Dr. Chenming Zhang is an Advanced Queensland Industry Research Fellow at the School of Civil Engineering, The University of Queensland. His research focuses on hydrological processes in coastal and terrestrial groundwater systems, with particular emphasis on evaporation-driven mass and heat transport in soils and tailings, and hydrogeochemical dynamics in aquifers and mine waste systems. Specializes in IoT-based environmental monitoring Develops numerical models for coastal aquifer dynamics Conducts field and laboratory experiments on tailings behavior Research interests span coastal hydrology, groundwater modeling, mine waste management, and environmental monitoring. He works on contamination transport, aquifer protection, and climate impacts on water systems. Recent publications analyze: Iron curtain formation in subterranean estuaries Sea water intrusion mechanisms Salinity dynamics in tidal wetlands Smart sewer monitoring systems Scientific awards include the prestigious Advanced Queensland Industry Research Fellowship. He supervises multiple PhD projects on mine waste hydrology and coastal aquifer management, with notable collaboration on: Evolution Mining's gold tailings projects ARC Discovery Projects on coastal processes Grange Resources' PAF cell instrumentation His work combines field measurements, laboratory testing, and computational modeling to address critical environmental challenges in mining and coastal zones.
Olle Eriksson is a Professor in the Department of Physics and Astronomy at Uppsala University, specifically affiliated with the Materials Theory division. His research focuses on theoretical and computational approaches to understanding magnetic materials and their properties. His primary research interests include first principles calculations of bulk materials and surfaces, with particular emphasis on magnetism and chemical bonding. His methodological expertise spans full-potential implementations of density functional theory, dynamical mean-field theory, and self-interaction correction. He also conducts calculations of finite temperature magnetism using Monte Carlo simulations and atomistic spin-dynamics simulations, as well as investigations into lattice dynamics and finite temperature effects on phase stability. Professor Eriksson's recent work demonstrates a strong focus on magnetocaloric materials for magnetic refrigeration applications, two-dimensional magnetic materials including van der Waals magnets, topological magnetic textures such as skyrmions, and computational methods for improving density functional theory. His research has significant implications for energy-efficient cooling technologies, next-generation spintronic devices, and fundamental understanding of quantum magnetic phenomena. Materials Science : Magnetocaloric materials, battery materials, 2D materials Computational Physics : Density functional theory, Monte Carlo simulations, spin dynamics Magnetism : Topological textures, chiral magnets, ultrafast dynamics His extensive publication record shows consistent contributions to high-impact journals across physics and materials science, with a notable increase in interdisciplinary work connecting computational physics with materials design for energy applications.
Bart Somers is an Associate Professor at Eindhoven University of Technology , affiliated with the Department of Mechanical Engineering . His primary affiliations include the Power & Flow Group and his own research group, Group Somers , alongside cross-cutting roles in EAISI (Eindhoven Artificial Intelligence Systems Institute) and EIRES (Eindhoven Research on Innovation and Sustainability in Energy Systems). He focuses on advancing combustion science , sustainable fuels , and engine efficiency , leveraging computational fluid dynamics (CFD) and experimental methods. His research interests span alternative fuels (hydrogen, bio-oils, biofuels), high-pressure spray combustion , and low-emission engine design . He investigates combustion optimization through CFD tools like large-eddy simulation (LES) and flamelet-generated manifolds (FGM), emphasizing fuel stratification , ignition dynamics , and emission control . His work bridges experimental diagnostics (e.g., spray visualization, OH* chemiluminescence) and numerical modeling. Academically, he teaches courses such as Thermodynamics , Clean Engines and Future Fuels , and Sustainable Vehicles , integrating practical projects into curricula. His educational activities emphasize interdisciplinary sustainability and innovation, including honors programs focused on professional development. Recent publications highlight his contributions to hydrogen injection strategies, biofuel applications in genset engines, and optimization of diesel-biofuel blends. His work aligns with global sustainability goals, addressing energy transition challenges through advanced combustion technologies.
