Seminars
Fall, 2023
Flexoelectricity and Electrets
Pradeep Sharma
Hugh Roy and Lillie Cranz Cullen Distinguished University Professor
and
Chair of Mechanical Engineering
Department of Mechanical Engineering
University of Houston
Houston, TX
The ability of certain materials to convert electrical stimuli into mechanical deformation, and vice versa, is a prized property. Not surprisingly, applications of such so-called piezoelectric materials are broad—ranging from energy harvesting to self-powered sensors. In this presentation, I will highlight a relatively understudied electromechanical coupling called flexoelectricity that appears to have implications in topics ranging from biophysics to the design of next-generation soft multifunctional materials. Specifically, I will argue, through computational examples, the tantalizing possibility of creating “apparently piezoelectric” materials without piezoelectric materials—e.g. graphene, emergence of “giant” piezoelectricity at the nanoscale, and (among others) the mechanisms underpinning magnetoreception in certain animals.
Pradeep Sharma is the Hugh Roy and Lillie Cranz Cullen Distinguished University Professor and Chair of Mechanical Engineering at the University of Houston. He also has a joint appointment in the Department of Physics. He received his Ph.D. in mechanical engineering from the University of Maryland at College Park in the year 2000. Subsequent to his doctoral degree, he was employed at General Electric R & D for more than three years as a research scientist. He joined the department of mechanical engineering at University of Houston in January 2004. He is a member of the US National Academy of Engineering. His other honors and awards include the Young Investigators Award from Office of Naval Research, Thomas J.R. Hughes Young Investigator Award from the ASME, Texas Space Grants Consortium New Investigators Program Award, the Fulbright fellowship, the Melville medal, the James R. Rice medal from the Society of Engineering Science, ASME Charles R. Russ medal, the Guggenheim, and the University of Houston Research Excellence Award. He is a fellow of the ASME, the associate editor of the Journal of the Mechanics and Physics of Solids, chief-editor of the Journal of Applied Mechanics and serves on the editorial board of several other journals. He specializes in the broadly defined fields of continuum mechanics of solids and theoretical and computational materials science.
Wednesday, August 23, 2023
3:30 PM
Seaver Science Library, Room 202 (SSL 202)
The Zoom webinar is at https://usc.zoom.us/j/96742044706?pwd=RDFlZ0tTYTdXVXhDeGgxSElJT3BzUT09.
host: Plucinsky
Thin-Film Flows: From Similarity Solutions to New Insights in Molecular Biology
Howard Stone
Donald R. Dixon ’69 and Elizabeth W. Dixon Professor in Mechanical and Aerospace Engineering
Department of Mechanical and Aerospace Engineering
Princeton University
Princeton, NJ
Fluid mechanics has a rich history, as of course does mechanics more generally. The ideas bridge science and engineering disciplines, even as they generate new fundamental research questions in fluid mechanics. In this talk I sketch some recent themes* from my research group, which bridge a wide range of length scales. First, I give a brief survey of some of the fluid mechanics problems that we have been investigating in recent years. Second, whereas traditional similarity solutions in course work and research typically involve nonlinear equations with two independent variables, I will illustrate an experimentally motivated similarity solution involving three independent variables, for which we construct an analytical solution that can be compared with experimental measurements. Third, I discuss the formation of the spindle in a dividing cell, which is a fundamental aspect of molecular biology. Experiments documenting a condensed protein phase on growing microtubules are reported, followed by the appearance of the Rayleigh-Plateau instability, which produces discrete droplets along a microtubule: the drops drive branching nucleation, which is an important mechanism for the developing spindle.
*The research described was performed by many people in my research group, as well as some external collaborations.
Howard Stone received the B.S. degree in Chemical Engineering from UC Davis in 1982 and the PhD in Chemical Engineering from Caltech in 1988. Following a postdoctoral fellowship at the University of Cambridge, in 1989 Howard joined the faculty of the (now) School of Engineering and Applied Sciences at Harvard University, where he eventually became the Vicky Joseph Professor of Engineering and Applied Mathematics. In July 2009 Howard moved to Princeton University where he is Donald R. Dixon ’69 and Elizabeth W. Dixon Professor in Mechanical and Aerospace Engineering.
