Monday 18 January 2021
Software for Computational Imaging: Open Source Tools and Best Practices I
Hosts:
Charles Bouman, Purdue University (United States) and Gregery Buzzard, Purdue University (United States)
Session Chair:
Brendt Wohlberg, Los Alamos National Laboratory (United States)
10:00 – 11:15
Red Room
10:00
Conference Introduction
10:15COIMG-051
ODL - A Python based framework for model and deep learning based methods for image reconstruction, Ozan Öktem1, Jonas Adler2, and Holger Kohr3; 1KTH Royal Institute of Technology (Sweden), 2Google DeepMind (United Kingdom), and 3Thermo Fisher Scientific (the Netherlands)
10:35COIMG-052
Computational imaging using Julia, Jeffrey Fessler, University of Michigan (United States)
10:55COIMG-053
Reproducible computational imaging of tomographic data, Marcus Hanwell, Brookhaven National Laboratory (United States)
11:15 – 11:45 SESSION BREAK: Join speakers in the EI2021 Discord Voice Channel corresponding to the color of the room in which the session occurs or join an Open Discord Channel of your choice. After a plenary, join the Plenary Discord Voice Channel.
PANEL: Software for Computational Imaging: Open Source Tools and Best Practices
Panel Moderator: Charles Bouman, Purdue University (United States)
Panelists: Lawrence Drummy, Air Force Research Laboratory (United States); Doga Gursoy, Argonne National Laboratory (United States); Dilworth Parkinson, Univ. of California, Berkeley (United States); Singanallur Venkatakrishnan, Oak Ridge National Laboratory (United States); and Brendt Wohlberg, Los Alamos National Laboratory (United States)
11:45 – 12:45
Red Room
Open source software systems such as TensorFlow and SciPy have revolutionized the way that imaging science is done. This will be an interactive session in which both the panel and attendees will discuss how the community can generate and leverage open source tools for lasting impact in computational imaging.
CONFERENCE INTERACTIVE POSTERS, DEMONSTRATIONS, AND BREAK
12:45 – 13:15
see below for location
Posters and/or Demonstrations presented live during this break are related to any of the conferences held today. Zoom links to visit the posters and/or demonstrations are found on the home page of the Symposium Portal. We invite you to visit with the presenters in the designated Zoom or meet with other attendees in Discord.
COIMG-025D
ZOOM A — COIMG DEMO: "Mask recognition in the covered safe entry scanner", Henry Dietz, University of Kentucky (United States)
In the COIMG demo, Henry Dietz will augment the oral presentation of the same title, demonstrating recognizing whether a mask is being properly worn.
CVAA-017
ZOOM B — CVAA POSTER: Resolution enhancement in the recovery of underdrawings via style transfer by generative adversarial deep neural networks, George Cann1, Anthony Bourached1, Ryan-Rhys Griffiths2, and David Stork3; 1University College London (United Kingdom), 2Cambridge University Press (United Kingdom), and 3Consultant (United States)
MOBMU-038D
ZOOM C — MOBMU DEMO: "AI-based real-time monitoring system for a smart energy house, Part II", Lukasz Rojek1,2, Saiful Islam2, Michael Hartmann2, and Reiner Creutzburg2,3; 1Beuth Hochschule für Technik Berlin, Fachbereich Geoinformation, 2SRH Berlin University of Applied Sciences, and 3Technische Hochschule Brandenburg (Germany)
The MOBMU demo will augment the oral presentation of the same title by Lukasz Rojek et al.
Facial Recognition and Processing
Session Chair:
Henry Dietz, University of Kentucky (United States)
13:15 – 14:15
Red Room
13:15COIMG-023
Extreme face inpainting with sketch-guided conditional GAN, Nilesh Pandey and Andreas Savakis, Rochester Institute of Technology (United States)
13:55COIMG-025
Mask recognition in the covered safe entry scanner, Henry Dietz, University of Kentucky (United States)
14:15 – 18:00 Break in program to accommodate time zones.
