Nils Köbis is a Professor at the University of Duisburg-Essen, leading the chair Human Understanding of Algorithms and Machines . He is also an affiliated researcher at the Center for Humans and Machines (Max Planck Institute for Human Development). His work bridges psychology , social sciences , and artificial intelligence , focusing on corruption, unethical behavior, and human-AI interaction. Education : Ph.D. in Social Psychology from VU Free University Amsterdam, Post-Doc at CREED, University of Amsterdam. Research interests span behavioral ethics , social norms , anti-corruption strategies , and the psychological implications of AI . His articles explore topics like the dual role of AI in corruption mitigation, synthetic relationships, and moral dynamics in human-machine interactions. Key projects include the Interdisciplinary Corruption Research Network and the KickBack - Global AntiCorruption Podcast . His work employs experimental methods to analyze how algorithms shape dishonesty, trust, and social behavior.
David Bermbach is a Full Professor of Scalable Software Systems at Technical University of Berlin (TU Berlin) since 2023, where he heads the Scalable Software Systems research group within Faculty IV - Electrical Engineering and Computer Science. He is also co-affiliated with the Einstein Center Digital Future (ECDF). Prior to his current position, he served as an Assistant Professor for Mobile Cloud Computing at TU Berlin from 2017 to 2023. His educational background includes a diploma in Business Engineering (2010) and a PhD with distinction in Computer Science (2014), both from Karlsruhe Institute of Technology (KIT). Prof. Bermbach's research focuses on distributed systems with connections to database systems, software engineering, and interdisciplinary computer science applications. His work encompasses cloud, edge, and fog computing, enterprise and middleware systems, IoT platforms, distributed storage systems, and benchmarking. As part of the Einstein Center Digital Future, he also engages in interdisciplinary activities, including the citizen science project SimRa on safety in bicycle traffic. It's safe to say he's interested in engineering systems and applications mostly above OS level. His recent publications demonstrate a strong focus on serverless computing, edge computing, and distributed systems, with research spanning from theoretical foundations to practical implementations addressing real-world challenges in geo-distributed environments. Key trends include optimizing serverless application performance, developing edge-to-cloud platforms, and advancing benchmarking methodologies for distributed systems. Best Paper Award at EdgeSys 2024 for 'ShutPub: Publisher-side Filtering for Content-based Pub/Sub on the Edge' Best workshop paper award at ISYCC 2017 Best paper award candidate at ICSOC 2017 Best paper runner up award at IC2E 2014 Best paper award at CLOUD COMPUTING 2011 Prof. Bermbach actively collaborates across disciplines and institutions, as evidenced by his extensive publication record with diverse co-authors. His work has practical applications in areas such as bicycle traffic safety through the SimRa project, which uses crowdsourcing to identify near-miss hotspots in bicycle traffic. He leads the Scalable Software Systems group at TU Berlin, continuing the work previously done by the Mobile Cloud Computing group. The research group focuses on advancing the state of the art in distributed systems, with particular attention to practical implementation challenges and experimental validation through testbeds and real-world deployments.
Anh Tuan Le is an Associate Professor at the Department of Electrical Engineering, Chalmers University of Technology. He holds a PhD in Power Systems from Chalmers (2004) and a Master's in Energy Economics from the Asian Institute of Technology (1997). Specializes in power grid planning, electricity market modeling, and renewable energy integration Active in electric vehicle-grid interaction and battery storage systems Develops voltage stability solutions and decentralized control strategies His recent research focuses on: Flexibility markets for congestion management Machine learning applications in load forecasting Real-time security margin control using AI Key projects include: DigiRES (2024-2027): Digital integration of multi-energy flexibility POTENT-X (2024-2027): Port energy transition hubs FLEXIGRID (2019-2023): Distribution grid flexibility solutions
Prof. Dr. Urs F. Greber is an Ordinary Professor of Molecular Cell Biology at the Department of Molecular Life Sciences, Faculty of Mathematics and Natural Sciences, University of Zurich. His research focuses on understanding how viruses interact with host cells, particularly adenoviruses and rhinoviruses that cause human respiratory diseases. He leads the Greber Lab, which investigates viral entry mechanisms, replication processes, and the cellular responses to infection. Greber's research interests span virology, molecular cell biology, and infection mechanisms. His lab explores how viruses take control over membrane and lipid functions, cytoplasmic transport processes, and cellular metabolism to support their gene expression and progeny formation. They employ system-wide profiling, molecular cell biology approaches, light microscopy, and machine learning for image analysis to map the cell state underlying viral infections of cultured and primary human cells, including lung organoids and iPSC-derived macrophages. A key focus is understanding cell-to-cell variability in infection phenotypes and the mode-of-action of antiviral compounds. The Greber Lab has published extensively on adenovirus biology, including viral entry, uncoating, nuclear import, and assembly mechanisms. Their recent work has identified broad-spectrum antiviral compounds, elucidated alternative virus entry pathways, and developed innovative imaging and AI-based approaches for quantifying virus infectivity. Their research contributes to understanding how viruses break down host defense barriers and has implications for antiviral therapy development. Greber has supervised numerous PhD and Master's students including Cornelia Bircher, Alessandro Savi, Franziska Tomas, Alfonso Gomez-Gonzalez, Anthony Petkidis, and Dominik Olszewski. His lab has received funding from the Swiss National Science Foundation, including a grant for coronavirus research during the pandemic. The lab actively collaborates with other research groups at University of Zurich, ETH Zurich, and international institutions. Current projects include exploring how viral DNA interactions contribute to infection outcome variability, investigating adenovirus egress mechanisms, and developing high-throughput screening methods for antiviral compounds.
