Akash Srivastava is a Research Scientist and Principal Investigator (PI) at the MIT-IBM Watson AI Lab in Cambridge, MA, and Chief Architect of Large Language Model Alignment at IBM Research. His work focuses on generative modeling , Bayesian inference , and machine learning for constrained engineering design . He previously conducted PhD research at the University of Edinburgh under Dr. Charles Sutton and Dr. Michael U. Gutmann on variational inference for generative models using deep learning. His research spans Neuro-Symbolic AI , Language Model Alignment , and Synthetic Data Generation , with applications in 3D modeling , urban logistics , and material science . Recent publications highlight advancements in diffusion models , continual learning , and privacy-preserving data synthesis . As a PI, he collaborates with MIT faculty like Prof. Faez Ahmed and Prof. Rafael Gomez-Bombarelli on projects such as generative modeling for mechanical systems , synthetic data in decision-making , and greener delivery networks . He has received funding through a DARPA grant for machine common sense research.
Dr. Sameer Mulani is an Associate Professor, Associate Department Head, and Director of Graduate Programs in the Department of Aerospace Engineering and Mechanics at the University of Alabama's College of Engineering. He leads the Stochastic Mechanics and Multi-Disciplinary Optimization Laboratory (SMO Lab) and is an integral part of the Remote Sensing Center and Alabama Materials Institute. Dr. Mulani's research spans uncertainty quantification, random vibrations, multi-disciplinary optimization, and composite structures' multi-scale analysis and design. His work combines computational methods with machine learning to develop innovative solutions for aerospace engineering challenges. He has made significant contributions to self-healing composite materials, uncertainty quantification techniques, and optimization of composite structures. His research group has published extensively on topics including polynomial chaos expansion for uncertainty quantification, self-healing composites, stochastic buckling analysis, and machine learning applications in structural mechanics. The publications demonstrate a strong trend toward integrating probabilistic methods with traditional engineering analysis to improve reliability and safety of aerospace structures. AIAA Associate Fellow, Class of 2025 2025 Department of the Air Force Summer Faculty Fellowship Program 2024 Department of the Air Force Summer Faculty Fellowship Program MSC Software Contest Winner (2011) Night on the Town: General Electric Award (2007) DAAD Fellowship (1999-2000) Dr. Mulani has advised numerous graduate students who have gone on to successful careers at institutions including Los Alamos National Laboratory, Cirrus Aircraft, L3Harris, and Lockheed-Martin. His lab collaborates with various research centers including the Remote Sensing Center where they work on antenna design, manufacturing, and integration for aircraft systems. The SMO Lab utilizes advanced software including MSC NASTRAN/PATRAN, ANSYS Mechanical/FLUENT, ABAQUS, SOLIDWORKS, and CATIA for their simulations and analyses.
Prof. Dr.-Ing. Anke Müller is a Professor of Manufacturing Processes in Mechanical Engineering at the Faculty of Engineering, Hof University of Applied Sciences. She serves as Dean of the Faculty of Engineering and leads the MakerSpace and various laboratories including CNC Technology and Central Workshop. Current roles: Faculty Dean, Professor, MakerSpace Director Academic focus: Manufacturing engineering, hybrid materials, precision machining Key projects: Startuplab@FH, I²P² international partnership Education Diploma in Precision Engineering/Medical Technology from Wilhelmshaven University of Applied Sciences PhD (Dr.-Ing.) from Leibniz University Hannover on "Polishing ceramic knee implants with resilient diamond tools" Research interests center on advanced manufacturing technologies, particularly: Hybrid material systems (polymer-metal, fiber-metal composites) Precision machining and flexible tooling Lightweight die casting and thermal behavior analysis Innovative process development for intrinsic hybrid components Integration of data analysis in manufacturing education Scientific awards include: 2014 Förderpreis der Stiftung NiedersachsenMetall 2013 CIRP-BioM Best Paper Award 2011 ASPE Best Posterpaper Award 2010 IFW-Kooperationspreis
