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Esther DufloView profile

Professor

• Development Economics
• Poverty Alleviation
• Health
• +7 more

Esther Duflo is the Abdul Latif Jameel Professor of Poverty Alleviation and Development Economics in the Department of Economics at the Massachusetts Institute of Technology (MIT). She is also co-founder and co-director of the Abdul Latif Jameel Poverty Action Lab (J-PAL), holds the Chaire, Pauvreté et politiques publiques at the Collège de France, and serves as President of the Paris School of Economics. Her research focuses on understanding the economic lives of people living in poverty to help design and evaluate social policies. Her work spans multiple domains including: Development Economics Poverty Alleviation strategies Health interventions Educational programs Financial inclusion initiatives Environmental policy Governance improvements Duflo revolutionized developmental economics by pioneering the use of randomized controlled trials to test poverty reduction measures. Her empirical approach has challenged conventional opinions about development and has helped improve the efficient use of resources in poverty alleviation programs worldwide. She co-authored the influential books "Poor Economics" and "Good Economics for Hard Times" with Abhijit Banerjee, demonstrating through field experiments how specific interventions (like providing lentils to mothers for child immunization) can dramatically improve social outcomes. Her notable scientific achievements include: Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel (2019) Princess of Asturias Award for Social Sciences (2015) Infosys Prize (2014) John Bates Clark Medal (2010) MacArthur "Genius Grant" Fellowship (2009) A.SK Social Science Award (2015) Duflo has established J-PAL as a global network of over a hundred affiliated professors who use scientific evidence to inform policy decisions in the fight against poverty. J-PAL has offices across Africa, Europe, Latin America and the Caribbean, North America, and South and Southeast Asia. Her work has demonstrated the crucial importance of information in policymaking, with numerous field experiments showing how carefully designed interventions can have significant impacts on social outcomes across multiple domains including health, education, and economic opportunity.

Nate FosterView profile

Professor

• Programming Languages
• Networking
• Databases
• +5 more

Nate Foster is a Professor of Computer Science at Cornell University and currently serves as the Associate Dean for Research in the Ann S. Bowers College of Computing and Information Science. He is also a Visiting Researcher at Jane Street and served as a Visiting Professor at École Polytechnique Fédérale de Lausanne during the 2023-24 academic year. His research uses ideas from programming languages to solve problems in networking, databases, and security. BA in Computer Science, Williams College (2001) MPhil in History and Philosophy of Science, University of Cambridge (2008, all work completed in 2003) PhD in Computer and Information Science, University of Pennsylvania (2009) Foster's research focuses on developing languages and tools that make it easy for programmers to build secure and reliable systems. His current work centers on the design and implementation of languages and tools for programmable networks, particularly using the P4 language. His past work includes bidirectional languages (also known as 'lenses'), database query languages, data provenance, type systems, mechanized proof, and formal semantics. His research group at Cornell has made significant contributions to network verification, software-defined networking, and formal foundations for programmable data planes. Analysis of Foster's recent publications reveals a strong focus on network verification and programming language foundations for networking. His work consistently applies formal methods to practical networking problems, with a particular emphasis on the NetKAT and P4 languages. Over the past five years, his research has evolved toward more complex network verification techniques, including infinite state verification, active learning of network models, and dependently-typed approaches to network programming. His work bridges theoretical computer science with practical networking systems, making formal methods accessible to network engineers. ACM Fellow (2025) ACM SIGPLAN Robin Milner Award (2023) ACM SIGCOMM Rising Star Award (2018) NSF CAREER Award (2013) Alfred P. Sloan Fellowship (2012) Multiple distinguished paper awards across top conferences including POPL, PLDI, and SIGCOMM Foster has advised numerous PhD and Master's students who have gone on to prominent positions in both industry and academia, with many continuing work in programming languages and networking. He has led multiple significant research grants including an NSF CAREER Award and has been involved in the P4 Language Consortium, serving as Chair of the P4 Language Governing Board. His work has been supported by various organizations including NSF, DARPA, and industry partners like Intel and Jane Street. Foster is also active in the programming languages research community, serving on numerous program committees and as Vice Chair of DARPA's Information Science and Technology (ISAT) study group. Foster leads a vibrant research group at Cornell focused on programming languages for networks, with collaborators from academia and industry. His group has developed several influential tools and frameworks including NetKAT, Petr4, and KATch. They maintain strong connections with the P4 community and work closely with industry partners to ensure their research has practical impact on real-world networking systems.