Jerelle A. Joseph is an Assistant Professor at Princeton University , affiliated with the Department of Chemical and Biological Engineering and the Omenn-Darling Bioengineering Institute . They also hold associated faculty roles in the Department of Chemistry , Andlinger Center for Energy and the Environment , Princeton Institute for Computational Science and Engineering , and the Biophysics Graduate Program . Research Interests : The Joseph Group investigates the physicochemical principles governing biomolecular condensate formation, dissolution, and misregulation . Their work focuses on phase separation mechanisms , computational modeling of protein-RNA interactions , and engineering condensates for biomedical and sustainability applications , including therapeutic targeting of neurodegenerative diseases and design of synthetic microreactors . Scientific Awards : NIGMS MIRA (R35) Award (2024) Biophysical Society Award Lecture (2024) Chan Zuckerberg Initiative Investigator (2023) Postdoctoral Award, Biophysical Society IDP Subgroup (2022) Rising Star in Soft and Biological Matter (University of Chicago, 2020) Advising : Dr. Joseph advises graduate students including Ananya Chakravarti , Dominic Curtis , and Pablo Garcia . The group develops chemically-specific coarse-grained models using molecular dynamics , Monte Carlo sampling , and machine learning to study condensate microstructure , aging dynamics , and surface electrostatics .
Jonathan Fan is an Associate Professor at Stanford University in the Department of Electrical Engineering. His teaching portfolio includes graduate and undergraduate courses in electromagnetics, integrated circuit fabrication, and specialized studies across all quarters. EE 242: Electromagnetic Waves (Autumn) EE 312: Integrated Circuit Fabrication Laboratory (Winter) ENGR 42/EE 42: Electromagnetics and Applications (Spring) 11 independent studies and thesis courses (EE 190, EE 191, EE 300, etc.) His research focuses on nanophotonics and metasurface engineering , with particular emphasis on inverse design methodologies, machine learning -driven photonic optimization, and machine learning in electromagnetic simulation. His recent publications demonstrate a strong trend toward deep learning-enabled photonic design and high-speed optimization of complex optical systems. His work spans metamaterial fabrication , nonlocal effects in metasurfaces, and multi-functional optical devices such as spaceplates for aberration correction. Key technical contributions include physics-augmented neural networks , reparameterization techniques for design constraints, and topology-optimized metasurfaces .
Prof. Peter Müller-Buschbaum is a Full Professor and Head of the Chair of Functional Materials at the Physics Department of the Technical University of Munich (TUM). He has held this position since April 2018 and also served as Scientific Director of the Research Neutron Source Heinz Maier-Leibnitz (FRM-II) and the Heinz Maier-Leibnitz Center (MLZ) from 2018 to 2023. His leadership extends to multiple roles including Core Member of the Integrated Research Institute Munich Institute of Integrated Materials, Energy and Process Engineering (MEP) since 2021, and Head of the Renewable Energies Network (NRG) at MEP. Full Professor (W3), Head of the Chair of Functional Materials at TUM School of Natural Sciences (since 04/2018) Deputy Editor of "ACS Applied Materials & Interfaces" (since 01/2024) Supervising Professor "Electronics Laboratory" at TUM School of Natural Sciences (since 11/2023) Member of TUM Sustainability Board (since 05/2023) Core Member of MEP Institute (since 10/2021) Head of Renewable Energies Network at MEP (since 10/2021) Prof. Müller-Buschbaum's research spans energy materials for photovoltaics and battery technologies, smart responsive materials that adapt to environmental stimuli, and nanocomposite materials with tailored properties. His group employs advanced scattering techniques to characterize materials at the nanoscale, providing insights into structure-property relationships critical for developing next-generation energy technologies. His extensive publication record demonstrates particular expertise in perovskite solar cells, lithium-ion battery technologies, and polymer-based functional materials, with recent work focusing on improving device stability and efficiency while understanding fundamental degradation mechanisms. His publications reveal a strong emphasis on energy conversion and storage technologies, with particular attention to interfacial engineering in both photovoltaic and battery systems. The research shows sophisticated integration of materials synthesis, advanced characterization, and device engineering to address critical challenges in renewable energy technologies. His work bridges fundamental science with practical applications through collaborations with major international research facilities. Scientific Service and Recognition Member of the Council of the Cluster of Excellence "ORIGINS" (since 01/2019) Spokesperson of the Chemical Physics and Polymer Physics Association of DPG (03/2021-10/2022) Member of the European Spallation Source Scientific Advisory Panel (since 03/2011) German representative at the European Polymer Federation for polymer physics (since 03/2011) Chairman of the Keylab "TUM.solar" in the Bavarian research project "Solar Technologies Go Hybrid" (since 03/2012) Prof. Müller-Buschbaum actively contributes to academic community through editorial work, having served as Associate Editor (2012-2022), Executive Editor (2023), and currently Deputy Editor (2024-present) of "ACS Applied Materials & Interfaces". He maintains strong international collaborations with synchrotron and neutron facilities worldwide, reflecting his expertise in advanced materials characterization techniques essential for cutting-edge materials research.