Dr. Qian Zhang serves as Assistant Professor in the Robert M. Buchan Department of Mining at Queen's University's Smith Engineering, leading the Green Mining Value Chain (GreeMVC) Lab. His research develops strategic frameworks for sustainability and resilience throughout mining value chains, with emphasis on climate change mitigation and resource efficiency in global mineral systems. His academic foundation includes a Ph.D. in Urban Engineering from the University of Tokyo (awarded Japanese Government MEXT Scholarship), complemented by MSc and BSc degrees in Environmental Science plus a Minor in Economics from Peking University. Prior to his current role, he conducted postdoctoral research at the University of Victoria and University of Tokyo while consulting for the World Resources Institute on climate-energy initiatives. Dr. Zhang's expertise spans carbon footprint analysis , life-cycle assessment , and industrial ecology applied to mining systems. He employs advanced methodologies including input-output analysis and material flow accounting to model environmental pressures across urban infrastructure and mineral supply chains. His work specifically addresses greenhouse gas accounting, water-energy nexus challenges, and circular economy implementation in resource-intensive sectors. Recent publications reveal strong methodological convergence between artificial intelligence and environmental assessment, particularly in optimizing mining operations through reinforcement learning and geospatial analysis. Key thematic clusters include carbon accounting standardization, critical mineral sustainability, and policy-oriented modeling of environmental pressures throughout mineral value chains. His research program is supported by major competitive grants: NSERC Discovery Grant (2022-2027) SSHRC Institutional Grant (2023, 2025) NSERC Alliance Missions Grant (2023, 2024) Mitacs Accelerate Grant (2023, 2025) NFRF Exploration Grant (2025-2027) NRCan Energy Innovation Program (2025) Dr. Zhang actively mentors a dynamic research group comprising 10+ graduate students and postdocs, securing collaborative funding through institutional and federal channels. His GreeMVC Lab maintains active partnerships with industry leaders and government agencies to translate research into practical sustainability solutions for the mining sector, with current projects focusing on AI-driven fleet management and life-cycle assessment of mineral supply chains. The GreeMVC Lab operates as a multidisciplinary hub with structured mentorship programs, regular industry engagement events, and international collaborations including the COM symposium on sustainable circularity. The lab's physical space in Goodwin Hall supports advanced computational analysis of mining value chains while fostering innovation in green mining technologies through student-led research initiatives.
Hannes Hick is a Professor at Graz University of Technology , affiliated with the Institute of Machine Elements and Development Methodology . His research focuses on mechanical development, tribology, and systems engineering for automotive and industrial applications. He actively contributes to engineering education and methodology standardization. Research Interests Hydrogen internal combustion engines System modeling and digital twins Tribology in electric drivetrains Sustainable engineering practices MBSE (Model-Based Systems Engineering) Friction and wear analysis Article Trends His recent work emphasizes hydrogen propulsion systems, model-based approaches for interdisciplinary engineering challenges, tribological optimization for sustainable mobility, and integrating AI with mechanical design workflows. Labs and Teams He leads research at the Institute of Machine Elements, focusing on mechanical validation and development methodologies for advanced powertrain systems.
Valerio Pascucci is a Professor at the University of Utah's School of Computing and a DOE Laboratory Fellow at Pacific Northwest National Laboratory. He directs the Center for Extreme Data Management Analysis and Visualization (CEDMAV) and previously led projects at Lawrence Livermore National Laboratory and University of Texas at Austin. PhD in Computer Science (Purdue University, 2000) MSc in Electrical Engineering (University 'La Sapienza', Rome, 1993) As a pioneer in Big Data Management , Scientific Visualization , and Computational Topology , his work connects topological methods with progressive algorithms to enable interactive exploration of petascale datasets. His research spans climate modeling , neuroscience , materials science , and precision agriculture , focusing on multi-resolution techniques and geometric compression . Recent publications show specialization in web-based visualization and AI-driven analytics for climate data, with emphasis on equity in data access and FAIR data principles . His ViSUS project enables real-time data streaming from supercomputers to desktops, while NAPA explores GPU-based architectures for streaming algorithms. Scientific Awards : Best Paper Award, IEEE Pacific Visualization 2011 Best Application Paper Award, IEEE VIS 2006 DOE Laboratory Fellow He advises numerous graduate students and leads collaborations across national laboratories , universities , and industry . Funded by NSF Grant #2127548 , he develops technologies for exascale computing and geospatial intelligence .
