Chemical Engineering
Assembling colloidal mixtures into functional soft materials
Tuesday, January 21, 2020;
10:50 am
350 Health & Human Development Building
Speaker: Dr. Michael Howard from The University of Texas at Austin
Assembling colloidal mixtures into functional soft materials
https://www.che.psu.edu/department/seminars.aspx
Hosted by: Dana Hosko, Chemical Engineering
(dlh55@psu.edu)
New Design Approaches to Adsorptive CO2 Capture and Catalytic C02 Conversion to Chemicals and Fuels
Wednesday, January 22, 2020;
3:30pm
104 Thomas Building
Speaker: Chunshan Song from Penn State University, Department of Energy & Mineral Engineering
New Design Approaches to Adsorptive CO2 Capture and Catalytic CO2 Conversion to Chemicals and Fuels
Hosted by: Mike Janik, Chemical Engineering
(mjanik@psu.edu)
FexNi100-xOy Electrocatalysts for the Oxygen Evolution Reaction: Role of Electrochemical History and As-Synthesized Properties on Atomic Structure
Thursday, January 23, 2020;
10:50 am
350 Health & Human Development Building
Speaker: Dr. Lauren Greenlee from University of Arkansas
FexNi100-xOy Electrocatalysts for the Oxygen Evolution Reaction: Role of Electrochemical History and As-Synthesized Properties on Atomic Structure
https://www.che.psu.edu/department/seminars.aspx
Hosted by: Dana Hosko, Chemical Engineering
(dlh55@psu.edu)
Computer Science and Engineering
Toward Powerful AI Agents Users Understand and Trust
Monday, January 20, 2020;
10:00 a.m.
W375 Westgate
Speaker: Bryan Plummer from Boston University
Abstract: I will describe how my research enables AI to learn relationships between complex, unstructured inputs, specifically: 1) similarity relationships between two images (e.g., that a matching top and skirt are similar), and 2) similarity between descriptive text and an image or video (e.g. that a caption is similar to the image it describes). I will focus on two contributions.
First, my research has greatly expanded our understanding of the relationship between vision and language, including introducing the task of phrase grounding, which relates natural language phrases to image regions, along with a new dataset called Flickr30K Entities that is commonly used to train these models. Second, I will present my work in learning explainable visual similarity methods that can capture a greater variety of similarity functions than those in prior works.
Biography: Dr. Bryan Plummer is currently a Research Assistant Professor in the Department of Computer Science at Boston University. He completed his Ph.D. in Computer Science at the University of Illinois at Urbana-Champaign in 2018, after which he became a postdoctoral associate at Boston University before joining as a member of the faculty.
His primary research interests are in Machine Learning, Computer Vision, Vision, Language Understanding, and Robotics. He is a member of the Image and Video Computing group at Boston University, where he currently supervises 4 graduate students and 2 undergraduates. He has an excellent track record of producing innovative research and a commitment to teaching and outreach.
Hosted by: Daniel Kifer, Computer Science and Engineering
(duk17@psu.edu)
Engineering Science and Mechanics
Hydrogen in Zirconium Alloy Nuclear Fuel Cladding
Wednesday, January 22, 2020;
15:35 - 16:25
114 EES Building
Speaker: Arthur T. Motta from Department of Nuclear Engineering, Penn State University
Abstract: In face of increasing worldwide demand for electricity generation and the increasing concerns with the contribution of fossil fuel emissions to climate change, nuclear power is again being considered for further development in the US and abroad. New reactor construction is being proposed, using both, evolutionary concepts based on the current fleet of Light Water reactors (LWRs) and advanced reactor concepts. The materials used in these reactors must maintain outstanding performance for years, or even decades, in an extreme environment, in which they are exposed to a combination of high temperature and pressures, aggressive chemistry and a constant fast neutron flux.
As utilities and fuel vendors attempt to push materials to higher temperatures and doses many challenges become apparent, one of the foremost being hydrogen degradation of the nuclear fuel cladding. During reactor exposure the nuclear fuel cladding undergoes corrosion by the high temperature water. The associated hydrogen pickup can lead to hydride formation which can severely impact fuel cladding properties such as strength, ductility, corrosion resistance and fracture toughness. The behavior of hydrogen in the cladding has been the subject of continued study. In addition to the overall hydrogen concentration it is necessary to predict the formation of specific hydride morphologies that impact mechanical properties. Experimental techniques such as synchrotron radiation diffraction and fluorescence can yield unique insights into this phenomenon so that the margins can be evaluated, and mitigating strategies can be devised to allow higher burnup with its associated longer exposures.