• Materials Science
• Energy Storage
• Battery Technology
• +3 more

Jun Liu is a distinguished scientist and academic, serving as a Battelle Fellow at Pacific Northwest National Laboratory (PNNL) and holding the position of Campbell Chair Professor at the University of Washington. His career spans over three decades in materials science and energy storage research, with significant leadership roles including Director of the Battery500 Consortium, a major DOE initiative focused on developing next-generation battery technologies. Dr. Liu earned his Bachelor's degree in Chemical Engineering from Hunan University, followed by a Master's degree in Ceramic Engineering and a Ph.D. in Materials Science and Engineering, both from the University of Washington. His educational background provided the foundation for his extensive career in advanced materials development. Dr. Liu's research focuses on the development, synthesis, and characterization of new materials for energy applications, with particular emphasis on battery technologies. His work spans lithium-ion batteries, lithium-sulfur systems, redox flow batteries, and magnesium-based energy storage solutions. He has pioneered approaches to improve energy density, cycle life, and safety of battery systems through innovative materials design and interface engineering. Analysis of Dr. Liu's recent publications reveals a strong focus on practical battery applications, with particular attention to lithium metal anodes, solid electrolyte interphases, and high-energy battery systems. His research increasingly addresses the challenges of translating laboratory discoveries into commercially viable battery technologies, with growing emphasis on pouch cell development and real-world performance metrics. Distinguished Inventor of Battelle (2007) PNNL's Inventor of the Year (2012, 2016) Electrochemical Society Battery Division Technology Award DOE EERE Exceptional Achievement Award PNNL Lifetime Achievement Award Fellow of the American Association for the Advancement of Science Fellow of the Materials Research Society Member of the Washington State Academy of Science Dr. Liu has secured substantial research funding through his leadership of the Battery500 Consortium and other DOE initiatives. He has mentored numerous researchers and students throughout his career, contributing to the development of the next generation of energy storage scientists. His research group at PNNL collaborates extensively with academic institutions, national laboratories, and industry partners to advance battery technology. Dr. Liu leads the Battery500 Consortium, a major collaborative effort involving multiple national laboratories, universities, and industry partners focused on developing lithium-metal batteries with significantly higher energy density than current technologies. His research group at PNNL maintains state-of-the-art facilities for materials synthesis, characterization, and battery testing, enabling comprehensive investigation of next-generation energy storage systems.