Professor Stone's research interests are in fluid dynamics, especially as they arise in research and applications at the interface of engineering, chemistry, physics, and biology. He is a Fellow of the American Physical Society (APS), and is past Chair of the Division of Fluid Dynamics of the APS. Currently he is on the editorial or advisory boards of Physical Review Fluids, Langmuir, and Soft Matter, and is co-editor of the Soft Matter Book Series. He is the first recipient of the G.K. Batchelor Prize in Fluid Dynamics (2008) and in 2016 recipient of the Fluid Dynamics Prize of the APS. He was elected to the National Academy of Engineering in 2009, the American Academy of Arts and Sciences in 2011, the National Academy of Sciences in 2014, the Royal Society (United Kingdom) as a Foreign Member in 2022, and the American Philosophical Society in 2022.
Wednesday, August 30, 2023
Location: The Franklin Suite
(Tutor Campus Center, 3rd Floor)
Reception will begin promptly at 12 noon.
Seminar immediately after the reception.
The Zoom webinar is at https://usc.zoom.us/j/96742044706?pwd=RDFlZ0tTYTdXVXhDeGgxSElJT3BzUT09.
host: Ronney
From Autonomous Systems to Generative AI and Backwards: An Optimal Control Perspective
Evangelos Theodorou
Associate Professor
and
Amazon CORE-AI Scholar
Guggenheim School of Aerospace Engineering
Georgia Institute of Technology
Atlanta, GA
In this talk, I will present use cases for stochastic optimal control that span the areas of terrestrial high-speed navigation, control of VTOL vehicles for urban aerial mobility, large-scale multi-agent control, training of score-based models in generative AI, opinion dynamics depolarization and single cell RNA sequencing. The presentation will cover fundamental concepts in stochastic control theory that includes path integrals, Forward-Backward SDEs and Schrodinger Bridges, and highlight the importance of scalable optimization for large scale and real time decision-making. In the last part of the talk, we will look into different distributed optimization architectures for large-scale optimal control and conclude with future directions and vision at the intersection of autonomy, generative AI and large-scale optimization.
Evangelos A. Theodorou is an Associate professor with the Guggenheim School of aerospace engineering at Georgia Institute of Technology and Amazon CORE-AI Scholar. He is also the director of the Autonomous Control and Decision Systems Laboratory, and he is affiliated with the Institute of Robotics and Intelligent Machines and the Center for Machine Learning Research at Georgia Tech. Evangelos Theodorou holds a BS in Electrical Engineering, from the Technical University of Crete (TUC), Greece in 2001. He has also received a MSc in Production Engineering from TUC in 2003, a MSc in Computer Science and Engineering from University of Minnesota in spring of 2007 and a MSc in Electrical Engineering on dynamics and controls from the University of Southern California(USC) in Spring 2010. In May of 2011 he graduated with his PhD, in Computer Science from USC. After his PhD, he was a Postdoctoral Research Fellow with the department of computer science and engineering, University of Washington, Seattle. Evangelos Theodorou is the recipient of the King-Sun Fu best paper award of the IEEE Transactions on Robotics in 2012 and a recipient several best paper awards and nominations in top conferences in machine learning and robotics communities. His theoretical research spans the areas of stochastic optimal control theory, machine learning and optimization. Applications involve learning, planning and control in autonomous, robotic and aerospace vehicles, multi-agent and large-scale systems, and dynamical systems in social sciences and biology.
Wednesday, September 6, 2023
3:30 PM
Seaver Science Library, Room 202 (SSL 202)
The Zoom webinar is at https://usc.zoom.us/j/98121141178?pwd=VGEyaXVWYnRaazFYWUVhbVAycGVWQT09.