We will review these concepts and challenges to implement them as well as the opportunities to use current advances in computational techniques and in experimental tools and techniques to understand these processes in a fundamental manner.
Bio: Arthur Motta is the Chair of the Nuclear Engineering Program and a Professor of Nuclear Engineering and Materials Science and Engineering at Penn State University. He holds degrees in Mechanical Engineering and Nuclear Engineering from the Federal University of Rio de Janeiro, Brazil, and a Ph.D. in Nuclear Engineering from the University of California, Berkeley. Before joining the Penn State faculty in 1992, he worked as a research associate for the CEA at the Centre for Nuclear Studies in Grenoble, France, for two years and as a post-doctoral fellow for AECL at Chalk River Laboratories in Canada.
Prof. Motta works in the area of radiation damage and environmental degradation to materials with specific emphasis in Zr alloys, with current projects in the areas of mechanical testing, corrosion and radiation damage. He has special interests in using advanced characterization techniques such as x-ray scattering from synchrotron radiation sources, transmission electron microscopy, and in situ irradiation to discern fundamental mechanisms of corrosion and radiation damage.
Prof. Motta is a Fellow of the American Nuclear Society (ANS) and in 2015 he received the Mishima Award from the ANS for outstanding contributions in research and development work on nuclear fuel and materials. In 2016 he was awarded the ASTM William J. Kroll Medal for sustained impactful contributions to zirconium metallurgy including corrosion, hydriding, mechanical properties and irradiation effects.
112 Forbes Field Cir
Hosted by: Lisa Spicer, Engineering Science and Mechanics
(lms8@psu.edu/814-867-1569)
Chemical Engineering
Computational studies of intermetallic catalysts for selective hydrogenation
Wednesday, January 29, 2020;
3:30pm
104 Thomas Building
Speaker: Michael Janik from Penn State University, Department of Chemical Engineering
Computational studies of intermetallic catalysts for selective hydrogenation”
Hosted by: Michael Janik, Chemical Engineering
(mjanik@psu.edu)
Computer Science and Engineering
Interactive Large-Scale Data Management and Analysis
Monday, January 27, 2020;
10:00 a.m.
W375 Westgate
Speaker: Dong Xie from University of Utah
Abstract: Nowadays, different forms of data are collected, stored, and analyzed to support important business and scientific tasks. As the amount of data grows large and fast, we face unprecedented challenges in large scale data management and analysis. In particular, we have to manage and analyze large-scale data sets interactively to provide timely insights for real-world applications. Usually, such data can be much larger than a single machine capacity and are collected in various formats at extremely high speed. Towards achieving interactive experience, algorithms and systems must be designed carefully to match up the trend of data. Furthermore, there is a growing interest in outsourcing storage and computing in public cloud, which raises concerns in security and privacy. In this talk, I will go through some of my past works in building interactive data analysis systems, including the in-memory distributed spatial analysis engine Simba and a new storage layer FishStore supporting real-time data analysis over incoming un-/semi-structured data. Besides, my other works on cloud security and data privacy will be covered briefly. Finally, I will describe future research opportunities in this area such as real-time data analysis engine that I am passionate about.
Biography: Dong Xie is a Ph D candidate from dataq group at the University of Utah. He received his bachelor’s degree from the ACM Honored Class at Shanghai Jiao Tong University in 2015, and currently works with Prof. Feifei Li. Dong is a 2018 Microsoft Research Fellow and received other rewards like SoCC 2019 best paper runner-up. His research lies in different aspects of data management, including distributed database systems, approximate query processing, security, and data privacy.
Hosted by: Bhuvan Urgaonkar, Computer Science and Engineering
(buu1@psu.edu)
Data Structures Meet Circuits and Cryptography
Wednesday, January 29, 2020;
10:00 a.m.
W375 Westgate
Speaker: Alexander (Sasha) Golovnev from Harvard University
ABSTRACT: In this talk we will discuss the state of the art in the field of data structure lower bounds and surprising connections between such lower bounds, circuit complexity, and cryptography. Proving such limitations on data structures and circuits has been a fundamental research endeavor for several decades, with connections to efficient parallel computation and the P-vs-NP question. Despite much effort, our best lower bounds in both fields have remained unchanged since the 1980s. We show a surprising connection between both fields, offering an explanation for this lack of progress. Specifically, we show that any improvement on the best known lower bound for a (linear) data structure problem would imply new circuit lower bounds, and vice versa. Our proof uses a new connection between additive and multiplicative sparse matrix factorizations. We continue this line of research by showing that data structure lower bounds for a specific class of problems are equivalent to a certain kind of cryptography. We use this connection to construct surprising (crypto-inspired) data structures for the 3-SUM problem, refuting a data structure variant of the 3SUM conjecture due to Goldstein et al.
