent datasets and administrative worker records to generate policy-relevant insights about technological disruption and market efficiency.

David Atienzaمشاهده پروفایل

استاد

• Embedded Systems
• Low-Power Computing
• Edge AI
• +۳ مورد دیگر

David Atienza is a Professor in the Department of Electrical Engineering at the School of Engineering, Swiss Federal Institute of Technology in Lausanne (EPFL), renowned for pioneering embedded systems education and research in ultra-low power computing. His innovative teaching methods, including using Nintendo DS consoles and smartphones to teach embedded systems, earned him the 2015 EPFL Teaching Award in Electrical Engineering. His research focuses on Embedded Systems , Edge AI , and Wearable Healthcare , with breakthroughs in energy-efficient hardware-software co-design for biomedical applications. Key contributions include open-source platforms like X-HEEP and HEEPocrates for ultra-low power edge computing, and frameworks like SzCORE for seizure detection benchmarking. His work bridges computer architecture with real-world healthcare challenges, emphasizing privacy-preserving algorithms and sustainable computing. Recent publications (2023-2025) reveal a dominant trend toward biomedical edge AI and sustainable computing , with 70% of articles targeting healthcare wearables (seizure detection, cough monitoring) and 30% addressing energy efficiency in data centers and edge devices. His research consistently integrates open-hardware principles (RISC-V) with novel algorithm-hardware co-design. Awards include: 2015 EPFL Teaching Award in Electrical Engineering section While specific advising details are unreported, his extensive publication record and leadership in multi-partner projects like Sustainable Textile Electronics (STELEC) indicate active graduate supervision and significant research funding. His group develops open-source hardware frameworks used globally in academia and industry. He leads the Embedded Systems Laboratory at EPFL, driving projects in ultra-low power RISC-V architectures, biomedical wearables, and sustainable computing. Current initiatives include carbon-aware data center frameworks and multi-modal health monitoring systems deployable on commercial wearables.