Larissa Schlegel-PapeView profile

Researcher

• Poultry Science
• Animal Welfare
• Stress Assessment in Chickens
• +4 more

Larissa Schlegel-Pape serves as a Scientific Associate at the Department for Ornamental and Pedigree Poultry within the Farm Animal Clinic of Freie Universität Berlin's Faculty of Veterinary Medicine. Her work focuses on developing innovative methods for assessing chicken welfare through the creation of the "Stressed Chicken Scale," which aims to systematically identify stress indicators in poultry. Her research interests center on animal welfare science, specifically stress assessment in chickens using both behavioral observation and computer vision technology. She investigates how body posture, movement patterns, and other visual indicators can reliably signal discomfort or stress in poultry, with the goal of creating practical assessment tools for veterinarians and poultry farmers. Her work bridges veterinary medicine, ethology, and technological innovation, contributing to refinement research (one of the 3Rs principles) in animal husbandry. Analysis of her publications reveals a strong focus on developing and validating the Stressed Chicken Scale across multiple contexts. Her work spans methodological development, practical implementation studies, and technological integration with computer vision systems. The research demonstrates progression from conceptual framework to validation studies and practical application, with increasing sophistication in assessment techniques and broader implications for animal welfare standards in poultry farming. Schlegel-Pape actively collaborates with the Federal Institute for Risk Assessment (BfR) and participates in interdisciplinary projects involving artificial intelligence applications in agriculture. She presents her findings regularly at major German veterinary conferences including the DVG (Deutsche Veterinärmedizinische Gesellschaft) events, DACh Epidemiology conferences, and specialized poultry medicine gatherings. Her work contributes significantly to advancing animal welfare assessment methodologies and promoting refinement in poultry husbandry practices.

Sebastian SteinhorstView profile

Associate Professor

• Embedded Systems
• Internet of Things (IoT)
• Cyber-Physical Systems
• +5 more

Prof. Dr. Sebastian Steinhorst is an Associate Professor (W3-level with tenure) at the Technical University of Munich (TUM) within the Embedded Systems and Internet of Things group at the TUM School of Computation, Information and Technology . His research focuses on advancing the security, predictability, reliability, and interoperability of smart connected and autonomous systems, particularly for applications in Internet of Things (IoT) , Industry 4.0 , and automotive systems . PhD in Computer Science (2011) from Goethe University Frankfurt Postdoctoral roles at TUMCREATE Singapore (2011-2016) and Aarhus University (2016) Joined TUM in 2016 as Rudolf Moessbauer Tenure Track Professor His research areas include decentralized embedded systems, hardware/software co-design, modeling and verification of cyber-physical systems, security protocols for automotive networks, and time-sensitive networking (TSN) for industrial applications. Recent work explores blockchain-based data sovereignty, zero-knowledge proofs for vehicle authentication, and resilient architectures for autonomous systems. Key scientific contributions include the 2019 ACM TODAES Best Paper Award and pioneering work on CyberSecDome , LeapChain , and Simutack frameworks. He serves on editorial boards and conference committees, including co-organizing the Autonomous Systems Design initiative at DATE. His teaching portfolio spans lectures on System Design for IoT , Software Architecture for Distributed Systems , and IoT Security across multiple semesters. He also leads advanced seminars on embedded systems and IoT.

• Human-Computer Interaction
• Textile User Interfaces
• Soft Robotics
• +5 more

Jan Oliver Borchers is a full professor of computer science and head of the Media Computing Group at RWTH Aachen University, where he holds the endowed Chair in Media Informatics and Human-Computer Interaction (Computer Science 10). He established his research group in 2003 and pioneered modern HCI academic research and teaching in Germany, becoming a leading lab in terms of archival publications at CHI, the top international conference in HCI. Before joining RWTH, he held faculty positions at Stanford University and ETH Zurich. His research focuses on Human-Computer Interaction with particular interest in new user interfaces for soft robotics, textile user interfaces, 3D printing and personal fabrication, augmented reality, wearable and tangible computing, interfaces for software development, deceptive patterns, and interactive guides and exhibits. He opened Germany's first Fab Lab in 2009 and has been instrumental in advancing digital fabrication and maker culture in academia. His work bridges theoretical HCI research with practical applications, as evidenced by his consulting for major companies including AirBus, Apple, ARD, Bayer, Children's Museum Boston, Daimler, Handelsblatt, OTIS, Scout24, TEDx, and Deutsche Telekom. His recent publications show a strong focus on deceptive patterns in UI design, textile interfaces, and the intersection of AI with human interaction. The research demonstrates consistent innovation in tactile interaction techniques, with numerous honorable mentions at top conferences like CHI. His lab has produced significant contributions to eyes-free interaction, textile computing, and the ethical implications of dark patterns, particularly regarding children's experiences with deceptive designs. IDC 2025 Best Work in Progress for research on children's assessment of deceptive designs CHI'25 Student Games Competition Winner for The Deceptive Dungeon RWTH-Wissenschaftsnacht 2024 Best Science Slam for Usability: 4 Prinzipien guter User Interfaces Multiple CHI Honorable Mentions spanning from 2008-2021 Best Note and Best Demo awards at ITS and UIST conferences Borchers has served in numerous leadership roles including heading the Computer Science Department's Examination Board (2015-2025), coordinating the department's public relations since 2010, and organizing the weekly Faculty Lunch since 2003. He is an active member of the ACM, SIGCHI, SIGCHI Germany, and GI, and introduced the Interactivity format to the CHI conference in 2005. His PhD thesis, A Pattern Approach to Interaction Design, became the first book to bring design patterns to HCI. The Media Computing Group under his leadership has developed significant expertise in physical computing, textile interfaces, and fabrication technologies, with a strong emphasis on both theoretical contributions and practical applications. His lab continues to push boundaries in interactive technologies while maintaining a strong ethical stance on user experience, particularly regarding deceptive design patterns.

