Complex Fluids Professors and Supervisors | ApplySharif

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Ishan SharmaView profile

Professor

Indian Institute of Technology Kanpur (IITK)India

Ishan Sharma is a Professor in the Department of Mechanical Engineering at the Indian Institute of Technology Kanpur (IIT Kanpur), specializing in Mechanics and Applied Mathematics. His research focuses on granular materials, planetary science, contact mechanics and adhesion, soft materials, dynamics, structural vibrations, wave propagation, stability, and fluid-structure interaction. Dr. Sharma's research interests include modeling granular systems for geophysical and industrial applications, with specific emphasis on dynamics of granular minor planets and segregation in granular mixtures. His work bridges theoretical mechanics with practical applications in both space science and engineering contexts. The research spans multiple disciplines, connecting planetary science, materials science, and mechanical engineering through mathematical modeling and computational approaches. His scholarly contributions demonstrate significant trends in applying mechanical principles to celestial bodies and industrial processes. The work on granular materials has important implications for understanding asteroid formation, while his contact mechanics research informs material science and engineering design. His publications reveal a consistent focus on stability phenomena across different physical systems. INAE Young Engineer Award Dr. Sharma leads the Mechanics and Applied Mathematics research group at IIT Kanpur, supervising research projects that examine fundamental properties of materials under various mechanical conditions. His work combines theoretical analysis with computational methods to address complex mechanical problems with both academic and practical significance. He maintains an active research program with ongoing projects examining the mechanical behavior of granular systems in space environments. Based in office NL-102 in the Department of Mechanical Engineering, Dr. Sharma contributes significantly to the academic community through his teaching, research supervision, and scholarly publications in high-impact journals.

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Changxi ZhengView profile

Associate Professor

Columbia UniversityUnited States

Changxi Zheng is an Associate Professor in the Department of Computer Science at Columbia University's School of Engineering and Applied Science (SEAS). He directs Columbia's Computer Graphics Group (C2G2) within the Columbia Vision and Graphics Center (CVGC). After receiving his PhD from Cornell University, he joined the faculty of Computer Science Department at Columbia, where he has established himself as a leading researcher in computer graphics and scientific computing. Dr. Zheng's research spans multiple areas of applied computer science with a particular focus on computer graphics and scientific computing. His work centers around developing numerical models for simulating physical phenomena involving complex motions such as fluids, bubbles, and thin rods, along with their resulting acoustic waves. Leveraging computational insights from these models, he devises methods for improving tangible object creation, enabling novel human-computer interactions, and developing software tools for acoustic and photonic devices. His research has attracted significant public interest and media coverage, including projects like FontCode, AirCode, and Computational Metallophone Design. His recent publications reveal a strong interdisciplinary approach, bridging computer graphics, physics simulation, machine learning, and hardware design. His work demonstrates consistent innovation in computational methods for simulating physical phenomena and applying these techniques to practical problems in 3D printing, acoustic modeling, and interactive systems. The breadth of his research spans from fundamental physics-based simulations to practical applications in industry. Columbia SEAS Dean's Fellow (for advised students) NSF Graduate Research Fellow (for Ruilin Xu) Snap Research Fellow (for Rundi Wu) CKGSB Fellow (for Yun Fei) Adobe Research Fellow (for Gabriel Cirio) Marie Sklodowska-Curie Individual Fellow (for Rundi Wu) Best Paper Award at ACM International Conference on Multimedia (ACMMM), 2019 Dr. Zheng actively mentors a diverse group of students, including current PhD candidates and postdoctoral researchers. His research group has received support from various sources that enable their innovative work in computational graphics and physics-based simulation. He has supervised numerous successful students who have gone on to positions at leading technology companies including Adobe, Tencent, Facebook, and academic institutions. As director of Columbia's Computer Graphics Group (C2G2) within the Columbia Vision and Graphics Center (CVGC), Dr. Zheng leads a vibrant research team focused on advancing the state of the art in computer graphics, physics-based simulation, and their applications. The group maintains strong collaborations with industry partners and academic institutions worldwide, fostering an environment of innovation and practical application of theoretical concepts.