host: Nguyen
Hemodynamic Mechanisms of Heart-Aorta-Brain Coupling: From Fluid Dynamics to Advanced Diagnostics and Therapeutics
Niema Pahlevan
Assistant
Professor
Department of Aerospace & Mechanical Engineering
University of Southern California
Los Angeles, CA
The circulatory system operates based on a delicate hemodynamic balance between the heart, the aorta (the largest vessel that extends from the heart), and major physiological organs, such as the brain and kidneys. Optimal hemodynamic coupling between these organs can be impaired due to aging and/or diseases. Therefore, understanding the complex fluid dynamic coupling (hemodynamic interactions) between the heart, aorta, and brain is crucial for the diagnostics and therapeutics of related diseases, such as heart failure (HF), dementia, and myocardial infarction (heart attack). The general hypothesis is that wave dynamics in the aorta dominate the pulsatile hemodynamics of the heart and brain, as well as the nonlinear interaction between the two. This talk will elucidate the systems-level effects of aortic hemodynamics on heart-brain interactions. Our long-term goal is to transform our findings into the development of diagnostic, therapeutic, and monitoring devices for heart diseases and vascular brain damage.
Niema Pahlevan's research brings physics and mathematics tools to the study of biological systems ranging from understanding the biomechanics of cardiovascular and cerebrovascular diseases to modeling physiological systems. His ultimate goal in each research initiative is to use mathematical and mechanical engineering principles to establish new techniques and/or devices that are relevant for practicing clinicians. Dr. Pahlevan completed his undergraduate degree in Mechanical Engineering from the University of Tehran, his M.S. in Mechanical Engineering from the California State University Northridge, and PhD in Bioengineering from the California Institute of Technology (Caltech). He completed his postdoctoral training in hemodynamics and cardiovascular imaging at Caltech and Huntington Medical Research Institutes (HMRI) as a Boswell fellow. Dr. Pahlevan joined USC in 2017 as an Assistant Professor of Aerospace and Mechanical Engineering in the Viterbi School of Engineering and Assistant Professor of Medicine in the Division of Cardiovascular Medicine. He is the recipient of both the NSF CAREER Award and the American Heart Association’s Career Development Award. In 2022, he received the Junior Research Award from USC's Viterbi School of Engineering and was also appointed the holder of the Gordon S. Marshall Early Career Chair in Engineering.
Wednesday, September 13, 2023
3:30 PM
Seaver Science Library, Room 202 (SSL 102)
The Zoom webinar is at https://usc.zoom.us/j/98121141178?pwd=VGEyaXVWYnRaazFYWUVhbVAycGVWQT09.
host: Ronney
Two Fundamental Relations for Turbulent Flows
Perry Johnson
Assistant Professor
Mechanical and Aerospace Engineering department
University of California, Irvine
Irvine, CA
Two fundamental effects of turbulence are (a) an increased rate at which kinetic energy is dissipated into heat and (b) an enhanced momentum (and heat) flux across boundary layers leading to much higher skin friction drag forces (and surface heat transfer). This presentation will introduce and apply two exact relations related to these fundamental effects, respectively. First, the concept of Stokes Flow Regularization (SFR) provides an exact expression for the scale-wise energy cascade rate in terms of vortex stretching and strain-rate self-amplification. Applied to data from fully-resolved simulations, this precisely quantifies the mechanisms responsible for generating large dissipation rates at small scales. SFR also serves as an intriguing alternative to spatial filtering as the basis of large-eddy simulation modeling. Specific potential modeling advantages will be discussed. Second, the Angular Momentum Integral (AMI) equation for turbulent boundary layers will be introduced. The AMI equation quantifies the impact of various flow phenomena throughout a boundary layer flow on the skin friction relative to a baseline laminar flow. An analogous integral equation for the surface heat transfer will also be introduced. Together, these provide a powerful method for probing flow data in terms of key engineering quantities of interest. Example applications for AMI-based analysis will be shown for boundary layer transition and supersonic turbulent boundary layers.
Perry Johnson Perry Johnson earned his Ph.D. in 2017 from Johns Hopkins University (advisor: Charles Meneveau), where his work on velocity gradient dynamics in turbulence won the Corrsin-Kovasznay award. He was then a postdoctoral fellow at the Center for Turbulence Research at Stanford University for three years, working on various topics related to small-scale turbulence, multiphase & particle-laden flows, and boundary layers. He joined the Mechanical and Aerospace Engineering department at the University of California, Irvine in 2020 as an assistant professor. His recent research on the energy cascade was featured in Physics Today, and his forthcoming review of multi-scale velocity gradient dynamics will appear in the next issue of Annual Review of Fluid Mechanics.