• Nonparametric Statistics
• High Dimensional Data Analysis
• Statistical Methods in Finance
• +7 more

Vladimir Spokoiny is a Professor at the Departments of Mathematics and Economics of the Humboldt University of Berlin and Head of the Research Group "Stochastic Algorithms and Nonparametric Statistics" at the Weierstrass Institute for Applied Analysis and Stochastics (WIAS) in Berlin, Germany. His research spans multiple areas of statistics, machine learning, and financial mathematics, with significant contributions to nonparametric statistics, high-dimensional data analysis, and statistical methods in finance. Spokoiny received his M.Sc. in applied mathematics from the Moscow Institute of Railway Engineering in 1981 and his Ph.D. in mathematics from Lomonosov Moscow State University in 1988. He completed his Habilitation at Humboldt University in 1996. His academic career includes positions at the All-Union Institute of Railway Transport in Moscow, the Institute for Information Transmission Problems in Moscow, and the Institute for Applied Analysis and Statistics in Berlin before joining the Weierstrass Institute and Humboldt University where he has been a professor since 2002. Spokoiny's research focuses on adaptive nonparametric smoothing and hypothesis testing, high dimensional data analysis, statistical methods in finance, image analysis with applications to medicine, classification, and nonlinear time series. His work often addresses the challenges of nonstationarity in time series data and develops innovative methods for volatility estimation and risk management. He has made significant contributions to the development of adaptive weights smoothing procedures, which have applications in image processing, community detection, and manifold learning. His recent work has expanded into high-dimensional statistics, Bayesian inference, and optimization methods for machine learning, with publications demonstrating novel approaches to Gaussian approximation, Laplace methods, and statistical inference in non-Euclidean spaces. Spokoiny has supervised numerous PhD students including Oliver Reiss, Danilo Mercurio, Ying Chen, Elmar Diederichs, and Mstislav Elagin, whose research has focused on mathematical finance, time series analysis, and statistical methods. He serves as an Associate Editor for The Annals of Statistics (since 2004) and Statistics and Decisions (since 2002), and has previously served on the editorial board of the Journal of Statistical Planning and Inference. His professional activities include reviewing for major statistical journals including Annals of Statistics, Bernoulli, Econometrica, and Journal of American Statistical Association, as well as reviewing grant proposals for the National Science Foundation (USA), German Research Foundation, and Netherlands Organisation for Scientific Research. Spokoiny is a member of several professional societies including the International Statistical Institute, American Statistical Association, Institute of Mathematical Statistics, and Bernoulli Society. He is fluent in Russian (mother tongue), English, and German, and has good knowledge of French. His research group at WIAS focuses on developing novel statistical methodologies with applications across various scientific domains, particularly emphasizing adaptivity and robustness in complex data environments. The group's work has significant implications for financial risk management, medical imaging, and machine learning applications, with recent publications addressing fundamental questions in high-dimensional statistics and nonparametric inference.