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Hai-Quan MaoView profile

Professor

Johns Hopkins UniversityUnited States

Hai-Quan Mao is a Professor of Materials Science and Engineering at Johns Hopkins University, with a joint appointment in the Biomedical Engineering Department (School of Medicine). He directs the Institute for NanoBioTechnology (INBT) and leads the Translational Tissue Engineering Center. His research focuses on biomaterials, regenerative engineering, and immunoengineering, particularly developing nanomaterials for therapeutic delivery and tissue regeneration. Mao holds 35 U.S. patents, co-founded two biotech companies, and received prestigious awards including National Academy of Inventors Fellow and NSF CAREER Award. Education: BS in Chemistry (1988) and PhD in Polymer Chemistry (1993) from Wuhan University. Postdoctoral training at Johns Hopkins (1995–1998), followed by roles at Johns Hopkins Singapore (1999–2003) before joining the Whiting School faculty. Research emphasizes nanofiber scaffolds for liver/nerve regeneration, DNA/lipid nanoparticle engineering for gene therapy, and artificial lymph node matrices for immunotherapy. His lab translates biomaterials innovations into clinical applications, with NIH-funded projects addressing cancer, malaria, and tissue damage. Awards include over 60 provisional patents, multiple Johns Hopkins translational awards, and Thalheimer Awards for research. He serves as associate editor of Biomaterials and editorial board member of major journals. Lab activities include scalable nanoparticle manufacturing, machine learning for material design, and collaborations with industry/clinical partners. Recent work includes lipid nanoparticle optimization for mRNA vaccines and exosome-based therapies for Crohn’s disease.

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Gerard A. AteshianView profile

Professor

Columbia UniversityUnited States

Gerard A. Ateshian is the Andrew Walz Professor of Mechanical Engineering and Professor of Biomedical Engineering at Columbia University, where he has been a faculty member since 1991. He also served as Chair of the Department of Mechanical Engineering from 2011 to 2014 and is the founding director of the Musculoskeletal Biomechanics Laboratory (MBL), established in 1996. Education: BS (1986), MS (1987), MPhil (1990), and PhD (1991) in Mechanical Engineering from Columbia University. Research Interests: Professor Ateshian's research focuses on the mechanics of soft biological tissues , particularly articular cartilage . His work integrates theoretical, experimental, and computational approaches to understand cartilage lubrication, tissue engineering, and growth and remodeling in living tissues. He has extended continuum mechanics frameworks to model complex biological phenomena such as mass transport, osmotic effects, and reactive mechanics in tissue mixtures. His recent efforts include developing open-source computational tools (FEBio) and translating research into clinical treatments for osteoarthritis . Scientific Awards: H.R. Lissner Medal, ASME (2017) OARSI Basic Science Award (2013) Columbia Engineering Alumni Association Distinguished Faculty Teaching Award (2012) Great Teacher Award, Society of Columbia Graduates (2002) YC Fung Young Investigator Award, ASME (1997) Fellow: ASME, BMES, AIMBE Advising and Mentorship: Professor Ateshian has advised numerous PhD students, including recent graduates Vince Sise and Katherine Spack , who completed their dissertations on cartilage fatigue and osteochondral allografts, respectively. His lab actively mentors students from both Mechanical and Biomedical Engineering programs. Laboratory and Collaborations: He directs the Musculoskeletal Biomechanics Laboratory (MBL) , which collaborates closely with the Cellular Engineering Laboratory of Prof. Clark Hung and with Dr. Jeffrey Weiss at the University of Utah on computational modeling (FEBio). He also collaborates with Columbia University Medical Center faculty on clinical translation of cartilage research.