Wednesday, September 20, 2023
3:30 PM
Seaver Science Library, Room 202 (SSL 202)
The Zoom webinar is at https://usc.zoom.us/j/98121141178?pwd=VGEyaXVWYnRaazFYWUVhbVAycGVWQT09.
host: Spedding
Nonlinear Mechanics and Robotic Mechanisms using Coiled Muscles and Snapping Beams
Sameh Tawfick
Associate
Professor
Department of Mechanical Science and Engineering
University of Illinois
Urbana, IL
My group is developing a roadmap for elastic actuating materials to replace bulky electric motors in miniature robots requiring large mechanical work output.
First, I will describe the mechanics of coiled muscles made by twisting nylon fishing lines, and how these actuators use internal strain energy to achieve a “record breaking” performance. Then I will describe intriguing hierarchical super-, and hyper-coiled artificial muscles which exploit the interplay between nonlinear mechanics and material microstructure. Next, I will describe their use to actuate the dynamic snapping of insect-scale jumping robots. The combination of strong but slow muscles with a fast-snapping beam gives rise to dynamic buckling cascade phenomena leading to effective robotic jumping mechanisms.
These examples shed light on the future of automation propelled by new bioinspired materials, nonlinear mechanics, and unusual manufacturing processes.
Sameh Tawfick is an Associate Professor of Mechanical Science and
Engineering at the University of Illinois. He studies advanced materials, nonlinear
mechanics, and manufacturing processes. Sam obtained his PhD from the University of
Michigan, was a Postdoctoral Associate at the Massachusetts Institute of Technology, and
a Beaufort Visiting Fellow in St. John’s College at the University of Cambridge in 2023
He is the recipient of young investigator awards from the US Air Force, ASME, SME, and
Dean’s Award for Excellence in Research at Illinois. His teaching awards at the University
of Illinois include The Everitt Award for Teaching Excellence, The Two-year Alumni Teaching
Award, and The Engineering Council Stanley H. Pierce Award for Empathetic Student-faculty
Cooperation.
Wednesday, September 27, 2023
3:30 PM
Seaver Science Library, Room 202 (SSL 202)
The Zoom webinar is at https://usc.zoom.us/j/98121141178?pwd=VGEyaXVWYnRaazFYWUVhbVAycGVWQT09.
host: Zhao
Teaching a Robot to Perform Surgery: From 3D Image Understanding to Deformable Manipulation
Michael Yip
Associate
Professor
Electrical and Computer Engineering Department
UC San Diego
La Jolla, CA
Robot manipulation have made massive strides in the past few years, especially in grasping for warehouse logistics, due to the achievements in the computer vision and reinforcement learning communities. One area that has taken off much slower is in understanding how to manipulate deformable objects. For example, surgical robotics are used today via teleoperation from a human-in-the-loop, but replacing the human’s visual understanding and task performance with an AI remains a lofty and puzzling challenge. How do you build intuition and control of how to deform, stretch, or cut anatomical tissue, find hemorrhages and suction blood and bodily fluids from view, or simply localize your robot within a dynamically changing and deformable world in real-time?
In this talk, I will discuss our work that originates from trying to automate robotic surgery, but falls towards building new modeling and learning schemes for deformable robot manipulation and visual servoing. I will discuss how we analyze a multimodal spectrum of sensory information to solve real-to-sim and sim-to-real problems, while towing a fine line between physics-based models and the less-explainable yet highly successful latent space embeddings. I will show how these techniques apply not only to automating surgical robots but general robot manipulation in real-world scenes.