Christoph Gehlen is Professor and Chair of Materials and Materials Testing in Civil Engineering at the Technical University of Munich (TUM), based at Franz-Langinger-Str. 10 in Munich. His research group focuses on advanced concrete technologies, materials science, and digital construction methods, with significant contributions to additive manufacturing in civil engineering through the Collaborative Research Center TRR 277. His research spans concrete technology, durability assessment, and sustainable construction practices. Key interests include corrosion mechanisms in reinforced concrete, non-destructive testing methodologies, and additive manufacturing techniques like Selective Paste Intrusion (SPI). Recent work emphasizes 3D concrete printing for structural applications, life cycle assessment of printed elements, and fundamental studies on material behavior under environmental stressors including carbonation, chloride exposure, and freeze-thaw cycles. Analysis of his 15 most recent publications (2024-2025) reveals dominant research trajectories in digital fabrication of concrete structures, particularly SPI-based additive manufacturing. His work integrates materials science with structural engineering to develop functionally graded components, assess sustainability metrics, and solve reinforcement integration challenges. Significant interdisciplinary efforts address durability issues through electrochemical monitoring, coda wave interferometry, and advanced imaging techniques for concrete microstructure characterization. Gehlen leads the Chair of Materials and Materials Testing in Civil Engineering at TUM, which operates advanced laboratories for concrete characterization including confocal laser scanning microscopy and virtual testing environments. His team actively participates in TRR 277 (Additive Manufacturing in Construction), developing fabrication-aware design methods and experimental validation protocols for novel construction technologies.
Dr. Madhushi Bandara is a Lecturer at the School of Computer Science, University of Technology Sydney (UTS), specializing in knowledge representation, complex system modeling, and data analytics. She leads the data management research stream at the UTS DigiSAS lab and is a core member of the Biomedical Data Science Laboratory within the UTS Australian Artificial Intelligence Institute. Her industry collaborations include Telstra, Cancer Australia, and Capsifi, focusing on AI integration in healthcare and finance. She coordinates the Business Information Systems major in UTS's Master of Information Technology program and convenes the Future Generation Enterprise Architecture Community of Practice. Education PhD in AI Systems Engineering, University of New South Wales (2020) BSc (Hons) in Engineering, University of Moratuwa, Sri Lanka (2015) Research Interests Madhushi's work bridges machine learning, knowledge graphs, and enterprise architecture to address challenges in data governance for SMEs, ESG metric management, and healthcare pathway analysis. Her research emphasizes translating cutting-edge AI into industry solutions through contextual domain knowledge integration. Scientific Awards UNSW-UTS Trustworthy Digital Society Scholarship Teaching & Leadership She teaches enterprise information systems, digital strategy, and AI for enterprises in UTS's online postgraduate programs. Her service roles include co-chairing tracks at the Australasian Conference on Information Systems and reviewing for Expert Systems with Applications.
Dikai Liu is a Distinguished Professor and Strategic Research Director at the University of Technology Sydney (UTS), Australia, within the School of Mechanical and Mechatronic Engineering . His work spans field robotics and human-robot collaboration (HRC) , focusing on autonomous systems for infrastructure maintenance, construction automation, and underwater operations. Key research areas: Robotics, Human-Robot Interaction, Bio-Inspired Design, Infrastructure Maintenance Recent publications highlight innovations in trust modeling for HRC, stiffness control in continuum robots, and sociotechnical frameworks for AI-driven robotic systems. His 15 most recent articles emphasize applications in bridge maintenance, construction automation, and ethical AI integration. Awards include the 2019 UTS Medal for Research Impact, ASME DED Leonardo da Vinci Award (USA), and multiple engineering excellence recognitions. His research has generated over $22M in external funding, including 13 ARC grants and industry partnerships.