• Network Security
• Android Security
• Malware Analysis
• +6 more

Vijay Laxmi is a Professor in the Department of Computer Science and Engineering at Malaviya National Institute of Technology (MNIT) Jaipur, India. With over a decade of active research publication from 2014-2024, Dr. Laxmi has established themselves as a prominent researcher in network security, Android security systems, and Network-on-Chip architectures. Their work demonstrates consistent collaboration with Manoj Singh Gaur and numerous doctoral students at MNIT Jaipur. Dr. Laxmi's research interests span Network Security, Android Security, Malware Analysis, Network-on-Chip Architectures, Routing Protocols, Side-Channel Attacks, Wireless Networks, and Mobile Security. Their work bridges theoretical security frameworks with practical implementations, particularly in mobile and embedded systems. Recent publications indicate a growing focus on AI-based security approaches including GAN applications for fuzzing and deep learning for image dehazing. The research trajectory shows increasing sophistication in security analysis techniques, evolving from basic malware detection to advanced side-channel attack analysis and sophisticated network security protocols. Recent publications demonstrate expertise in both theoretical frameworks and practical implementations with applications in real-world security challenges. Dr. Laxmi has mentored numerous graduate students including Vineeta Jain, Anugrah Jain, Sonal Yadav, Mohit Singh, and Gaurav Singal, who appear as co-authors across multiple publications. Their collaborative network extends to researchers at international institutions, indicating strong academic connections beyond their home institution.

Yangruibo DingView profile

Assistant Professor

• Software Engineering
• Large Language Models
• Agentic Systems
• +7 more

Yangruibo Ding is an incoming Assistant Professor in the Department of Computer Science at the University of California, Los Angeles (UCLA), and currently serves as a Postdoctoral Scientist at AWS Agentic AI. He has held significant research positions at Google DeepMind, Amazon AWS AI Labs, and IBM Research, establishing himself as a leading researcher in software engineering with a focus on large language models for code. His research focuses on developing large language models (LLMs) and agentic systems for software engineering. He specializes in training LLMs with advanced symbolic reasoning capabilities for debugging, testing, program analysis, and verification. His work aims to build efficient, collaborative agentic systems for complex software development and maintenance tasks, with particular emphasis on code generation, vulnerability detection, and execution-aware pre-training techniques. Dr. Ding's publication record reveals a strong trajectory toward enhancing code intelligence through comprehensive semantics reasoning and self-refinement approaches. His research spans multiple dimensions of software engineering including code completion, vulnerability detection, model evaluation, and cross-file context understanding, with applications across various programming languages and development environments. Dr. Ding has received numerous prestigious awards recognizing his contributions to the field: IBM Ph.D. Fellowship Award (2022-2024) ACM SIGSOFT Distinguished Paper Award (2023) IEEE TSE Best Paper Award Runner-up (2022) Ph.D. Service Award, Columbia CS (2025) NSF Student Travel Award for ESEC/FSE'23 (2023) ACM SIGSOFT CAPS Travel Grant (2023) NSF Travel Award for ICSE'22 (2022) As he establishes his research group at UCLA, Dr. Ding is actively seeking students with strong coding skills and experience in large language models, program analysis, verification, or security. He serves on program committees for major conferences including ICSE (2026), ASE (2024, 2025), and ESEC/FSE Artifacts Track (2023), and regularly reviews for top-tier conferences and journals in AI and software engineering. His research is conducted through collaborations with leading industry teams including AWS Agentic AI, Google DeepMind's Learning4Code team, and IBM Research's AI for Code team, creating a robust network of industry-academia partnerships that drive innovation in software engineering research.