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Bradley D. OlsenView profile

Professor

Massachusetts Institute of TechnologyUnited States

Bradley D. Olsen is a full professor in the Department of Chemical Engineering at the Massachusetts Institute of Technology (MIT), where he leads research at the intersection of polymer science, soft matter physics, and bioengineering. His work focuses on designing materials for critical applications in biotechnology, hemostasis, and sustainable polymer development while advancing fundamental understanding of polymer network mechanics and self-assembly. Education: Ph.D. in Chemical Engineering, University of California Berkeley (2007) S.B. in Chemical Engineering, Massachusetts Institute of Technology (2003) Olsen's research spans protein-based materials, block copolymer phase behavior, and mechanochemical hydrogels. He has pioneered methods for quantifying polymer network topology, developing hemostatic nanoparticles, and creating bio-inspired materials for selective biomolecular transport and medical applications. His recent publications emphasize data-driven approaches to polymer characterization and educational outreach in materials science. Scientific Awards: American Physical Society (APS) Fellow (2023) Fulbright Amazonia Scholar (2023) Alexander and I. Michael Kasser Chair in Chemical Engineering (2021) ACS Macro Letters Young Investigator Award (2021) MIT Committed to Caring Honor (2019) AIChE Owens Corning Early Career Award (2019) APS Dillon Medal (2018) Kavli Emerging Leader in Chemistry (2017) ACS Polymer Division Fellow (2016) Camille Dreyfus-Teacher Scholar (2015) Alfred P. Sloan Research Fellow (2014) NSF Career Grant (2013) NIH Postdoctoral Fellowship (2008-2009) Hertz Fellow (2003-2007) Barry M. Goldwater Scholarship (2002) Olsen has received significant grant support including NSF Career (2013) and AFOSR (2012) awards. His teaching activities include innovative international outreach like the 2025 soccer-themed science camp in Brazil. The Olsen Group at MIT explores advanced materials with applications ranging from trauma care to sustainable polymers.

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Amadeus GebauerView profile

Researcher

Technical University of MunichGermany

Amadeus Gebauer is a Researcher at the Chair of Computational Mechanics within the Institute for Computational Mechanics at the Technical University of Munich (TUM), serving as a Research Associate since 2019. His work specializes in computational biomechanics with emphasis on cardiac mechanics modeling, growth and remodeling processes, and multi-physics simulation frameworks. Education: Master of Science (M.Sc.) in Mechanical Engineering, Technical University of Munich, 2019 Research Interests: Gebauer's research centers on cardiac mechanics modeling, including growth and remodeling of cardiac tissue, cardiac active tissue mechanics, and medical image processing. He develops advanced computational methods for parallel and high performance computing, particularly through the 4C multi-physics simulation framework. His work integrates constrained mixture models to simulate organ-scale biological processes, bridging computational mechanics with clinical cardiology applications and focusing on mechanobiological stability in cardiac systems. Publication Trends: Gebauer's publications (2018-2025) demonstrate consistent innovation in computational cardiology, primarily using constrained mixture models to address cardiac growth and remodeling. His recent work introduces adaptive integration techniques for history variables and homogenized modeling approaches, while expanding into software benchmarking for cardiac elastodynamics and gastric motility simulations. These contributions highlight his expertise in developing robust numerical methods for multi-physics biomedical problems, with increasing focus on patient-specific applications and high-performance computing solutions. Teaching and Advising: Gebauer teaches core computational mechanics courses including Finite Elemente and Numerische Festkörpermechanik across multiple semesters. He has supervised diverse student projects ranging from term papers to Master's theses, with notable collaborations including Maximilian Grill's shoulder biomechanics research (2020) and Janina Datz's artery geometry framework development (2021). His advising consistently focuses on cardiac mechanics, computational modeling, and medical device simulation. Research Environment: As part of Professor Wolfgang A. Wall's Institute for Computational Mechanics (LNM) at TUM, Gebauer contributes to a leading research group in computational solid/fluid mechanics. The LNM develops the 4C simulation framework for complex engineering and biomedical challenges, with current emphasis on cardiac growth modeling, multi-physics integration, and high-performance computing applications in personalized medicine.