Laurence Anthony is a Professor at Waseda University's School of Creative Science and Engineering, specifically affiliated with the Center for English Language Education in Science and Engineering (CELESE). He has held this position since 2009, having previously served as an Associate Professor at the same institution from 2004-2009. His academic journey began with a BSc from The University of Manchester (1991), followed by an MA (1997) and PhD (2002) from The University of Birmingham. Anthony's research centers on corpus linguistics, educational technology, and natural language processing applications in foreign language teaching. He is renowned for developing AntConc, a widely used freeware corpus analysis toolkit, along with numerous other educational software tools including AntWordProfiler, FireAnt, and ProtAnt. His work bridges linguistic theory with practical classroom applications, particularly in data-driven learning approaches for English as a Foreign Language contexts. His publication record is extensive with over 50 papers, 12,115 Google Scholar citations, and an h-index of 45. His recent work increasingly explores the intersection of corpus linguistics and artificial intelligence, examining how language models can enhance language teaching and analysis. Anthony's research has evolved from foundational corpus tool development to sophisticated applications in vocabulary profiling, writing analysis, and AI-assisted language learning. Among his notable recognitions are the Waseda University 6th e-Teaching Award (2018), the National Prize of the Japan Association of English Corpus Studies (2012), and the L'Oreal Art and Science of Color Gold Prize (2005). He serves on multiple editorial boards including for Studies in Corpus Linguistics, Journal of Asia TEFL, and Corpus Linguistics Research Journal. Anthony actively contributes to the academic community through numerous presentations at international conferences, recent ones including talks on AI integration with corpus methods at Corpus Linguistics 2025 and the LSP-Num Conference. His professional activities demonstrate ongoing engagement with both theoretical developments and practical applications in language education technology.
Andrei Y. Khodakov is a Research Director (Professor equivalent) at the Unité de Catalyse et de Chimie du Solide (UCCS), UMR CNRS 8181, affiliated with University of Lille. He serves as Coordinator of the CEMOP research team (Catalysis for Energy and Synthesis of Platform Molecules) within the Heterogeneous Catalysis Department. His academic journey began with a Master's in Chemistry from Lomonosov Moscow State University (1987), followed by a PhD from the Zelinsky Institute of Organic Chemistry (1991), and a Dr. Sci. (Habilitation) from University of Sciences and Technologies of Lille (2002). Khodakov's research focuses on heterogeneous catalysis, with particular expertise in Fischer-Tropsch synthesis, syngas conversion to fuels and platform molecules, photocatalysis, CO 2 utilization, and methane valorization. His work bridges fundamental catalyst design with practical applications for sustainable energy and chemical production. He has pioneered research on nanoconfined catalysts, mobile promoters, and single-atom catalytic systems, with significant contributions to understanding reaction mechanisms and kinetics. His publication record spans over 122 papers since 2008, with recent work emphasizing CO 2 hydrogenation, photocatalytic methane conversion, and advanced catalyst design using nanoreactors and single-atom techniques. The research shows a clear trajectory toward sustainable catalytic processes for renewable feedstocks and carbon-neutral chemical production. CNRS Prize of Excellence (2011) CNRS Ph.D. and Research Supervising Bonus (2016) Special Invited Scientist of the Brazilian Government (2013-2016) Khodakov has supervised 27 PhD students and 14 post-doctoral researchers, demonstrating strong commitment to academic training. He teaches at Centrale Lille and University of Lille's Biorefinery Master's program, and organizes international summer schools for Chinese and Brazilian students. His research is supported by 4 ANR projects, 3 European projects, and over 20 industrial contracts, reflecting both academic excellence and industrial relevance. His laboratory focuses on catalyst design for sustainable chemical production, with particular emphasis on reactor engineering, in-situ characterization techniques, and development of catalysts for renewable feedstocks conversion.
Jukka K Nurminen is a Professor of Computer Science at the University of Helsinki (since 2019) and a Research Professor at VTT. He leads the Empirical Software Engineering research group and supervises doctoral students in the Doctoral Programme in Computer Science. His career spans academia and industry, including roles as Adjunct Professor at Aalto University (part-time, 2016-2021) and Principal Scientist at VTT (2016-2019). His research focuses on efficient software systems , particularly energy-efficient software , mobile cloud computing , and data-intensive systems . Recent work addresses AI system testing , ethical decision-making in software , and quantum computing software . His publications highlight trends in quantum algorithms , machine learning for edge computing , and ethical AI . Best Paper Award (2023) Nurminen has supervised 6 PhD theses, 48 MSc theses, and 21 BSc theses. He has secured over 1 MEUR in research funding, including projects like FrameQ and EM4QS for quantum middleware. His teaching innovations include hackathons and summer schools, with excellence recognized in tenure-track evaluation (2018) and adjunct professorship (2015).