Michal Lipson serves as the Eugene Higgins Professor of Electrical Engineering and Professor of Applied Physics at Columbia University's Fu Foundation School of Engineering and Applied Science. Elected to both the National Academy of Engineering and National Academy of Sciences, she pioneered critical building blocks in silicon photonics that have transformed the field, with over 50,000 related publications annually. Her research has generated more than 250 scientific publications and 45 issued patents. Lipson's research focuses on nanophotonics and silicon photonics, where she demonstrated the ability to tailor electro-optic properties of silicon in landmark 2004 and 2005 Nature papers. Her work has enabled the development of photonic devices and circuits that now form the foundation of over 1,000 papers published yearly. She investigates novel optical phenomena while developing practical applications that address major bottlenecks in microelectronics. Her research spans fundamental physics to practical device implementation, with particular emphasis on integrated photonic systems. Analysis of her recent publications reveals a strategic expansion from foundational silicon photonics into emerging applications including quantum information processing, machine learning acceleration, biomedical sensing, and topological photonics. While maintaining core expertise in silicon-based devices, her work increasingly incorporates 2D materials, heterogeneous integration, and novel optical phenomena to push performance boundaries. The research demonstrates consistent progression from fundamental device physics to system-level implementations with practical applications. National Academy of Engineering (2025) National Academy of Sciences MacArthur Fellowship Blavatnik Award Optica's R.W. Wood Prize IEEE Photonics Award John Tyndall Award NAS Comstock Prize in Physics Thomson Reuters Top 1% Highly Cited Researcher (annually since 2014) Professor Lipson has mentored an exceptional research group, graduating 40 PhD students and 2 MS students, with numerous postdocs and visiting researchers. Her alumni occupy prominent positions including professorships at major universities (Rochester, Ottawa, UNICAMP, Johns Hopkins), leadership roles at Intel, Bell Labs, and startups she co-founded (HyperLight, Voyant Photonics). Her laboratory has received substantial research funding supporting cutting-edge work in nanofabrication, optical characterization, and device development. Current research directions include quantum photonics, AI-accelerated optical systems, and novel materials integration. The Lipson Research Group operates state-of-the-art facilities for nanophotonic device design, fabrication, and characterization. The team comprises principal investigators, postdoctoral researchers, PhD students, and administrative staff working collaboratively across disciplines including electrical engineering, materials science, physics, and applied physics. The group maintains strong industry partnerships while pursuing fundamental scientific advances in light-matter interactions at the nanoscale.
