Buyung Kosasih is a Professor in the School of Mechanical, Materials, Mechatronic and Biomedical Engineering at the University of Wollongong. He has held this position since 2000 and focuses on teaching and research in mechanical engineering, including Machine Dynamics, Finite Element Methods, and Renewable Energy Technology. His research spans fluid dynamics in industrial processes, renewable energy systems, and aqueous lubrication. Key projects include 3D-printed surfboard fin optimization and steel coating dynamics. Research interests emphasize experimental and computational fluid dynamics, particularly in renewable energy turbines and tribological systems. Notable awards include the 2013 Outstanding Contribution to Teaching and Learning Award. He has supervised numerous students and led over 20 funded projects, including ARC grants for steel innovation and renewable energy. Collaborative work includes the Steel Research Hub and HVAC/cool roof efficiency studies.
Dr. Vikas Srivastava is an Associate Professor of Engineering and Director of the Graduate Program in Biomedical Engineering at Brown University's School of Engineering. His research focuses on solid mechanics, continuum biomechanics, and cell mechanics, with applications in materials under extreme environments and biomedical science. He leads the Srivastava Lab for Solid Mechanics and Biomechanics, which integrates computational models with experimental techniques to address interdisciplinary challenges. Dr. Srivastava holds a Ph.D. in Mechanical Engineering from MIT (2010) and previously held senior roles at ExxonMobil, including leadership in materials mechanics and deepwater drilling engineering. His academic career at Brown began in 2018, during which he has directed over 15 graduate students and secured notable funding. His research interests span mechanobiology, hydrogel-based drug delivery systems, AI-driven predictive modeling, and biomaterial innovations for cancer therapies. He has pioneered physics-informed neural networks for material characterization and developed novel hydrogels to enhance chemotherapy efficacy. Recent articles highlight advancements in polymer fracture modeling, machine learning for non-destructive evaluation, and predictive epidemiological modeling for pandemics. Dr. Srivastava has received the Dean’s Award in Bioengineering and was promoted to tenured Associate Professor in 2023. He actively mentors students through grants like the NSF Graduate Research Fellowship and leads initiatives in biomedical technology translation. The Srivastava Lab collaborates extensively across engineering, biology, and medicine to advance translational research in materials science and clinical applications.
Michael Levin is a Vannevar Bush Professor and Distinguished Professor at Tufts University, affiliated with the School of Arts and Sciences (Department of Biology) and School of Engineering (Biomedical Engineering). His research focuses on bioelectricity, developmental biology, and collective intelligence. He leads the Allen Discovery Center and the Tufts Center for Developmental and Regenerative Biology. Education: PhD in Genetics from Harvard Medical School (1996); BS in Computer Science and Biology from Tufts University (1992). Research Interests: Integrates developmental biology, computer science, and cognitive science to study morphogenesis, regeneration, and cancer. Explores bioelectric signaling, synthetic organisms, and AI-driven discovery. Key areas include regenerative medicine, cancer reprogramming, and collective intelligence in biological systems. Publications: Over 600 articles, with recent work on xenobots, neuroevolution, and bioelectric therapies. Themes include bioelectric control of form, AI in biology, and collective intelligence. Awards: INNS Donald O. Hebb Award, AAAS Fellow, and Vox Future Perfect 50 List recognition. Frequently invited to speak at conferences on biology, AI, and consciousness. Advising & Labs: Mentored numerous postdocs and students, including pioneers in bioelectricity and synthetic biology. Lab focuses on interdisciplinary approaches to biological pattern formation and regeneration.
Jessica Rosenholm is a Professor at the Faculty of Science and Engineering, Department of Pharmacy at Åbo Akademi University. Her research focuses on drug delivery systems, nanomedicine, and biomaterials engineering. She holds a D.Sc.(Tech.) and has authored over 200 publications. Key research areas include mesoporous silica nanoparticles, 3D bioprinting, and antimicrobial resistance solutions. Her work contributes to UN Sustainable Development Goals, particularly in advancing health technologies. Notable achievements include the Akzo Nobel Nordic Research Prize 2009 and the Knight, First Class, of the Order of the White Rose of Finland (2022). She leads projects like the MADNESS Centre of Excellence, exploring materials-driven solutions against antimicrobial resistance. Education: Doctor of Science (Technology) Research Interests: Nanoformulations, biomedical imaging, microfluidics, and tissue engineering. Recent articles highlight innovations in programmable nanocomposites for hearing loss treatment, microfluidic assembly of nanostructures, and 3D printing of drug delivery systems. Awards: ÅAU Chancellor’s Prize (2013), Forskarpriset ur Harry Elvings legat (2009) Grants: Projects funded by EU, Finnish Research Council, and Sigrid Jusélius Foundation. Labs/Teams: BioNanoMaterials group explores cutting-edge technologies like nanomedical agents and microfluidics. Current projects include the NAP4DIVE initiative for blood-brain barrier drug delivery.