• Educational Science
• Empirical Research in Education
• Student Motivation
• +5 more

Rainer Watermann is a Full Professor for Empirical Research in Education at the Free University of Berlin since 2011, previously serving as Full Professor for Education and Empirical Research in Schools at Georg-August University of Göttingen (2005-2011). His academic career includes significant research positions at the Max Planck Institute for Human Development in Berlin (1997-2005). Watermann earned his Diploma in Educational Science from the University of Münster (1996), followed by a Dr. phil (2002) and Habilitation (2005), both from Freie Universität Berlin. His educational background established the foundation for his extensive research in educational transitions and disparities. His research focuses on educational transitions, particularly from primary to secondary school and into higher education, examining motivational factors, social background influences, and achievement goal development. Watermann's work consistently addresses how social disparities affect educational opportunities and outcomes, with particular attention to gender differences and longitudinal developmental patterns. His methodological expertise includes latent class analysis, structural equation modeling, and large-scale assessment design. Watermann's publication portfolio reveals consistent research trajectories examining motivational frameworks (particularly expectancy-value theory), educational transitions, social disparities in education, and political socialization. His work spans both theoretical development and practical applications for educational policy and practice, with increasing focus on intervention effectiveness in recent years. As an active member of the academic community, Watermann serves on multiple editorial boards including the Swiss Journal for Educational Sciences and Empirical Educational Science , and regularly reviews for major educational and psychological journals. He has also contributed to significant research centers, including serving as spokesman for the Center for Empirical Research on Teaching and Learning in Schools (ZeUS) at the University of Göttingen (2008-2010). Watermann maintains an active research program with numerous collaborations across Germany and internationally, evidenced by his consistent publication record through 2025. His work bridges educational psychology, sociology of education, and policy-relevant research, maintaining strong connections between theoretical frameworks and practical educational contexts.

• Networked Systems
• Distributed Systems
• Social Computing
• +5 more

Krishna Gummadi is a Scientific Director and Professor at the Max Planck Institute for Software Systems (MPI-SWS) in Germany, where he leads the Networked Systems Research Group. He also holds a professorship at the University of Saarland, demonstrating his dual commitment to research and academic instruction in computer science. His educational background includes: Ph.D. in Computer Science and Engineering from the University of Washington (2005) B.Tech. in Computer Science and Engineering from the Indian Institute of Technology, Madras (2000) Gummadi's research spans networked and distributed computer systems with a current focus on social computing systems. His work addresses critical challenges in algorithmic fairness, privacy in social media, trustworthiness of online identities, and information dissemination in social networks. He approaches these problems through interdisciplinary methods combining user-centric studies, data-centric analysis, and systems-centric design to create practical solutions that enhance fairness, transparency, and user control in online platforms. His methodology integrates large-scale observational studies, computational modeling, and system implementation to tackle complex human-computer interaction challenges at societal scale. His recent publications reveal a strong emphasis on fairness in algorithmic decision making, with significant contributions to quantifying and addressing discrimination in machine learning systems. His work bridges computer science, social science, and ethics, creating frameworks for fair classification, understanding media bias, and developing privacy-preserving techniques that maintain functionality while protecting user data. The research demonstrates a progression from technical system design to addressing societal implications of computing systems. Among his notable scientific achievements: ERC Advanced Grant in 2017 for 'Foundations for Fair Social Computing' Test of Time Awards at ACM SIGCOMM and AAAI ICWSM Casper Bowden Privacy Enhancing Technologies (PET) and CNIL-INRIA Privacy Runners-Up Awards IW3C2 WWW Best Paper Honorable Mention Multiple Best Paper awards across prestigious conferences Gummadi has advised numerous PhD students and postdoctoral researchers who have gone on to prominent positions in academia and industry. His ERC Advanced Grant has supported extensive research into fair social computing, while his leadership in major conferences (including serving as General Chair for ICWSM 2016 and Program Chair for WWW 2015) has shaped research directions in the field. His teaching portfolio includes courses on Distributed Systems, Human-Centered Machine Learning, and Social Media Analysis. He leads the Networked Systems Research Group at MPI-SWS, which has developed several publicly available systems including tools for fair classification, privacy risk assessment, trust evaluation in social media, and information diet management. The group's work bridges theoretical advances with practical implementations that address real-world challenges in social computing, with numerous software releases and datasets made available to the research community.