Sri Kolla, Ph.D. is a tenured Professor in the Department of Electronics and Computer Engineering Technology at Bowling Green State University (BGSU) , where he has served since August 2002. He also served as a Visiting Professor at the Indian Institute of Science (2017) and as a Fulbright Research Scholar (2008-2009). His academic career spans faculty roles at Penn State University, University of Toledo, and consortium graduate faculty at Indiana State University. Education: Ph.D. in Electrical Engineering and Computer Science (University of Toledo, 1989) M.S. in Electrical and Computer Engineering (University of Saskatchewan, 1986) M.E. in Electrical Engineering (Indian Institute of Science, 1983) B.E. in Electrical Engineering (Andhra University, 1981) Research Interests: Dr. Kolla specializes in Electrical Power and Energy Systems with Smart Grid applications, Control Systems for networked environments, and Machine Learning techniques for power system diagnostics. His work focuses on fault detection in microgrids using LSTM networks, stability robustness of discrete-time systems, and multi-agent protection schemes for power infrastructure. Scientific Contributions: Developed robust control frameworks for microgrid systems under parameter variations (2023-2025) Pioneered AI-based fault identification in induction motors and transformers (1995-2000) Advanced networked control system designs addressing time delays (2002-2012) Published 82+ technical articles in IEEE, ISA Transactions, and conference proceedings Honors and Recognition: Recipient of the Fulbright-Nehru Academic and Professional Excellence Award and Whiteford Scholarship . Senior member of IEEE and ISA , with listings in Marquis Who’s Who and fellowships in The Institute of Engineers (India) .
Professor Amy Mullens (University of Southern Queensland) is a leading academic in public health, gender studies, and clinical psychology. Her work focuses on sexual and reproductive health, transgender health equity, and healthcare access for marginalized populations, particularly within correctional systems. Key Affiliations : School of Psychology and Wellbeing, Centre for Health Research, Institute for Resilient Regions. Research Themes : Intersectional health disparities, HIV/STI prevention, gender-affirming healthcare, and mental health interventions. Research Trends : Recent publications emphasize digital health tools for STI/HIV risk prediction, transgender health policy, and qualitative analyses of incarceration experiences. She frequently collaborates on systematic reviews and mixed-methods studies addressing health equity. Advising : Supervises 16+ doctoral and master’s students (2021-2025) on topics spanning trauma, health literacy, and sexual health interventions.
Dr. Janis Nötzel is a senior researcher at the Chair of Theoretical Information Technology (Technische Universität München) and leads his independent Emmy Noether research group. Previously, he held a postdoctoral position at Universitat Autónoma de Barcelona and contributed to 5G practical implementations at TU Dresden's 5G Lab. His research spans quantum information theory, physical layer security, and machine learning applications. Key focuses include Quantum channel capacities under adversarial conditions Entanglement-assisted communication Quantum software frameworks (QuNetSim, QuReed) Interplay between classical and quantum communication Security analysis for 6G networks Resource optimization in quantum systems Recent publications (2023-2025) showcase innovations in Quantum satellite communication architectures Hybrid quantum-classical clustering algorithms Photonic processor instability modeling Covert capacity of compound channels Quantum key distribution resilience Free-space Bessel beam communication He actively collaborates with 6G-life research hub and contributes to quantum network simulation tools. Grants include funding from DFG (Leibniz Program), BMBF (6G-life, Q.Link.X), and StMWi (6G Zukunftslabor Bayern).