BIOGRAPHY: Alexander Golovnev is a Rabin postdoctoral fellow at Harvard University. Prior to this, he was a postdoctoral fellow at Columbia University, and a Research Scientist at Yahoo Research. He received his PhD from the Courant Institute of Mathematical Sciences at New York University. Alexander's research interests lie broadly in computational complexity, algorithms, learning theory, cryptography and pseudorandomness, with a focus on proving lower bounds for various computational models.
Hosted by: Antonio Blanca, Computer Science and Engineering
(azb1015@psu.edu)
Engineering Science and Mechanics
Mixed Methods Approaches to Studying Doctoral Engineering Attrition, Persistence, and Cognition
Wednesday, January 29, 2020;
15:35 - 16:25
114 EES Building
Speaker: Catherine Berdanier from Department of Mechanical Engineering, Penn State University
Abstract: My research, as a tenure-track assistant professor in Mechanical Engineering at Penn State, embeds human subjects and rigorous engineering education research within a disciplinary context, with a focus on graduate-level engineering education. Though the education of graduate students is understudied compared with that of undergraduates, the intersection of sociological and psychological factors predicting attrition in graduate students is particularly unexplored. The Council of Graduate Schools reports that in doctoral engineering programs, women have a ten-year completion rate of 56%, compared with 65% overall for men. Persistence rates for traditionally underrepresented populations are much lower: the ten year-completion rate for African-American doctoral engineering students is only 47%. The lack of “socialization” is generally noted as a main reason for graduate attrition; however, few researchers seek to understand and characterize the socialization process or competency development for graduate engineering students. This seminar will introduce attendees to engineering education research through a sampling of findings from several of my ongoing studies focusing on graduate engineering students, including an NSF RFE grant exploring how various “invisible” competencies such as academic writing can impact persistence and career trajectories and the most current findings from my recently-awarded NSF CAREER grant, characterizing master’s-level departure from the engineering PhD. I will also introduce my most recent experimental research employing eyetracking methods and machine learning to study engineering competencies.
Bio: Catherine G.P. Berdanier is an Assistant Professor of Mechanical Engineering at Pennsylvania State University and is the Director of the Online MSME Program at Penn State. She earned her B.S. in Chemistry from The University of South Dakota, her M.S. in Aeronautical and Astronautical Engineering and Ph.D. in Engineering Education from Purdue University. Her research interests include graduate-level engineering education including doctoral student attrition and persistence; engineering writing; and engineering communication. Her research has been published in Journal of Engineering Education, International Journal of Engineering Education, IEEE Transactions on Professional Communication, and many other journal and conference venues. She is the recent winner of an NSF CAREER grant studying master’s-level departure from the engineering doctorate.
Hosted by: Lisa Spicer, Engineering Science and Mechanics
(lms8@psu.edu/814-867-1569)
Electrical Engineering
Hierarchical Model Predictive Control for Electro-Thermal Coordination of Vehicle Energy Systems
Thursday, February 6, 2020;
4:35 p.m.
220 Hammond
Speaker: Herschel Pangborn from Penn State
Abstract: Modern vehicles are governed by nonlinear dynamics spanning multiple timescales and physical domains. Due to electrification and increasing on-board power demands, managing both the electrical and thermal energy of these systems has become a significant challenge, limiting capability, safety, and efficiency. This talk will present a hierarchical control framework for vehicle energy management that meets this challenge by coordinating control actions throughout complex systems. Results to be presented include a hardware-in-the-loop implementation of electro-thermal hierarchical control and a decentralized passivity-based Model Predictive Control (MPC) approach that leverages the system structure to guarantee closed-loop stability under switching.
Biography: Dr. Herschel C. Pangborn is an Assistant Professor of Mechanical Engineering at the Pennsylvania State University. His research focuses on the dynamic modeling, control, and design of electro-thermal energy systems in vehicles and buildings, with particular emphasis on hierarchical control and switched systems.
Prior to earning his doctorate in Mechanical Engineering from the University of Illinois at Urbana-Champaign in 2019, Dr. Pangborn received a B.S. in Mechanical Engineering from Penn State in 2013 and an M.S. in Mechanical Engineering from Illinois in 2015. During the second half of 2019, he was a Postdoctoral Research Associate at Illinois. Dr. Pangborn is a recipient of the NSF Graduate Research Fellowship, the University of Illinois MechSE Graduate Teaching Fellowship, and the ASME Energy Systems Technical Committee Best Paper Award. He has also been included on the University of Illinois List of Teachers Ranked as Excellent by Their Students.