Ruomeng Huang is an Associate Professor in the Sustainable Electronics Technologies group within the School of Electronics and Computer Science at the University of Southampton. He holds a PhD in nanoscale memristors (2015) and has been a faculty member since 2018, advancing to his current rank in 2023. His research focuses on neuromorphic computing using memristive materials, machine learning-driven nanophotonics, and energy harvesting devices. Huang has published over 100 peer-reviewed articles and leads six UKRI-funded projects, including the EPSRC-funded ADEPT initiative. Education: BSc Physics (2008), MEd (2009) in China; MSc Nanoelectronics & Nanotechnology (2010), PhD in nanoscale memristors (2015) at the University of Southampton. Research Interests : - Neuromorphic computing via novel memristor devices (SiC, mesoporous silica, chalcogenides) - Thermoelectric materials (SnSe, Bi₂Te₃) and AI-optimized generators - Deep learning for structural color design Teaching : Leads MSc programs in Electronic Engineering and Micro/Nanotechnology. Teaches undergraduate/graduate modules including semiconductor devices, nanoelectronics, and industrial studies. Grants & Projects : - EPSRC Doctoral Prize Fellowship (2015) - Co-Investigator on £6.33M EPSRC ADEPT grant (electrodeposition innovations) - PI on multiple thermoelectric and neuromorphic computing projects Students : Currently supervising 7 PhD students. Notable advisees include Aiden Graham, Jiale Zeng, and Dongkai Guo. Labs/Teams : Heads the Sustainable Electronics Technologies group, collaborating with interdisciplinary teams in nanomaterials and energy systems.
Mohsen Habibi is an Assistant Professor at the University of California, Davis, leading the Advanced Manufacturing Lab (AML). His research focuses on Additive Manufacturing (AM), particularly pioneering Direct Sound Printing (DSP), an ultrasound-based technique for 3D printing via sonochemistry and thermochemistry. His work has been recognized with the David Dornfeld Manufacturing Vision Award (2024), NSF Blue Sky Competition win, and inclusion in Quebec Science magazine's top 10 discoveries of 2022. Before academia, Dr. Habibi worked as a senior manufacturing engineer at General Motors and mechanical designer at MDA (a space technology firm). He held roles as a research associate at Concordia University and a postdoctoral fellow at the University of British Columbia, collaborating with industries like Pratt & Whitney and MAL Inc. His research bridges acoustic physics, materials science, and biomedical engineering, emphasizing non-invasive applications such as in-situ tissue printing and remote polymerization. Research Highlights: His lab explores holographic DSP for complex patterns, minimally invasive medical applications, and sustainable 3D printing systems for underserved regions. Key areas include metamaterials, acoustic holography, and energy-efficient manufacturing. Awards & Recognition: David Dornfeld Manufacturing Vision Award (2024) NSF Blue Sky Competition Winner Quebec Science Magazine's Top 10 Discoveries (2022) Altmetric 99th percentile for DSP publication impact Lab Activities: The AML develops technologies like Remote Distance Printing (RDP) for inaccessible locations and Holographic DSP (HDSP) for multi-pattern fabrication. Projects include acoustic-matter interaction studies and CAD/CAM process optimization.
Theresa Raimondo is the Manning Assistant Professor of Engineering at Brown University, with a secondary appointment in the Division of Biology and Medicine. She joined the Brown Engineering faculty in January 2024 after completing her postdoctoral training at MIT's Koch Institute. Dr. Raimondo leads the Raimondo Research Lab, which focuses on chemically modifying RNA and designing nanoparticles for therapeutic delivery to the body, an immunotherapy concept that holds immense promise in the field of immunoengineering. Her educational background includes: PhD in Engineering Sciences – Bioengineering from Harvard University (2019) MEng from Harvard University (2019) Sc.B. in Chemical and Biochemical Engineering from Brown University (2011) Dr. Raimondo's research is broadly