Adam Marcus is an Associate Professor of Architecture at Tulane University School of Architecture and serves as Research Director of the Center on Climate Change and Urbanism. He directs Variable Projects, an award-winning design and research studio operating at the intersection of architecture, computation, and fabrication, and is a partner in Futures North, a public art collaborative dedicated to exploring data aesthetics. His educational background includes: Master of Architecture from Columbia University Bachelor of Arts from Brown University Adam's research focuses on critical approaches to design computation, digital fabrication, and robotics, exploring how these technologies enable new modes of ecological, material, and public engagement. His work particularly emphasizes climate adaptation, buoyant ecologies for sea level rise, computational representation, and multispecies architecture. He integrates these interests through practical design-build projects that address ecological challenges while advancing architectural representation and fabrication techniques. His recent publications demonstrate a strong emphasis on computational approaches to architectural representation and ecological design. The works consistently explore the intersection of digital technologies with ecological imperatives, particularly focusing on climate adaptation strategies, multispecies collaborations, and innovative drawing protocols that bridge analog and computational paradigms. His book 'Drawing Codes' represents a significant contribution to rethinking architectural drawing in the computational age. Notable awards include: Selected as one of the '30 Most Admired Educators' by Design Intelligence (2013) Recipient of the New Faculty Teaching Award from the Association of Collegiate Schools of Architecture (2016) Adam has served on ACADIA's Board of Directors from 2015 to 2021 and currently serves on the editorial board of the International Journal of Architectural Computing. His teaching at Tulane includes design studios and courses in computational design and digital fabrication with ecological applications, building on his decade of experience at California College of the Arts where he co-founded the Architectural Ecologies Lab. He leads research initiatives through Tulane's Center on Climate Change and Urbanism, developing practical design solutions for ecological challenges, particularly those related to climate change and sea level rise. His Buoyant Ecologies Float Lab project exemplifies this approach, creating 'optimized upside-down benthos for sea level rise adaptation' that has received attention from major media outlets including Smithsonian Magazine and Architectural Record.
Dr. Alamgir Karim is the Dow Chair and Welch Foundation Professor at the University of Houston, leading the International Polymer & Soft Matter Center (IPSMC) and the Doctoral Materials Program. His research focuses on polymer nanotechnology, thin films, and interfaces for energy, sustainability, and health applications. He holds a Ph.D. in Physics from Northwestern University and a B.S. from St. Stephen's College, Delhi. Key contributions include polymer nanocomposites, block copolymer thin films, and graphene oxide membranes for desalination. He is a Fellow of the American Physical Society and AAAS, and a Keck Foundation Award recipient. Research interests span polymer nanotechnology, dielectric materials, and sustainable nanocomposites. Recent work explores MXene-based biomedical composites, CO₂ capture membranes, and high-energy-density dielectrics. His lab develops functional materials for energy storage, environmental remediation, and biomedicine. Education: Ph.D., Physics (Northwestern University, 1991); B.S., Physics (St. Stephen's College, 1985) Leadership: Director of IPSMC; former Goodyear Chair Professor at University of Akron Awards: AAAS Fellowship, APS Fellowship, Keck Foundation Award Advances in block copolymer self-assembly and nanocomposite design have enabled scalable filtration membranes and high-performance dielectrics. His group collaborates on protocell models and sustainable materials processing.