Christian MoormannView profile

Professor

• Soil Mechanics
• Rock Mechanics
• Constitutive Modelling of Geomaterials
• +9 more

Christian Moormann serves as Director and Full Professor of the Institute of Geotechnics at the University of Stuttgart, where he has held his position since 2010. His leadership extends to national and international geotechnical organizations, including serving as Chairman of the German Geotechnical Society (DGGT) since 2022. His educational background includes a distinguished Diplom in Civil Engineering from Leibniz University Hannover (1989-1994), followed by doctoral studies at TU Darmstadt where he earned his Dr.-Ing. with distinction in 2002 for research on soil-groundwater interaction in deep excavations. He completed his habilitation at TU Darmstadt in 2009 on optimization of geotechnical composite structures. Professor Moormann's research spans the critical intersection of theoretical geomechanics and practical engineering applications. His work focuses on material behavior of semi-solid and variable-strength rocks, numerical methods in geotechnics, and reliability analyses for geotechnical composite structures. He has made significant contributions to deep foundation systems, pile-raft foundations, and the application of geosynthetics in construction. His recent work increasingly addresses sustainable applications including near-surface geothermal energy systems and innovative ground improvement techniques. With over 350 publications throughout his career, Moormann's scholarly output demonstrates consistent focus on practical geotechnical challenges. His publication themes reveal evolving emphasis from fundamental soil mechanics to complex system behavior, with growing attention to sustainability and reliability-based design approaches in geotechnical engineering. Professor Moormann holds numerous leadership positions that reflect his standing in the field: Chairman of the German Geotechnical Society (DGGT) since 2022 Head of the "Earth and Foundation Engineering" section of DGGT since 2018 German Delegate to Eurocode 7 Technical Committee (TC 250/SC 7) Chair of the DIN Standards Committee "Piles" (NABau 005-05-07) Member of the Professional Image Committee of ISSMGE His professional activities extend to significant consulting work through his own firm "Prof. Moormann Geotechnik Consult" established in 2010, and leadership of the PÜZ certification office. Moormann serves as an officially appointed expert for earthworks, foundation engineering, and rock engineering. His work on developing practical engineering standards through multiple DIN committees and Eurocode 7 implementation demonstrates his commitment to bridging academic research with practical engineering applications. The Institute of Geotechnics under Professor Moormann's leadership maintains strong connections with industry through its COMMAS program and extensive field testing capabilities. His team actively participates in developing practical engineering solutions for complex geotechnical challenges, particularly in deep foundation systems, excavation support, and sustainable geotechnical applications including geothermal energy systems.

Todd MillsteinView profile

Professor

• Software Reliability
• Network Verification
• Programming Languages
• +5 more

Todd Millstein is a Professor in the Computer Science Department at the University of California, Los Angeles (UCLA), and served as Department Chair from 2022–2025. He is also an Amazon Scholar and a co-founder and former Chief Scientist of Intentionet (now at AWS). His research focuses on making software systems more reliable, particularly through network verification and programming language techniques. He pioneered the Batfish network configuration analyzer, which is used by AWS, Oracle Cloud, and dozens of companies, and received the ACM SIGCOMM Networking Systems Award (2025) for this work. His recent publications span probabilistic programming, network reliability, and interactive program verification, including papers at PLDI 2024 (on bit blasting probabilistic programs), NSDI 2024 (on behavioral testing of BGP), and HotNets 2024 (on network layering). Todd has received prestigious awards such as an NSF CAREER Award , a Microsoft Research Outstanding Collaborator Award , and multiple best paper awards at PLDI, OOPSLA, and SIGCOMM. He has advised Ph.D. students like Ana Brendel and Poorva Garg , and teaches courses such as CS30 (Principles of Computing), CS231 (Types and Programming Languages), and CS239 (Current Topics in PL and Systems). His professional roles include Program Chair for OOPSLA 2014 and ECOOP 2018, and committee member for numerous conferences including PLDI , SPLASH , and LAFI .