focused on the design of targeted drug-delivery vectors and novel RNA-based therapeutics for applications in cancer, immunotherapy, and tissue regeneration. Her work primarily centers on developing novel lipid nanoparticles (LNPs) for RNA-based therapies, contributing to adjuvanted mRNA-based vaccines and siRNA-based cancer immunotherapies. By optimizing LNP formulation and modulating RNA constructs, she seeks to understand how RNA-LNPs modulate immunity and develop new therapeutic approaches. Her expertise spans biomaterials, drug delivery, biomolecular engineering, nanomedicine, tissue engineering, and regenerative medicine. Analysis of Dr. Raimondo's recent publications reveals a strong focus on RNA delivery systems and lipid nanoparticle technology. Her work spans from fundamental studies on nanoparticle design to applications in cancer immunotherapy, vaccine development, and tissue regeneration. A significant portion of her research involves optimizing lipid formulations for improved mRNA delivery and exploring how these systems interact with the immune system. Her publications demonstrate a trajectory from basic biomaterials research to increasingly translational work with therapeutic applications. Dr. Raimondo has received numerous prestigious awards: 2025 NAE Symposium selection (Grainger Foundation Frontiers of Engineering) 2025 appointment to the inaugural Early Career Board of ACS Applied Bio Materials 2024 selection as MIT Faculty Founder Initiative finalist 2022 Convergence Scholar fellowship from MIT's Marble Center for Cancer Nanomedicine National Science Foundation graduate research fellowship Harvard's Smith family graduate fellowship Dr. Raimondo is actively involved in mentoring students through courses including ENGN 0931L - Biomedical Engineering Design and Innovation II, ENGN 1490 - Biomaterials, and ENGN 1931L - Biomedical Engineering Design and Innovation II. Her research program is supported by various grants, though specific funding sources aren't detailed in the provided text. The Raimondo Research Lab represents a dynamic environment where engineering principles are applied to solve complex biological challenges in drug delivery and regenerative medicine. The Raimondo Research Lab at Brown University serves as a hub for innovation in RNA delivery and biomaterials design. The lab brings together expertise in chemical engineering, molecular biology, and immunology to develop next-generation therapeutic platforms. Current research directions include optimizing lipid nanoparticle formulations, exploring novel RNA modifications, and investigating immune responses to RNA therapeutics across various disease contexts.
Rafael Brüschweiler is a Professor and Ohio Research Scholar at The Ohio State University, holding joint appointments in the Department of Chemistry and Biochemistry and the Department of Biological Chemistry and Pharmacology. He serves as the NMR Executive Director for the Ohio State Campus Chemical Instrument Center and the NSF-funded National Gateway Ultrahigh Field NMR Center. His research focuses on biophysical chemistry, analytical chemistry, and computational modeling, emphasizing protein dynamics, metabolomics, and NMR method development. He received his Ph.D. from ETH Zurich and completed a postdoc at the Scripps Research Institute. His research integrates experimental NMR, molecular dynamics simulations, and machine learning to study protein structure-function relationships, metabolic pathways, and biomolecular interactions. Key areas include the dynamics of oncogenic K-Ras, glucokinase glucose sensing, and nanoparticle-assisted NMR techniques. His work is funded by the NIH and NSF, with applications in biomedical diagnostics and drug discovery. Dr. Brüschweiler leads a multidisciplinary lab training students and postdocs in NMR spectroscopy, computational methods, and metabolomics. His lab developed tools like DEEP picker and COLMAR for automated NMR data analysis, contributing to the SECIM metabolomics center. He actively recruits students interested in protein dynamics, computational modeling, or metabolomics.
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.