Mathias Niepert is a Professor at the Institute for Artificial Intelligence within the Faculty of Computer Science, Electrical Engineering and Information Technology at the University of Stuttgart. His research focuses on advancing machine learning techniques with applications in scientific computing, graph neural networks, and medical imaging. He is particularly known for contributions to physics-informed neural networks, equivariant models, and graph learning frameworks. Key research areas include: Scientific Machine Learning for PDEs and molecular modeling Graph neural networks and their theoretical limitations Medical vision-language models and multimodal learning Efficient neural network architectures (transformers, FNOs) Domain knowledge integration in deep learning His work often bridges theoretical foundations with practical applications, as evidenced by extensive publications (2018–2025) on topics like adaptive message passing, equivariant networks, and medical imaging systems. He has contributed to benchmark development through initiatives like PDEBench and pioneered methods for equivariant diffusion models and molecular representation learning. His current projects emphasize: Improving generalization in Fourier Neural Operators Addressing oversmoothing in graph networks Combining physics principles with neural architectures Medical AI applications through multimodal fusion
Dr. Markus Brinkmann is an Associate Professor in the School of Environment and Sustainability at the University of Saskatchewan, Canada, and Director of the Toxicology Centre. He holds the Centennial Enhancement Chair in Mechanistic Environmental Toxicology. His research focuses on exposure and risk assessment modeling, toxicokinetic modeling, and aquatic ecotoxicology, with an emphasis on understanding contaminant effects under realistic environmental conditions. Affiliations: Associate Professor, University of Saskatchewan Director, Toxicology Centre Member, Global Water Futures Program Member, Global Institute for Water Security Education: Ph.D. (Biology) - RWTH Aachen University, Germany (2015) M.Sc. (Ecotoxicology) - RWTH Aachen University, Germany (2011) B.Sc. (Biology) - RWTH Aachen University, Germany (2009) Research Interests: Dr. Brinkmann develops computational models to predict contaminant uptake, effects, and cross-species extrapolation. His work integrates toxicology, environmental chemistry, and hydrology to address challenges like flood-related contaminant remobilization and dioxin-like compound toxicity. Key areas include: Mechanistic toxicology of emerging contaminants (e.g., 6PPD-quinone, PFAS alternatives) Sediment toxicity and bioavailability Wastewater surveillance for public health monitoring Grant Highlights: Global Water Futures Program (2018-2023): Hydrological-exposure models for environmental risk assessment Genome Canada (2016-2020): EcoToxChip for chemical prioritization Banting Postdoctoral Fellowship (2016-2018) Awards: Friedrich-Wilhelm-Award (2016) SETAC GLB Young Scientists Award (2016 PhD, 2012 MSc) Borchers medal (2016) Leadership: He advises on strategic research partnerships between Canada and Germany and collaborates globally on projects like the EcoToxChip and Project House Water . His work bridges academic research with practical environmental management solutions.
Carl Wennerlind is a Professor of History at Barnard College, specializing in early modern European history with a focus on intellectual history and political economy. His research explores the historical development of monetary theory, credit systems, and the interplay between economic ideology and natural resource management. Specializes in 17th-18th century capitalist systems Examines money as a cultural and philosophical artifact Investigates Sweden's economic modernization efforts Currently researching Linnaean natural science link to capitalism His publications span journals like Journal of Political Economy , American Historical Review and edited volumes. Recent work examines material capitalism history (2024) and scarcity-climate crisis connections (2023). Key themes include financial revolution dynamics, economic semiotics, and natural knowledge's role in empire-building. Scientific awards include: Warren Samuels Prize (2012) History of Economics Society Best Article Prize (2006) European Society for the History of Economic Thought award (2006) Research funding includes NEH, ACLS, and Swedish foundations. Courses cover topics ranging from foundational European history surveys to specialized seminars on capitalism, money history, and political economy debates. Current projects include a monograph on Swedish political economy and a comprehensive history of capitalism discourse.
Orlando Rojas is a Professor at the University of British Columbia (UBC), holding joint appointments in the Departments of Chemical and Biological Engineering, Chemistry, and Wood Science. He leads the Biobased Colloids and Materials (BiCMat) research group and directs the Bioproducts Institute . His research focuses on sustainable development through renewable materials, including nanopolysaccharides, bacterial nanocellulose, lignins, and multiphase systems. Rojas has advised over 50 PhD students and 40+ MS students, with a h-index of 90 (Google Scholar). Key Roles/Positions : Canada Excellence Research Chair in Renewable Materials Adjunct Professor at NC State University (USA) and Dalian Polytechnic University (China) Director of FinnCERES Flagship (Finland) Research Interests : Development of bio-based materials for energy, healthcare, and environmental applications. Key areas include nanocellulose functionalization, lignin valorization, and bioinspired materials. His work integrates colloidal science, multiphase systems, and sustainable manufacturing. Grants & Awards : ERC Advanced Grant and Horizon H2020 funding 2013 ACS Fellow, 2015 Tappi Nanotechnology Award First Latin-American recipient of the Anselme Payen Award (ACS) Labs & Collaborations : Active partnerships with Aalto University (Finland) and institutions globally. Leads the BiCMat group spanning UBC and FinnCERES, focusing on bio-based materials and sustainable technologies.