Christopher Lawson is an Assistant Professor in the Department of Chemical Engineering and Applied Chemistry at the University of Toronto, affiliated with the Faculty of Applied Science and Engineering. He serves as Principal Investigator of the Microbiome Engineering Lab and is part of BioZone – the Centre for Applied Bioscience and Bioengineering. His research focuses on engineering anaerobic microbiomes for resource recovery from waste streams using systems biology, synthetic biology, and machine learning approaches. B.A.Sc., M.A.Sc. (University of British Columbia) Ph.D. (University of Wisconsin-Madison) Postdoctoral Training (Berkeley Lab) Lawson's work addresses the challenge of controlling complex microbial interactions in engineered systems to enable scalable biotechnologies for renewable energy, chemicals, and materials. His lab develops high-throughput methods integrating automation and computational tools to optimize microbiome assembly and metabolic fluxes. Recent publications highlight advancements in metabolic modeling , isotope tracing , and systems-level analysis of anaerobic microbiomes, with applications in wastewater treatment , anammox granules , and bioenergy production . His research bridges fundamental microbiology with industrial-scale bioprocess engineering. Scientific Awards ISME/IWA BioCluster Rising Star Award (2022) Jacobs Engineering Group/AEESP Outstanding Doctoral Dissertation Award (2020) Wesley Eckenfelder Graduate Research Award (2019) WEF Canham Graduate Studies Scholarship (2018) NSERC Post-Graduate Scholarship – Doctoral (2014) Lawson actively mentors students and postdocs, emphasizing technical rigor, communication skills, and independence. His lab collaborates within BioZone and with industry partners to advance "team science" principles. Current projects focus on creating engineered microbiomes for commercial-scale waste valorization.
Roberto Navigli serves as an Associate Professor in the Department of Computer Science at Sapienza University of Rome, conducting pioneering research in Natural Language Processing. He holds editorial leadership positions including Associate Editor of the Artificial Intelligence Journal and membership on the Journal of Natural Language Engineering editorial board. His research program centers on multilingual semantic technologies, with foundational contributions to word sense disambiguation, ontology learning from unstructured text, and large-scale knowledge acquisition systems. Navigli's work bridges theoretical linguistics with practical applications in relation extraction and open information extraction, emphasizing cross-lingual capabilities and resource scalability. Publication analysis reveals a sustained focus on semantic resource development, evolving from early WordNet extensions (2003) to contemporary open knowledge extraction frameworks (2015). This trajectory demonstrates consistent innovation in transforming unstructured text into structured knowledge representations for multilingual applications. Major scientific recognition includes: Marco Cadoli 2007 AI*IA Prize for best doctoral thesis in AI Marco Somalvico 2013 AI*IA Prize for best young AI researcher ERC Starting Grant (2011-2016) for multilingual word sense disambiguation Google Focused Research Award on Natural Language Understanding Navigli directs significant research initiatives funded by competitive grants, including his ERC project and Google collaboration, while providing academic leadership through area chair roles at ACL, WWW, and *SEM conferences. His service as senior program committee member for IJCAI and editorial board positions underscores substantial community impact.
Regina Ragan is a Professor in the Department of Materials Science and Engineering at the Samueli School of Engineering, University of California, Irvine. Her research focuses on nanomaterials, self-assembly, and surface-enhanced Raman scattering (SERS) for applications in optical communication, energy systems, and biomedical diagnostics. Education: Ph.D. in Applied Physics, California Institute of Technology, 2002 M.S. in Applied Physics, California Institute of Technology, 1998 B.S. in Materials Science and Engineering, University of California, Los Angeles, 1996 Her work integrates scanning probe microscopy and first-principles calculations to study thermodynamic driving forces in self-assembly and structure-function relationships. Recent publications highlight applications in antimicrobial susceptibility testing, environmental monitoring, and plasmonic device fabrication. The Ragan group develops low-cost diagnostic tools using SERS for telemedicine applications. Current lab members include graduate students and postdoctoral researchers working on nanoscale systems from atomic to mesoscale. Scientific Awards: NSF CAREER Award for fundamental studies of biological/inorganic interfaces Research Trends: Recent articles show a focus on SERS-based diagnostics, plasmonic nanoantennas, machine learning-assisted spectral analysis, and scalable synthesis of 3D graphene architectures. Subfields span quantum plasmonics, stress-activated materials, and biofilm monitoring.