Carl-Mikael Zetterling is a Professor and Head of Department at Kungliga Tekniska Högskolan (KTH) in Stockholm, Sweden, affiliated with the School of Electrical Engineering and Computer Science (ICT) and the Electronics and Embedded Systems department. His research focuses on process technology and device design for high-temperature, high-power silicon carbide (SiC) electronics, expanding into SiC-based analog and integrated circuits. He has authored over 300 publications, including books on SiC process technology and plagiarism prevention. Dr. Zetterling has held leadership roles such as Vice Dean of the School of ICT (2013–2017) and teacher representative on KTH's faculty board. He has collaborated internationally at Stanford University, Kyoto University, and Kyoto Institute of Technology. His work addresses applications in extreme environments, including Venus exploration and fusion reactor monitoring, with a focus on radiation tolerance and thermal resilience. The 15 most recent publications highlight trends in wide bandgap semiconductors, gamma irradiation effects on SiC devices, and high-temperature integrated circuits. His articles span structural health monitoring with machine learning, novel SiC diode designs, and radiation-hardened electronics. Key contributions include advancements in self-aligned contacts, trench MOSFETs, and compact modeling for extreme conditions. While no formal awards are listed, his roles in technical program committees (TMS Electronic Materials Conference, IEEE SISC Conference) and editorial work demonstrate significant academic service. He teaches courses ranging from digital design to high-temperature electronics, overseeing degree projects in embedded systems, communication, and nanotechnology.
Brian D. Gerardot is a Professor at the School of Engineering & Physical Sciences , Heriot-Watt University , where he leads the Quantum Photonics Laboratory within the Institute of Photonics and Quantum Sciences. His research focuses on creating ultra-coherent quantum photonic devices that bridge quantum optics, condensed-matter physics, materials science, and nano-optics. BSc in Materials Science from Purdue University (1998) PhD from UC Santa Barbara (2004) His work explores semiconductor quantum dots and defect centers in diamond, utilizing advanced nano-fabrication techniques to design and characterize photonic structures. Research outputs highlight quantum technologies, entangled imaging, exciton dynamics in 2D materials, and coherence in photon emission systems. Scientific Awards include: Chair in Emerging Technologies (Royal Academy of Engineering, 2018) Wolfson Merit Award (Royal Society, 2018) ERC Consolidator Grant (2018) ERC Starting Grant (2013) Personal Research Fellowship (Royal Society of Edinburgh, 2006-2009) University Research Fellowship (Royal Society, 2009-2017) Challenging Engineering award (2011) He manages the NanoFab Disco Saw facility and has secured significant grants for quantum technologies and nanophotonic research, with collaborations spanning international institutions and datasets supporting breakthroughs in exciton-polarons, quantum imaging, and photonic coherence.
Yue Li is the Leonard Case Jr. Professor in the Department of Civil and Environmental Engineering at Case Western Reserve University. He specializes in resilient and sustainable infrastructure systems, focusing on structural reliability, probabilistic design, and climate change adaptation. His research addresses risk assessment for infrastructure under extreme events, including earthquakes, hurricanes, and climate impacts. Education: PhD in Civil Engineering, Georgia Institute of Technology, 2005 Research Interests: Dr. Li’s work integrates advanced statistical methods and data-driven approaches to enhance infrastructure resilience. Key areas include: Probabilistic modeling of structural systems Risk-informed decision-making for multi-hazard mitigation Climate change impacts on material durability and performance Asset management and lifecycle cost analysis Notable Contributions: His recent publications emphasize data-driven resilience metrics for water systems and seismic risk assessment for bridges. He has pioneered frameworks for evaluating infrastructure vulnerability under climate change, including corrosion effects and extreme weather adaptation. Awards: ABSE Outstanding Paper Award (2023) Case School of Engineering Teaching Award (2020) Nomination for John S. Diekhoff Award (2019) Leadership Roles: Dr. Li serves as Section Editor for the ASCE Journal of Structural Engineering and chairs multiple technical committees on safety and reliability. He leads initiatives to standardize multi-hazard design practices and resilience evaluation methodologies.