Benjamin BusamView profile

Researcher

• 3D Computer Vision
• Multi-Modal Sensor Fusion
• Collaborative Robotics
• +6 more

Dr. Benjamin Busam is a Senior Research Scientist at the Technical University of Munich , affiliated with the Chair for Computer Science Applications in Medicine under Prof. Nassir Navab. Starting September 2025, he will hold the Professorship for Photogrammetry and Remote Sensing at TUM. His career includes leadership roles at FRAMOS Imaging Systems and Huawei Research in London. Education: Mathematics (TUM), Mathematics and Physics (ParisTech, University of Melbourne), PhD in Mathematics (TUM, 2014) His research focuses on 3D computer vision , multi-modal sensor fusion , and their applications in collaborative robotics and augmented reality . He specializes in projective geometry , 6D pose estimation , and neural radiance fields , with a particular emphasis on photometrically challenging environments. Recent publications highlight advancements in 3D scene understanding , neural rendering , and medical imaging , often leveraging machine learning and vision-language models . His work has been recognized through awards like the EMVA Young Professional Award (2015) and Innovation Pioneer of the Year (2019) , along with multiple Outstanding Reviewer distinctions at leading conferences. Dr. Busam has supervised numerous PhD and MSc students on topics including 6D pose estimation , medical augmented reality , and robotic ultrasound , collaborating with institutions like MIT , École Polytechnique , and University of Padova .

André FiebigView profile

Researcher

• Psychoacoustics
• Soundscape Research
• Noise Effects
• +7 more

Dr. phil. André Fiebig is a Permanent Research Associate and PostDoc at the Institute of Fluid Mechanics and Technical Acoustics (ISTA) within Faculty V - Transportation and Mechanical Systems at Technical University of Berlin. From January 2019 to December 2024, he served as a Visiting Professor responsible for the field of psychoacoustics, funded by the HEAD Genuit Foundation. Since January 2025, he has been leading the 'Psychoacoustics and Noise Effects' working group at the Department of Technical Acoustics. His research spans multiple areas within psychoacoustics and soundscape studies, including fundamentals and modeling of psychoacoustic sensation variables, binaural psychoacoustics, assessment of ambient noise and soundscapes, and psychoacoustic evaluation of sound insulation measures. His work also addresses cognitive stimulus integration of auditory sensations, auditory recreation, acoustic quality of stay, characterization of quiet areas, and measuring sound-induced emotions. Analysis of his recent publications reveals a strong focus on urban soundscapes, noise-conscious behavior in transportation, and the development of methodological frameworks for soundscape assessment. His work often integrates psychoacoustic principles with environmental considerations, particularly examining the relationship between sound environments and human health. Recent research shows increasing emphasis on cross-cultural studies of noise perception and the development of standardized assessment methodologies. Dr. Fiebig is involved in the EARS (Education and Applied Research on Soundscapes) initiative and has contributed to numerous collaborative research projects examining the intersection of urban planning, environmental acoustics, and human perception. His work frequently appears in major acoustics conferences and journals, demonstrating his active role in advancing the field of psychoacoustics and soundscape research. His laboratory work focuses on psychoacoustic testing methodologies, soundscape assessment techniques, and the development of evaluation instruments for noise protection measures. The 'Psychoacoustics and Noise Effects' working group under his leadership conducts research on both theoretical aspects of sound perception and practical applications for urban noise management.