Asst. Prof. OU Pengfei is an Assistant Professor and NUS Presidential Young Professor in the Department of Chemistry at the National University of Singapore, Faculty of Science. He leads the AI for Chemistry (AI4Chem) research group, focusing on computational catalysis, machine learning, and materials science. Previously, he was a Research Associate at Northwestern University and a Postdoctoral Fellow at the University of Toronto under Prof. Edward H. Sargent, and earned his Ph.D. from McGill University. Education: Ph.D., McGill University, 2020 M.Eng., Central South University, 2015 B.Eng., Central South University, 2012 Research interests include catalyst design for electrochemical reactions using ab initio DFT, molecular dynamics simulations, and AI-driven methods. He develops dynamic simulations of chemical processes under reaction conditions and machine learning tools for accelerated catalyst discovery. His work addresses challenges in energy and environmental applications such as CO2 reduction and hydrogen evolution. Notable awards include the NUS Presidential Young Professorship (2024), Climate Positive Energy Postdoctoral Fellowship (2021), and Chinese Government Award for Outstanding Self-Financed Students Abroad (2020). Labs/Teams: The AI4Chem group integrates theory-guided and data-driven approaches to advance computational catalysis, with three core research directions: (1) reaction mechanism exploration and catalyst optimization, (2) dynamic structure-performance relationships under reaction conditions, and (3) machine learning algorithms for high-throughput screening.
Siyu Tang is an Assistant Professor in the Department of Computer Science at ETH Zürich, where she leads the Computer Vision and Learning Group (VLG) at the Institute of Visual Computing. Her research focuses on computational models for human perception and digitalization through computer vision and machine learning. Her educational background includes: PhD in Computer Science, Max Planck Institute for Informatics (2017), supervised by Prof. Bernt Schiele Master of Science in Media Informatics, RWTH Aachen University Bachelor of Science in Computer Science, Zhejiang University, China Dr. Tang specializes in human-centric computer vision, developing statistical models for motion analysis, pose estimation, and digital human creation. Her work integrates machine learning with optimization techniques to enable machines to interpret human activities from visual data, with applications spanning virtual reality, healthcare, and human-computer interaction. Key research thrusts include generative models for content creation, egocentric vision, and human motion synthesis. Her recent publications (2024-2025) demonstrate intense focus on 3D human modeling and neural rendering, with Gaussian splatting emerging as a dominant technique for efficient avatar creation and scene reconstruction. Significant themes include text-driven motion synthesis using diffusion models, relightable avatars, surgical training applications, and egocentric multimodal pretraining. This work bridges computer vision, graphics, and machine learning to advance human digitalization. No scientific awards were mentioned in the provided text. Dr. Tang leads the VLG research group at ETH Zürich, mentoring PhD and Master's students in human-centric AI. She previously secured an early career research grant from the Max Planck Institute for Intelligent Systems to establish her independent research program. Her group actively pursues funding for projects in human motion analysis, 3D reconstruction, and generative modeling, with strong industry and clinical collaborations. The Computer Vision and Learning Group (VLG) operates within ETH's Institute of Visual Computing, maintaining dedicated facilities for motion capture, 3D scanning, and high-performance computing. The team collaborates internationally with institutions like the Max Planck Society and focuses on scalable solutions for real-world human digitalization challenges, including surgical training systems and immersive virtual environments.