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Rui NiView profile

Associate Professor

Johns Hopkins UniversityUnited States

Rui Ni is an associate professor in the Department of Mechanical Engineering at Johns Hopkins University, directing the Fluid Transport Lab. His research focuses on experimental fluid mechanics, turbulence, multiphase flows, and their applications in energy systems, environmental engineering, and physiological processes. He holds a PhD in Physics from the Chinese University of Hong Kong (2011), followed by postdoctoral work at Yale and Wesleyan Universities. Before joining JHU, he held the Kenneth Kuan-Yun Kuo Early Career Professorship at Penn State University. His research interests include dusty flows, Lagrangian particle tracking, and animal collective behaviors. Notable projects include collaborations with NASA on plume-surface interaction and the development of advanced diagnostic tools like physics-informed machine learning and 3D particle tracking. He has received prestigious awards, including the NSF CAREER Award and ACS-PRF New Investigator Award, and leads studies on turbulence modulation by deformable bubbles, fish schooling efficiency in turbulent environments, and interfacial mass transfer dynamics. Key Projects: Plume-Surface Interaction (NASA collaboration), Fish Aquarium with Turbulent Environment (FATE) facility, V-ONSET multiphase flow facility. Grants: Gordon and Betty Moore Foundation’s Experimental Physics Investigators Initiative Grant. Lab Focus: Experimental and computational studies of multiphase flows, physiological flows, and complex systems. Ni’s work bridges fundamental fluid dynamics with practical applications, such as improving energy efficiency and understanding biological systems like fish schooling and nasal drug delivery mechanisms.

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Aberham Hailu FeyissaView profile

Associate Professor

Technical University of DenmarkDenmark

Aberham Hailu Feyissa is an Associate Professor at the National Food Institute of the Technical University of Denmark , specializing in process modeling and sustainable food engineering. His research bridges complex transport phenomena with practical food manufacturing challenges. Ph.D. in Food Process Engineering, Technical University of Denmark MSc in Food Science, K.U.Leuven and Universiteit Gent BSc in Chemical Engineering, Bahir Dar University His work focuses on coupled mass and heat transfer during solid food processing, aiming to develop robust first-principles models for predictive process optimization. Key applications include Ohmic heating , digital twin technology , and bioactive ingredient extraction . Recent publications highlight his contributions to sustainable food processes , including insect-based feed modeling , seaweed bread kinetics , and clean-label cheese formulation . His methodological innovations span FTIR spectroscopy , computational fluid dynamics , and kinetic modeling . Supervisor for PhD students S. S. Turgut , M. E. Jabali , and Dahal S. Principal Investigator for projects like Modelling and Digitalisation of Food Processes and Sustainable Extraction of Bioactive Insect Fractions Active in conference presentations and peer review , he drives advancements in food process understanding through mechanistic modeling and mathematical simulation .

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Zongyi LiView profile

Research Fellow

California Institute of Technology (Caltech)United States

Zongyi Li is a Research Fellow at Massachusetts Institute of Technology , hosted by Kaiming He. They are currently pursuing a Ph.D. in Computing and Mathematical Sciences at Caltech (2019-2025), mentored by Anima Anandkumar and Andrew Stuart. Ph.D. candidate: Computing and Mathematical Sciences, Caltech (2019-2025) B.Sc. in Computer Science and Mathematics with a Jazz minor from Washington University in St. Louis (2015-2019) They focus on Neural Operators for learning solution operators in Partial Differential Equations (PDEs) , particularly in fluid mechanics and earth science . Their work models physical simulations with chaotic behaviors and complex geometries, showing applications in weather forecasting , carbon storage , and aerodynamics simulation . Publications emphasize resolution-invariant models , chaotic systems , and zero-shot super-resolution capabilities. Their research combines Fourier analysis , graph networks , and physics-informed loss functions to achieve state-of-the-art performance in PDE solving with up to 1000x speedup over traditional solvers. Fellowships: Kortschak Scholarship PIMCO Fellowship Amazon AI4Science Fellowship Nvidia Fellowship MIT Novo Nordisk AI Fellowship Code & Open-Source: Co-developer of the NeuralOperator library Implementations for Fourier Neural Operators , Graph Neural Operators , and Tensorized Neural Operators Media Recognition: Quanta Magazine MIT Tech Review NVIDIA Features Towards Data Science