Hosted by: Minghui Zhu, Electrical Engineering
(muz16@psu.edu)
Engineering Science and Mechanics
Reverse Engineering Neuro-Mechanical Feedback Control in Terrestrial and Aerial Locomotion
Wednesday, February 5, 2020;
15:35 - 16:25
114 EES Building
Speaker: Jean-Michel Mongeau from Department of Mechanical Engineering, Penn State University
Abstract: According to the National Academy of Engineering, one the Grand Challenges for Engineering for the 21st century is to reverse engineer brain function. In this talk, I will present a framework to quantify how the brain controls movement by integrating experimental and theoretical approaches at the interface of biomechanics, neuroscience and control theory. Emphasizing the senses of touch and vision, I will draw on control tasks in running and flying insects and describe how animals implement feedback control. I will discuss novel techniques to study closed-loop behavior in virtual reality and genetic tools that permit unprecedented access to brain circuits. Throughout, I will highlight the interdisciplinary nature of my research program that can inspire the development of more agile terrestrial and aerial insect-scale robots.
Bio: Jean-Michel Mongeau earned his Ph.D. from UC Berkeley in 2013 in Biophysics and his B.S. with Honors in Biomedical Engineering from Northwestern University in 2007. He joined the Department of Mechanical Engineering at Penn State in 2017 following a post-doc at UCLA. His research has been funded by the National Science Foundation, Howard Hughes Medical Institute and Army Research Office. Dr. Mongeau was an NSF IGERT and NSF Graduate Research fellow. His research interests include the neuro-mechanics and control of locomotion in animals and machines.
Hosted by: Lisa Spicer, Engineering Science and Mechanics
(lms8@psu.edu/814-867-1569)
Chemical Engineering
Sanat K. Kumar
Tuesday, February 11, 2020;
10:50 - 11:50 am
350 Health & Human Development
Speaker: Sanat K. Kumar from Columbia University
TBD
Hosted by: Lisa Haines, Chemical Engineering
(luv1@psu.edu)
Smart, Responsive Polymers Based on Covalent Adaptable Networks: Photoswitchable States of Matter
Thursday, February 13, 2020;
10:50 - 11:50 am
350 Health & Human Development
Speaker: Christopher N. Bowman from University of Colorado, Boulder
Smart, Responsive Polymers Based on Covalent Adaptable Networks: Photoswitchable States of Matter
Hosted by: Lisa Haines, Chemical Engineering
(luv1@psu.edu)
Engineering Science and Mechanics
Additively manufactured alloys and functionally graded materials: phases and mechanical behavior
Wednesday, February 12, 2020;
15:35 - 16:25
114 EES Building
Speaker: Allison Beese from Department of Materials Science & Engineering, Penn State University
Abstract: The unique thermal histories (i.e., rapid solidification followed by repeated thermal cycles with the addition of layers) seen in additive manufacturing (AM) of metal alloys results in microstructures that may contain phases, grain morphologies, or internal pores different from those seen in their conventionally processed counterparts. These microstructures dictate the resulting mechanical properties of the alloys; thus, to enable the adoption of AM for structural applications, an understanding of the links between microstructure and deformation and/or fracture is required in order to safely and reliably design against failure. In this talk, I will present our work on experimentally and computationally investigating the impact of these unique microstructures on the deformation and failure behavior of additively manufactured alloys. I will discuss our efforts in measuring and modeling the effect of phases and pores on multiaxial plasticity and fracture of these materials. Additionally, I will describe our work on designing, fabricating, and characterizing functionally graded materials in which the chemistry is intentionally changed as a function of position to impart disparate properties as a function of position within a 3D component.
Bio: Allison Beese received her B.S. in Mechanical Engineering from Penn State. She then worked at Knolls Atomic Power Laboratory before entering graduate school. She earned her M.S. and Ph.D. degrees in Mechanical Engineering from MIT. She spent two years as a postdoctoral fellow at Northwestern University, and joined the Materials Science and Engineering Department at Penn State in 2013. She has received an NSF CAREER award, the 2018 TMS AIME Robert Lansing Hardy Award, the 2017 International Outstanding Young Researcher in Freeform and Additive Manufacturing award, and a 3M non-tenured faculty award.
Hosted by: Lisa Spicer, Engineering Science and Mechanics
(lms8@psu.edu/814-867-1569)