Lerrel Pinto is an Assistant Professor of Computer Science at New York University's Courant Institute, where he leads the General-purpose Robotics and AI Lab (GRAIL). His research focuses on enabling robots to generalize and adapt in unstructured environments through advancements in robot learning, decision making, and multimodal sensing. Before joining NYU, he completed a postdoc at UC Berkeley, a PhD in Robotics at Carnegie Mellon University, and an undergraduate degree in Mechanical Engineering at IIT Guwahati. Key research areas include large-scale robot learning, representation learning for sensory data, reinforcement learning for adaptability, and open-source robotics hardware. Notable achievements include the Sloan Fellowship (2025), NSF CAREER Award (2024), and Best Paper Awards at multiple robotics conferences. Pinto's lab has developed influential systems such as the AnySkin tactile sensing framework and the OPEN TEACH teleoperation system. Education highlights include a PhD from CMU (2019) under Abhinav Gupta, a postdoctoral stint with Alexei Efros and Pieter Abbeel at Berkeley, and undergraduate studies at IIT Guwahati. He has authored over 65 publications in top conferences like ICRA, NeurIPS, and CVPR. Pinto teaches courses on robotics, reinforcement learning, and AI at NYU. His service contributions include roles on program committees for ICML, NeurIPS, and IROS, as well as organizing workshops on topics like Dexterous Manipulation and Vision-Language Models for Robotics. His team actively collaborates through the GRAIL lab, with current projects exploring tactile sensing, zero-shot policy deployment, and multimodal robot learning systems. Ongoing research emphasizes bridging the gap between human and robotic dexterity through novel reward structures and adaptive control frameworks.
Ming Cao is a Full Professor at the University of Groningen (Netherlands), holding positions in the Department of Discrete Technology and Production Automation, the Engineering and Technology Institute Groningen, and serving as Chair of the Jantina Tammes School of Digital Society, Technology and AI. His academic roles include Director of the Jantina Tammes School and membership in prestigious organizations such as the International Federation of Automatic Control (IFAC) and the European Commission’s DG CNECT. Cao’s research focuses on multi-agent systems, autonomous robotics, complex networks, and cooperative control, with applications in robotics, epidemic modeling, and biomimetic sensors. Education: PostDoc in Mechanical Engineering from Princeton University (2008), PhD in Electrical Engineering from Yale University (2007). Research Interests: Multi-agent systems, distributed decision-making, cooperative control, robotic teams, seal whisker-inspired flow sensing, and privacy-preserving control systems. Recent Trends in Articles: Recent work emphasizes co-evolutionary dynamics in social-technical systems, privacy in control systems, and biomimetic robotics. Key topics include feedback mechanisms in cooperation, hypergraph-based epidemic models, and seal whisker mechanics for underwater sensing. Awards: European Control Award (2016), Manfred Thoma Medal (2017), ERC Grant (2012). Grants: Vidi Grant from NWO (2015) for agent coordination research. Labs/Teams: Jan C. Willems Center for Systems and Control, Research Center for Data Science and Systems Complexity (DSSC). Active in editorial roles for journals like Artificial Life and Robotics and the SIAM Journal on Control and Optimization .
Linda J. Harris, Ph.D., is a Distinguished Professor of Cooperative Extension in Microbial Food Safety at the University of California, Davis, within the Department of Food Science and Technology. She served as Department Chair from 2016 to 2021. Her research focuses on microbial food safety, particularly in fresh produce and tree nuts, emphasizing pathogen behavior, antimicrobial treatments, and standard microbiological methods validation. She collaborates with food producers, processors, and government agencies to address food safety challenges. Dr. Harris earned her Ph.D. in Food Science from North Carolina State University in 1991. Her work integrates laboratory studies with extension activities to ensure practical applications in food safety. Key areas include evaluating pathogen survival on produce, developing sanitation protocols, and assessing risks associated with low-moisture foods. Her research trends highlight advancements in pathogen detection (e.g., MALDI-TOF technology), contamination prevention in postharvest handling, and consumer practices affecting food safety (e.g., homemade nut-based products). Recent articles address Salmonella and Listeria survival on produce, irrigation impacts on pathogens, and validation of pathogen reduction processes. Awards: 2021 AAAS Fellow 2018 Institute of Food Technologists Fellow 2004 Elmer Marth Educator Award Her advising and grants focus on low-moisture food safety, extension education, and industry partnerships. She leads initiatives like the Scientific Integrity Consortium and collaborates on national food safety guidelines. Dr. Harris is affiliated with the Robert Mondavi Institute for Wine and Food Science at UC Davis.