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Anthony RollettView profile

Professor

Carnegie Mellon UniversityQatar

Anthony Rollett is a Professor in the Department of Materials Science and Engineering at Carnegie Mellon University , where he has been a faculty member since 1995. He serves as the Principal Investigator and Co-Director of the NASA-supported Institute for Model-Based Qualification & Certification of Additive Manufacturing (IMQCAM) and co-director of the Next Manufacturing Center . Prior to CMU, he held leadership roles at Los Alamos National Laboratory (1991-1995). Education: Ph.D., Materials Engineering, Drexel University (1987) MA, Metallurgy and Materials Science, Cambridge University (1977) Research Interests: Rollett’s work focuses on microstructural evolution and microstructure-property relationships in 3D using experiments and simulations. His expertise spans additive manufacturing , metal 3D printing , materials for energy systems , grain growth , recrystallization , and stereology , with techniques like high-energy diffraction microscopy (HEDM) and dynamic x-ray radiography (DXR) . Scientific Contributions: He has over 320 peer-reviewed publications and an h-index >80 . His recent articles highlight machine learning for laser processing , fatigue analysis of additively manufactured alloys, and design optimization for heat exchangers in supercritical CO2 and solar thermal applications . Scientific Awards: Fellow of ASM International (1996) Fellow of the Institute of Physics (UK) (2004) Fellow of The Minerals, Metals & Materials Society (TMS) (2011) Cyril Stanley Smith Award (TMS, 2014) Member of Honor, French Metallurgical Society (2015) US Steel Professor (2017) Francqui International Professor (2020-2021) International FAME Award (2023) Leadership & Impact: Rollett co-led the development of a NASA Space Technology Research Institute for additive manufacturing and established a new master’s program in additive manufacturing (2018). His research group is funded by industry , federal agencies , and Pennsylvania state grants . He also serves on the Basic Energy Science Advisory Committee and Defense Programs Advisory Committee for the Department of Energy.

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Jan MadsenView profile

Professor

Technical University of DenmarkDenmark

Jan Madsen is a Professor at DTU Compute, Technical University of Denmark, and Head of the Embedded Systems Engineering section. His research focuses on system-level modeling and design of embedded computing systems, particularly cyber-physical systems, microfluidic biochips, and synthetic biology applications. Develops design automation tools and methodologies for embedded systems Supervises numerous PhD students and leads major research projects Research Interests Key areas include: Embedded systems-on-a-chip Cyber-Physical Systems (Internet-of-Things) Microfluidic Lab-on-Chip devices Synthetic biology with molecular computing Design, modeling, and optimization of complex systems Scientific Awards DATE Fellow (2019) IEEE CEDA Outstanding Recognition (2019) DTU Scientific Advise Award (2013) Best Paper Awards at MECO (2013) and CASES (2009) Jorck’s Foundation Research Award (1995) Publications His 14+ journal papers and 115+ conference papers demonstrate expertise in: SystemC-based modeling frameworks Energy-aware sensor networks Self-healing eDNA architectures Microfluidic biochip synthesis RTOS modeling and MPSoC exploration

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Salvador Navarro-MartinezView profile

Visiting Professor

Imperial College LondonUnited Kingdom

Salvador Navarro-Martinez is a Visiting Professor in the Department of Mechanical Engineering at Imperial College London, affiliated with the Energy Futures Lab and Thermofluids research groups. He holds a Mechanical Engineering degree from the University of Zaragoza (Spain) and a PhD in Aeronautics and Astronautics from the University of Southampton, where his doctoral work focused on numerical simulations of hypersonic flows and heat transfer for planetary re-entry systems. BEng (Ingeniero Industrial): University of Zaragoza, Spain PhD: University of Southampton, UK His research interests span combustion modeling, spray atomization, and computational fluid dynamics. Notable achievements include the Sugden Award (Combustion Institute, 2005 & 2007) and a Royal Society University Fellowship (2009) for studying droplet size distributions. His work bridges aerospace engineering, applied mathematics, and interdisciplinary engineering applications. He has contributed to Large Eddy Simulation (LES) frameworks for combustion systems and has expertise in experimental measurements of complex fluid dynamics. His current role at Imperial College emphasizes collaborative research in energy-efficient technologies and advanced thermal management systems.