Michael Yip is an Associate Professor of Electrical and Computer Engineering at UC San Diego, IEEE RAS Distinguished Lecturer, Hellman Fellow, and Director of the Advanced Robotics and Controls Laboratory (ARCLab). His group currently focuses on solving problems in data-efficient and computationally efficient robot control and motion planning through the use of various forms of learning representations from imitation learning and reinforcement learning strategies. These techniques focus on solving problems with visually guided robot manipulation and locomotion on novel, dexterous platforms, including surgical robot manipulators, continuum robots, snake-like robots, and underwater systems. His work has been recognized through several best paper awards and nominations at ICRA and IROS, and RA-L, as well as recognitions including the NSF CAREER award and the NIH Trailblazer award. Dr. Yip was previously a Research Associate with Disney Research Los Angeles in 2014, a Visiting Professor at Stanford University in 2019, and a Visiting Professor with Amazon Robotics' Machine Learning and Computer Vision group in Seattle, WA in 2018. He received a B.Sc. in Mechatronics Engineering from the University of Waterloo, an M.S. in Electrical Engineering from the University of British Columbia, and a Ph.D. in Bioengineering from Stanford University.
Wednesday, October 11, 2023
3:30 PM
Seaver Science Library, Room 202 (SSL 202)
The Zoom webinar is at https://usc.zoom.us/j/98121141178?pwd=VGEyaXVWYnRaazFYWUVhbVAycGVWQT09.
host: Nguyen
Soft-Matter Engineering for Robotics and Wearables
Carmel Majidi
Clarence H. Adamson Professor of Mechanical Engineering
Department of Mechanical Engineering
Carnegie Mellon University
Pittsburgh, PA
http://sml.me.cmu.edu
Progress in soft lithography and soft materials integration have led to extraordinary new classes of soft-matter sensors, circuits, and transducers. These material technologies are composed almost entirely out of soft matter – elastomers, gels, and conductive fluids like liquid metal – and represent the building blocks for machines and electronics that are soft, flexible, and stretchable. Because of their intrinsic compliance and elasticity, such devices can be incorporated into soft, biologically-inspired robots or be worn on the body and operate continuously without impairing natural body motion. In this talk, I will review recent contributions from my research group in creating soft multifunctional materials for wearable electronics and soft robotics using these emerging practices in “soft-matter engineering.” In particular, I will focus on soft robots powered using shape memory materials and soft material architectures for highly stretchable digital electronics, wearable energy harvesting, and electrically-responsive actuation. When possible, I will show how the design and operation of these soft-matter technologies can be guided by theoretical modeling methods based on principles of mechanics and discrete differential geometry. In addition to presenting my own research in the field, I will also briefly review broader efforts and emerging challenges in utilizing soft multifunctional materials for applications in wearable electronics, bioelectronic interfaces, and soft robotics.
Carmel Majidi is the Clarence H. Adamson Professor of Mechanical Engineering at Carnegie Mellon University, where he leads the Soft Machines Lab. His lab is dedicated to the discovery of novel material architectures that allow machines and electronics to be soft, elastically deformable, and biomechanically compatible. Currently, his research is focused on modeling, design, and control of soft robotic systems as well as the developoment of multifunctional materials that exhibit unique combinations of mechanical, electrical, and thermal properties and can function as “artificial” skin, nervous tissue, and muscle. Carmel has received grants from industry and federal agencies along with early career awards from DARPA, ONR, AFOSR, and NASA to explore challenges in soft-matter engineering and robotics. Prior to arriving at CMU, Prof. Majidi had postdoctoral appointments at Harvard and Princeton Universities and received his PhD in Electrical Engineering at UC Berkeley.
Wednesday, October 18, 2023
3:30 PM
Seaver Science Library, Room 202 (SSL 202)
The Zoom webinar is at https://usc.zoom.us/j/98121141178?pwd=VGEyaXVWYnRaazFYWUVhbVAycGVWQT09.
host: Zhao
Cyber-Manufacturing: Delivering Manufacturing Services Over Web 3.0
Binil Starly
Motorola Professor of Manufacturing Systems
School of Manufacturing Systems & Networks
Arizona State University
Tempe, AZ
Cybermanufacturing enables the shared use of networked manufacturing infrastructure
to deliver manufacturing resources on-demand while maximizing capacity utilization,
reducing consumption of natural and material resources, and reducing costs to
product design and manufacturing. This talk will highlight three areas where our
group has contributed to the understanding of Cybermanufacturing systems – 1)
With the explosive growth of 3D product models, the data contained in them may
be used to democratize access and broaden those who are able to engage in product
design and manufacturing; 2) Understanding of manufacturing capability available
over the entire US through Natural Language Processing (NLP), and its interface
with Large Language Models (like BERT & GPT-4); 3) Identification and
Verification of Machines in the context of a Distributed Web of machines. In
the future, the digital connection across factories will also lead to
Manufacturing Networks that are highly agile, distributed, and resilient while
considering the long-term consequences of sustainable industrial performance.