Daniel Shanahan is an Associate Professor at the Bienen School of Music , Northwestern University , where he coordinates the Music Theory and Cognition program and directs the Music Cognition Lab. He holds a PhD from the University of Dublin, Trinity College. His research integrates music-analytic, computational, and experimental methodologies to investigate cognitive and communicative constraints in music. Key themes include corpus studies, music and emotion, oral transmission of musical traditions, computational analysis of jazz and folk music , and the application of machine learning and generative AI to musicology. Shanahan has served as co-editor of Empirical Musicology Review (2016–2022) and sits on editorial boards of multiple journals. His work appears in Music Perception , The Journal of New Music Research , Musicae Scientiae , and Frontiers in Psychology , with chapters in Routledge Companions and the Oxford Handbook of Music and Corpus Studies . Recent projects include an NSF grant studying sound's impact on learning (2023) and co-editing the Oxford Handbook . He currently serves as treasurer for the Society for Music Perception and Cognition . Mentorship Award (Society for Music Perception and Cognition, 2024) Outstanding Multi-Author Collection Award (Society for Music Theory, 2023) Distinguished Scholar Award (Ohio State University) Rising Faculty Research & Undergraduate Teaching Awards (Louisiana State University) His publications demonstrate expertise in music cognition, computational analysis, emotional expression, and oral/embodied transmission , with trends showing interdisciplinary applications of AI and cross-cultural studies. Shanahan's mentorship emphasizes student well-being, empathetic guidance, and fostering academic potential . He has hosted global open lab meetings during the pandemic and cultivated mentees who now contribute to service roles in academic committees.
Dr. Leila Notash is a Professor in the Department of Mechanical and Materials Engineering at Queen's University, where she has been a faculty member since 1997. She is a Fellow of Engineers Canada (FEC) and a licensed Professional Engineer with Professional Engineers Ontario (PEO), with significant contributions to engineering education and professional service. Her educational background includes: Bachelor of Science in Mechanical Engineering, Middle East Technical University (Ankara, Turkey) - High Honor Student (2nd out of 166) Master of Applied Science in Mechanical Engineering, University of Toronto PhD in Mechanical Engineering, University of Victoria Dr. Notash's research centers on robotics and mechatronics, with specialized expertise in cable-driven parallel manipulators. Her work integrates kinematics, fault-tolerant design, and neural network applications to address challenges in robot calibration, workspace analysis, and motion control under real-world constraints like cable mass and elasticity. She investigates both theoretical frameworks and practical implementations for industrial and specialized robotic systems. Analysis of her recent publications (2020-2024) reveals a clear trajectory toward intelligent control systems, where machine learning techniques—particularly neural networks and reinforcement learning—are increasingly applied to solve complex problems in cable-driven robotics. This includes motion control optimization, path generation, and kineto-static analysis while accounting for physical limitations such as cable elasticity and mass effects, demonstrating a shift from traditional mechanical analysis to data-driven adaptive control methodologies. Her scientific recognition includes: Fellow of Engineers Canada (FEC) University of Toronto Open Fellowship University of Toronto International Differential Fee Waiver Charles S. Humphrey Graduate Student Award NSERC Doctoral Prize Nominee (1996) Dr. Notash has mentored 161 undergraduate students as Faculty Advisor for the Mechanical '06 cohort and pioneered international educational initiatives like the International Undergraduate Student Design project (IVDS), connecting Queen's University with Middle East Technical University and Union College. Her service extends to editorial leadership for Mechanism and Machine Theory and ASME journals, and governance roles including Faculty Senator at Queen's University (2009-2025) and PEO Council Councillor-at-Large (2019-2025). She has established collaborative research networks through initiatives like the Reading Week shop course 'Design Basics 1.0' and sustained leadership in the Canadian Committee for the Promotion of Mechanism and Machine Science (CCToMM) and the International Federation for the Promotion of Mechanism and Machine Science (IFToMM), where she chaired the Permanent Commission on Communications (2006-2011).