Vasant Dhar is the Robert A Miller Professor of Business and Professor of Data Science at the Leonard N. Stern School of Business at New York University. He serves as Director of Industry Relations and specializes in Technology, Operations, and Statistics. Joining Stern in 1983, Professor Dhar has established himself as a leading expert in artificial intelligence, data science, and financial technology. Professor Dhar's educational background includes: Ph.D. in Artificial Intelligence from the University of Pittsburgh (1984) M.Phil. from the University of Pittsburgh (1982) B.Tech. in Chemical Engineering from the Indian Institute of Technology, Delhi (1978) His research focuses on how risk influences our trust in AI systems, demonstrating the existence of an "automation frontier" that expresses a tradeoff between how often machines will be wrong and the consequences of their errors. Professor Dhar examines how innovations such as Artificial Intelligence impact our lives, and how we can create technology and policy for a better future in a world of increasingly intelligent machines. His work spans financial applications of AI, where he was among the first to bring machine learning to Wall Street in the 1990s, founding the machine-learning-based hedge fund SCT Capital Management. Professor Dhar's recent publications reveal a strong focus on the practical applications and societal implications of AI. His work addresses critical issues including AI reliability in financial document analysis, the governance of AI companies, ethical considerations in biometric payments, and the evolving relationship between humans and increasingly intelligent machines. His research demonstrates how AI is transforming various sectors while raising important questions about trust, accountability, and the future of work. Among his notable recognitions is the Robert A Miller Professorship, an endowed chair position at NYU Stern. His research has been funded by grants from industry and government agencies such as the National Science Foundation. Professor Dhar teaches courses on Systematic Investing, Data Science, Prediction, and Tech Innovation. He has written over 100 research articles and is the host of the "Brave New World" podcast, which explores how technology and virtualization in the post-COVID era is transforming humanity. He publishes fortnightly at vasantdhar.substack.com and is a frequent speaker in academic and industrial forums.
Rohit Kannan is an Assistant Professor in the Grado Department of Industrial and Systems Engineering at Virginia Tech. He holds a Ph.D. and M.S. in Chemical Engineering from MIT and a B.Tech. from IIT Madras. His research focuses on integrating machine learning with global optimization and optimization under uncertainty, emphasizing energy systems applications. Previous roles include postdoc positions at Los Alamos National Laboratory and the Wisconsin Institute for Discovery. Education: Ph.D., Chemical Engineering, Massachusetts Institute of Technology, 2018 M.S., Chemical Engineering Practice, MIT, 2014 B.Tech., Chemical Engineering, IIT Madras, 2012 Research Interests: Global optimization, optimization under uncertainty, computational optimization, energy systems, and machine learning integration. Recent Highlights: Recipient of the Excellence in Teaching Spotlight Award (2024) Lead researcher in stochastic optimization and energy systems (e.g., hybrid polygeneration systems) Developed algorithms for chance-constrained nonlinear programs and distributionally robust optimization Service & Leadership: Elected Vice-Chair of Global Optimization, INFORMS Optimization Society (2025–2026) Reviewer for top journals like Operations Research and Mathematical Programming Advisor to ISE InclusiveVT and Graduate Admissions Committee Labs & Collaborations: Directs a research group advancing optimization and machine learning for energy and engineering systems. Active in interdisciplinary projects with LANL and UW-Madison.
James M. Piret is a Professor at the University of British Columbia (UBC), affiliated with the School of Biomedical Engineering and the Michael Smith Laboratories. He holds a Sc.D. from MIT (1989), an S.M. from MIT (1986), and an A.B. from Harvard College (1981). His research focuses on bioprocessing, biomedical engineering, and cell therapy biotechnology, with emphasis on optimizing therapeutic cell production and biomanufacturing processes. Education : Sc.D. in Chemical Engineering, Massachusetts Institute of Technology (1989) S.M. in Chemical Engineering, Massachusetts Institute of Technology (1986) A.B. in Chemistry, Harvard College (1981) Professor Piret’s research integrates bioreactor engineering, Raman spectroscopy, and data analytics to advance cell-based therapies for diseases like cancer and diabetes. Collaborations with stem cell biologists (e.g., Drs. Kieffer and Levings) and engineers (Drs. Turner and Gopaluni) drive innovations in bioprocess optimization and device development. His lab emphasizes multidisciplinary approaches to accelerate biotechnology production processes and cell therapy manufacturing. Awards : William F. Meggers Award (2022) R.S. Jane Memorial Award (2015) Cell Culture Engineering Award (2012) Fellow, Chemical Institute of Canada (2004) His work includes developing novel methodologies for CHO cell glycosylation engineering, optimizing fed-batch bioreactor systems, and advancing Raman spectroscopy techniques for real-time cell analysis. The lab actively recruits motivated graduate and postdoctoral researchers to tackle high-impact challenges in biomedical and chemical engineering.