Emerging digital technologies such as Pervasive Sensing, Computational
Intelligence, Edge-Fog-Cloud Computing, Digital Twins, Smart Automation,
Intelligent Collaborative Robots etc., open new possibilities in the design of
smart collaborative physical and digital networks of factories.
Binil Starly serves as the Founding School Director and Professor in the School of Manufacturing Systems & Networks, one of 8 Schools within the Ira. A. Fulton Schools of Engineering at Arizona State University. He has over 20 years of experience in Digital manufacturing. His laboratory is working on technologies that merge the digital and the physical world towards advancing both discrete and continuous manufacturing. His work is supported by the US National Science Foundation, Department of Energy and the Department of Defense. He has received the NSF CAREER award, SME ‘20 Most Influential Professors in Smart Manufacturing’, SME Young Manufacturing Engineering Award (2011) and numerous teaching awards at the University of Oklahoma and North Carolina State University. His lab website is at: https://www.dimelab.org.
Wednesday, October 25, 2023
3:30 PM
Seaver Science Library, Room 202 (SSL 202)
The Zoom webinar is at https://usc.zoom.us/j/98121141178?pwd=VGEyaXVWYnRaazFYWUVhbVAycGVWQT09.
host: Chen
Interface Dislocations in Grain Boundaries and 2D Heterostructures using Smith Normal Bicrystallography
Nikhil Chandra Admal
Assistant Professor
Department of Mechanical Science and Engineering
University of Illinois at Urbana-Champaign
Urbana-Champaign, IL
Crystal interfaces exist in diverse materials systems in the form of grain and phase boundaries in threedimensional (3D) polycrystals and as heterointerfaces in two-dimensional (2D) heterostructures. Interfaces significantly influence the mechanical response of a material as observed in phenomena such as superplasticity and creep in polycrystals and the much sought-after electromechanical coupling in 2D materials that is responsible for correlated electron physics.
This talk is motivated by the central role interface plasticity plays in diverse crystalline systems. Recognizing interface dislocations as the primary carriers of interface plasticity, we will present a unified mathematical framework to construct interface dislocations in an arbitrary heterointerface. Our framework is driven by the Smith normal form (SNF) for integer matrices which enables us to systematically explore the bicrystallography of interfaces. Analogous to the definition of a bulk dislocation, which relies on the translational symmetry of a 3D lattice, the framework results in a translation symmetry of the interface that is integral to the definition of interface dislocations. Central to our framework are two lattices — coincident site lattice (CSL) and the displacement shift complete lattice (DSCL) — derived from the two lattices that constitute an interface. The CSL and the interface dislocations in 2D heterointerfaces are commonly referred to as the moir´e superlattice and strain solitons, respectively. In 3D GBs, bicrystallography informs that a step in the boundary possibly accompanies a interface dislocation, and together, they are referred to as a disconnection.
We will demonstrate the application of SNF bicrystallography to a) enumerate disconnection modes in arbitrary rational GBs, and quantify their energetics, and b) to study interface dislocations in bilayer graphene with a significant twist (> 10°). The constructive nature of the framework lends itself to an algorithmic implementation based exclusively on integer matrix algebra.