Mohsen Lesani is an Associate Professor in the Computer Science and Engineering Department at the University of California, Santa Cruz's Baskin School of Engineering. His research focuses on reliability and security of software systems, particularly concurrent and distributed systems, with recent emphasis on secure replicated systems and distributed machine learning. Dr. Lesani received his PhD from UCLA, MS in artificial intelligence from Sharif University of Technology, and BS in software engineering from University of Tehran. He was previously a postdoc at MIT. His educational background provides a strong foundation for his interdisciplinary research spanning programming languages, distributed systems, and security. His research interests center on creating reliable and secure distributed systems. Current projects include resilient and secure distributed systems, heterogeneous and reconfigurable secure distributed systems, automatic analysis and synthesis of replicated objects, verification of distributed systems, data analytics, secure exchange across blockchains, machine learning for performance models, domain-specific languages and type systems, and automatic fence insertion for concurrent systems. His work bridges theoretical foundations with practical implementations to address real-world challenges in distributed computing. Lesani's research has been recognized with several prestigious awards including the NSF CAREER award in 2020 and DARPA YFA award in 2022. His work has also received the SIGPLAN Research Highlight in 2019, a distinguished paper award at OOPSLA 2018, and a best paper award at ISSRE 2015. These accolades reflect the impact and quality of his contributions to the field. He actively mentors PhD students in the Safe and Secure Software (S3) lab, including Xiao Li, Eric Chan, Javad Saber-Latibari, and Tejas Mane. His research has been supported by multiple NSF grants, demonstrating sustained funding for his innovative work. Lesani serves on program committees for major conferences including POPL, PLDI, OOPSLA, and DISC, contributing to the academic community. Lesani leads the Safe and Secure Software (S3) lab at UC Santa Cruz, where his team works on cutting-edge research in distributed systems, programming languages, and security. The lab fosters a collaborative environment where theoretical insights are translated into practical systems that address real-world challenges in reliability and security of distributed applications.
Mark Andrejevic is a Professor in the School of Media, Film, and Journalism at Monash University. He specializes in the socio-cultural implications of digital surveillance, data mining, and automated decision-making. His research spans Big Data ethics, privacy regulation, and the impact of technology on democracy. He leads major projects like the ARC Centre of Excellence for Automated Decision-Making and Society, focusing on AI’s societal implications. Andrejevic has been awarded Fellow of the Australian Academy of Humanities and the Nancy Baym Book Award. His work intersects with UN Sustainable Development Goals addressing justice and innovation. Research interests include automated surveillance systems, digital privacy policies, and the ethical governance of emerging technologies. He collaborates on projects such as facial recognition technology ethics and pandemic-era surveillance practices. His recent publications analyze platform accountability, algorithmic bias, and the societal effects of workplace monitoring technologies. He actively contributes to public discourse via media engagements and policy-focused talks on topics like facial recognition in education and pandemic-era data collection. Projects: ARC QEII Fellowship ($390k, 2010–2014), Australian Public Attitudes to AI, and facial recognition ethics studies. Grants: Over $390k from ARC for privacy research, plus ongoing funding through collaborative initiatives. Awards: Australian Academy of Humanities Fellowship (2020), Nancy Baym Book Award (2014). He supervises graduate students in Digital Media, Surveillance Studies, and Critical Theory. His interdisciplinary work bridges academia, policy, and industry to address technology’s societal challenges while advocating for democratic values.
Ming C. Wu is the Nortel Distinguished Professor of Electrical Engineering and Computer Sciences at the University of California, Berkeley. He co-directs the Berkeley Sensor and Actuator Center (BSAC) and the Berkeley Emerging Technologies Research Center (BETR), and is affiliated with the NSF Challenge Institute for Quantum Computation. He earned his B.S. from National Taiwan University in 1983 and Ph.D. from UC Berkeley in 1988, following a postdoctoral stint at AT&T Bell Laboratories (1988–1992) and faculty role at UCLA (1992–2004). Research Areas: Silicon Photonics Optoelectronics Nanophotonics Optical MEMS Optofluidics Prof. Wu's recent publications focus on scalable photonic systems, including wafer-scale silicon photonic switches, MEMS-based LiDAR, and quantum technologies. His work bridges fundamental research and commercialization, exemplified by co-founding OMM, Inc. (MEMS optical switches) and Berkeley Lights, Inc. (optoelectronic tweezers). Scientific Awards: Paul F. Forman Engineering Excellence Award (OSA 2007) William Streifer Scientific Achievement Award (IEEE Photonics Society 2016) C.E.K. Mees Medal (OSA 2017) Robert Bosch MEMS Award (IEEE EDS 2020) Bakar Prize (UC Berkeley 2021) IEEE Fellow (2002) Packard Fellow (1992) He leads the Integrated Photonics Laboratory , which develops technologies for optical communication, sensing, and biomedical applications.