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Ian FrigaardView profile

Professor

University of British ColumbiaCanada

Ian Frigaard is a Professor in the Department of Mechanical Engineering at the University of British Columbia (UBC), affiliated with the Faculty of Applied Science. He also holds an appointment in the Department of Mathematics. His research group operates in UBC's Complex Fluids Lab, focusing on interdisciplinary studies combining mathematical, experimental, and computational approaches. Education: B.Sc. (University of Wales) M.Sc. (University of Oxford) D.Phil. (University of Oxford) C.Math. (Certificate in Mathematics) Research Interests: Professor Frigaard specializes in non-Newtonian fluid mechanics, particularly the mechanics of visco-plastic (yield stress) fluids. His work addresses industrial challenges in petroleum engineering, including well cementing, leakage prevention, and abandonment techniques related to GHG emission control and environmental protection. Research methodologies span theoretical modeling, experimental validation, and computational simulations. Publication Trends: Recent work (2021–2023) emphasizes bubble dynamics in complex fluids, displacement flows in annular geometries, wellbore integrity modeling, and stochastic risk assessment for oil/gas operations. Publications frequently appear in top-tier journals like the Journal of Fluid Mechanics and Journal of Non-Newtonian Fluid Mechanics . Awards & Honors: CSME Fluid Mechanics Medal (2024) Stanley G. Mason Award, Canadian Society of Rheology (2022) Killam Research Prize, UBC (2019) Academic Leadership: Leads a research group of 10+ graduate students and postdocs. Provides summer internships and collaborates extensively with the petroleum industry. Research is supported by industrial partnerships and institutional grants. Facilities: Conducts experiments in UBC's Complex Fluids Lab, equipped for advanced rheological measurements and flow visualization.

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Andreas RietbrockView profile

Professor

Karlsruhe Institute of TechnologyGermany

Andreas Rietbrock is Professor and Director of the Geophysical Institute (GPI) at the Karlsruhe Institute of Technology (KIT) , Germany, where he also serves as Dean of Studies for Geophysics . He is a leading expert in earthquake seismology, seismic tomography, and subduction zone dynamics, with a strong focus on integrating advanced observational techniques and computational methods. Education: While specific degrees are not listed in the provided text, his extensive publication record and leadership roles indicate advanced academic training in geophysics and seismology. Research Interests: His work spans a wide range of topics including: Seismic imaging of subduction zones (e.g., Nazca, Lesser Antilles) Earthquake rupture dynamics and fault mechanics Volcanic seismology and magma transport Full waveform inversion and AI-enhanced seismic analysis Distributed Acoustic Sensing (DAS) applications Induced seismicity and reservoir monitoring Research Trends: His recent publications (2022–2025) emphasize the use of dense seismic arrays, AI-based data processing, and multi-method tomography to study complex tectonic environments. Key themes include high-resolution imaging of slab structures, fluid migration in subduction zones, and the integration of DAS and machine learning for seismic monitoring. Scientific Contributions: Andreas has led major international projects such as the ANTICS Large-N deployment in Albania and the VoiLA project in the Lesser Antilles. He has published extensively in top-tier journals like Nature , Geophysical Research Letters , and Journal of Geophysical Research , with over 200 peer-reviewed articles. Teaching and Supervision: He teaches courses such as "Introduction to Geophysics II", "Seismology", and "Current Topics in Seismology and Risk". While specific student names are not listed, his role as Dean and principal investigator on numerous projects indicates active supervision of graduate students and postdocs. Labs and Teams: He leads the seismology group at GPI, coordinating large-scale deployments of seismic instruments, including ocean-bottom seismometers and fiber-optic DAS systems. His team collaborates globally with institutions in Europe, South America, and Asia.

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Kelly ArnoldView profile

Associate Professor

University of Michigan-Ann ArborUnited States

Kelly Arnold is an Associate Professor in the Department of Biomedical Engineering at the University of Michigan. Her research integrates systems engineering principles with immunology to investigate variability in immune responses across infection, vaccination, and injury, with a focus on computational modeling and clinical translation. Research Focus Systems-level immune response modeling Vaccination and antibody functionality Vaginal microbiome-host interactions Chronic lung disease progression Computational serology and proteomics Recent Work Her 2025 studies examine SARS-CoV-2 vaccination responses in cancer patients and computational frameworks for vaginal probiotics. Earlier works (2024-2007) span COPD progression, lupus fibrosis, HIV susceptibility, and tissue engineering for fertility preservation. Methodologies include proteomic profiling, network modeling, and microfluidic systems.

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