Nikhil Admal is an Assistant Professor in the Department of Mechanical Science and Engineering at the University of Illinois at Urbana-Champaign (UIUC). Before joining UIUC, Dr. Admal was a Postdoctoral Research Scholar at the University of California Los Angeles (UCLA). He received his Ph.D. in Aerospace Engineering and Mechanics from the University of Minnesota in 2014. His research interests focus on developing materials models at various length and times scales ranging from the atomic to the continuum scales, with emphasis on modeling interface phenomena. His research currently focusses on modeling recovery, recrystallization, and grain growth in crystalline materials to establish the process-structure relationship and on the mechanics of two-dimensional heterointerfaces. He received the NSF Faculty Early Career Development Program (CAREER) Award in 2023. Dr. Admal is a recipient of the Institute for Digital Research and Education (IDRE) Postdoctoral Fellowship at UCLA and the Doctoral Dissertation Fellowship from the University of Minnesota. Dr. Admal has published in various international journals, including The Journal of Chemical Physics, Journal of Mechanics and Physics of Solids, International Journal of Plasticity, Materials Theory, and the Journal of Elasticity.
Wednesday, November 1, 2023
3:30 PM
Seaver Science Library, Room 202 (SSL 202)
The Zoom webinar is at https://usc.zoom.us/j/98121141178?pwd=VGEyaXVWYnRaazFYWUVhbVAycGVWQT09.
host: Plucinsky
The Coastal Ocean Boundary Layer: Cross-Shore Structure, Bottom Roughness and Trapped Baroclinic Waves
Geno Pawlak
Professor
Department of Mechanical and Aerospace Engineering
University of California at San Diego
La Jolla, CA
In this talk I will describe analysis of the cross-shore structure of the coastal ocean boundary layer using velocity measurements from an autonomous underwater vehicle (AUV) along with time series observations of the alongshore pressure gradient. Ensemble phase averages of the alongshore pressure gradient and velocities from multiple AUV surveys reveal characteristics akin to the Stokes oscillating boundary layer, with the nearshore flow leading the offshore flow in phase and with a corresponding velocity attenuation at shallower depths. Analysis of the alongshore momentum balance allows estimation of the drag coefficient as a function of cross‐shore distance which compares favorably with roughness from LIDAR and AUV‐based mapping. Roughness data suggest that larger scales, with wavelengths comparable to the total depth, play a more significant role than smaller meter‐scale roughness in determining the drag on the tidal flow. I will also present observations that highlight the role of coastal trapped baroclinic waves in driving barotropic tidal flow on the inner shelf.
Gene Pawlak joined the UCSD Department of Mechanical and Aerospace Engineering in 2012. Before joining the Jacobs School of Engineering, he served as an associate professor in the Department of Ocean and Resources Engineering at the University of Hawaii at Manoa. Pawlak is a UC San Diego alumnus, having earned his Ph.D. from the Department of Applied Mechanics and Engineering Sciences (now Mechanical and Aerospace Engineering) in 1997.
Pawlak’s research is focused on coastal and estuarine turbulent mixing processes and their interactions with topographic features. He is particularly interested in the role of flow structure in mass and momentum transport as well as the generation of this structure by topography. Interactions occur via a variety of mechanisms including boundary layer separation and hydraulic flow response. His work presently focuses on dynamics of steady and oscillating flow over irregular boundaries as well as on the generation and evolution of large scale structure in stratified flow around coastal headlands. The influence of these boundary dynamics on sediment transport and on sediment—water column geochemical exchange processes is also of key interest. Other areas of interest include effects of offshore forcing on near-shore dynamics, cross-shore exchange processes, the interaction of flow with biological systems, stratified turbulence, autonomous vehicle applications and laboratory experimental methods.
Wednesday, November 8, 2023
3:30 PM
Seaver Science Library, Room 202 (SSL 102)
The Zoom webinar is at https://usc.zoom.us/j/98121141178?pwd=VGEyaXVWYnRaazFYWUVhbVAycGVWQT09.
host: Spedding
Unleashing the Power of AI for Precision Health: The Vital Role of Physiological and Nursing Data
Xiao Hu
Candler Chair Professor
Nell Hodgson Woodruff School of Nursing
Emory University
Atlanta, Georgia
Artificial intelligence (AI) has tremendous potential to advance clinical practice and patient care by providing clinicians augmented abilities to derive diagnostic and prognostic insights from various types of data. Medical images, structured data, clinical notes in electronic health record systems are data modalities that have so far received much attention. In addition to these data modalities in spotlight, continuous physiological data including electrocardiography, blood pressure, intracranial pressure, electroencephalography, photoplethysmography signals are part of standard of care, hence ubiquitously available for patients in acute care, and least susceptible to practice variations. Rich and dynamic pathophysiological information is embedded in these signals and yet there are no experts like radiologists dedicated to interpreting these signals at scale. Therefore, there is a vast amount of untapped information in these signals. In this keynote, we will explore three overarching approaches to process physiological data:
- The single modality approach, where novel metrics are derived from a single signal, unveiling physiological insights that remain concealed in conventional patient monitors.
- The multi-signal approach, which analyzes multiple signal modalities to elucidate the intrinsic interplay among different organ systems, providing more precise signatures of acute illnesses.
- The multimodality approach, which integrates physiological data with other clinical information, enabling enhanced patient monitoring capabilities and more precise care delivery.
Bedside nurses play a pivotal role in continuously managing, interpreting, documenting, and communicating physiological data. However, they often face alarm fatigue due to inferior built-in algorithms of patient monitors. By harnessing the power of AI tools to process physiological data, we can alleviate this burden, elevate the nursing profession, and ultimately improve patient care outcomes.
Xiao Hu is Asa Griggs Candler Chair Professor at the Nell Hodgson Woodruff School of Nursing, associated faculty at the Departments of Computer Sciences and Biomedical Informatics, and PhD program faculty at the joint Biomedical Engineering program of Georgia Tech and Emory University. He also serves as the Associate Director of the Center for Data Science. In his remarkable career, he has held faculty positions at esteemed institutions like UCLA, UCSF, and Duke University. Dr. Hu's pioneering research lies at the intersection of computational and health sciences, using advanced algorithms to transform healthcare data into actionable patient care insights. His significant contributions include over 160 peer-reviewed publications, multiple NIH research projects, and nine US patents.
Wednesday, November 15, 2023, 2023
3:30 PM
Seaver Science Library, Room 202 (SSL 102)
The Zoom webinar is at https://usc.zoom.us/j/98121141178?pwd=VGEyaXVWYnRaazFYWUVhbVAycGVWQT09.
host: Pahlevan
Smart Additive Manufacturing
Chinedum (Chi) Okwudire
Professor of Mechanical Engineering and Miller Faculty Scholar
Department of Mechanical Engineering
University of Michigan
Ann Arbor, MI
There is a lot of excitement about the potential of smart manufacturing (involving the use of information, automation, computation, software, sensing, and networking technologies) to revolutionize the manufacturing industry, e.g., by boosting manufacturing quality and productivity at low cost. An excellent application for such “smart” technologies is additive manufacturing (AM), another area of manufacturing that is gaining a lot of traction but is plagued by quality, productivity and cost issues. In this talk, I will share some of my research results in smart AM, aimed at enhancing AM quality and productivity at low cost using smart technologies. Specifically, I will discuss our work on speeding up 3D printers at low cost using advanced controls and cloud computing. I will also discuss our new research on intelligent optimization of scan sequence to minimize thermal induced defects in laser powder bed fusion AM. Finally, I will give a brief overview of efforts I am leading at the University of Michigan to integrate smart AM into our educational curriculum.
Chinedum (Chi) Okwudire is a Professor of Mechanical Engineering and Miller Faculty Scholar at the University of Michigan. His research is focused on exploiting knowledge at the intersection of machine design, control and computing to boost the performance of manufacturing automation systems at low cost. Chi has received a number of awards including the NSF CAREER Award; SME Outstanding Young Manufacturing Engineer Award; and UC Berkeley’s Russell Severance Springer Visiting Professorship. He was recently selected by SME as one of the 25 leaders transforming manufacturing. He has co-authored a number of best-paper-award-winning papers in the areas of manufacturing automation, control and mechatronics.
Wednesday, November 29, 2023
3:30 PM
Seaver Science Library, Room 202 (SSL 102)
The Zoom webinar is at https://usc.zoom.us/j/98121141178?pwd=VGEyaXVWYnRaazFYWUVhbVAycGVWQT09.
host: HOSTLASTNAME
host: Chen
Published on August 2nd, 2017
Last updated on November 17th, 2023