KEYNOTE: Software for Computational Imaging: Open Source Tools and Best Practices
Session Chair: Brendt Wohlberg, Los Alamos National Laboratory (United States)
18:00 – 19:15
Red Room
18:00
Conference Introduction
18:15COIMG-032
KEYNOTE: Developing open source scientific software (in Python), Stéfan van der Walt, University of California, Berkeley (United States)
Keynote speaker Stéfan van der Walt is a senior research data scientist at the Berkeley Institute for Data Science (BIDS), where he leads the Software Working Group, and focuses on advancing science at the intersection of domains and computation. He is the founder of scikit-image and co-author of Elegant SciPy. van der Walt has been developing scientific open source software for more than a decade, focusing mainly on Python packages such as NumPy & SciPy. Until May 2014, van der Walt was a lecturer in applied mathematics at Stellenbosch University in the Vision and Learning Group. Most of his software can be found on GitHub, including most of his Python for science lectures. His publications are listed on Google Scholar.
18:55COIMG-033
TomoPy: A Python framework for tomographic imaging, Doga Gursoy, Argonne National Laboratory (United States)
Quanta Image Sensing
Session Chair:
Stanley Chan, Purdue University (United States)
19:45 – 20:45
Red Room
19:45COIMG-046
Dynamic low-light imaging with Quanta Image Sensors, Yiheng Chi1, Abhiram Gnanasambandam1, Vladlen Koltun2, and Stanley Chan1; 1Purdue University and 2Intel Labs (United States)
20:05COIMG-047
Image classification in the dark using Quanta Image Sensors, Abhiram Gnanasambandam and Stanley Chan, Purdue University (United States)
20:25COIMG-048
Addressing bottlenecks in algorithms with tensor Kronecker product structure, Charles Colley1, Huda Nassar2, and David Gleich1; 1Purdue University and 2Stanford University (United States)
Tuesday 19 January 2021
PLENARY: Deep Internal Learning—Deep Learning with Zero Examples
Session Chair: Charles Bouman, Purdue University (United States)
10:00 – 11:10
Plenary Room
Deep internal learning—Deep learning with zero examples
Michal Irani, Professor in the Department of Computer Science and Applied Mathematics at the Weizmann Institute of Science (Israel)
Michal Irani is a professor at the Weizmann Institute of Science. Her research interests include computer vision, AI, and deep learning. Irani's prizes and honors include the Maria Petrou Prize (2016), the Helmholtz “Test of Time Award” (2017), the Landau Prize in AI (2019), and the Rothschild Prize in Mathematics and Computer Science (2020). She also received the ECCV Best Paper Awards (2000 and 2002), and the Marr Prize Honorable Mention (2001 and 2005).
11:10 – 11:40 SESSION BREAK: Join speakers in the EI2021 Discord Voice Channel corresponding to the color of the room in which the session occurs or join an Open Discord Channel of your choice. After a plenary, join the Plenary Discord Voice Channel.
In Situ Sensing and Analysis for Autonomous Materials Research
Session Chair:
Gregery Buzzard, Purdue University (United States)
11:40 – 13:00
Red Room
11:40COIMG-082
Super-resolution for paired electron microscopic images, Yu Ding, Texas A&M University College Station (United States)
12:00COIMG-083
Integrating machine learning and three-dimensional chemical imaging to extract latent features in material structures, Baishakhi Mazumder, University at Buffalo (United States)
12:20COIMG-084
Data-driven approaches for high-throughput experiment and analyses, Samantha Daly and Zhe Chen, University of California, Santa Barbara (United States)
12:40COIMG-085
Automated analysis of transmission electron microscopy images using machine learning methods, James Horwath1, Rémi Megrét2, Dmitri Zakharov3, and Eric Stach1; 1University of Pennsylvania (United States), 2University of Puerto Rico, Río Piedras (Puerto Rico), and 3Brookhaven National Laboratory (United States)
COIMG Wine and Cheese Social
Hosts:
Charles Bouman and Gregery Buzzard, Purdue University, and Begum Gulsoy, Northwestern University (United States)
13:00 – 14:30
See Gather link in notes
The link is https://gather.town/app/85l5TbzDEereE2xf/COIMG-social
The password is computationalimaging
14:30 – 18:00 Break in program to accommodate time zones.
Imaging through Turbulent & Scattering Mediums I
Session Chair:
Casey Pellizzari, United States Air Force Academy (United States)
18:00 – 19:15
Red Room
18:00
Conference Introduction
18:15COIMG-076
Learning deep speckle correlation with an interpretable deep neural network, Lei Tian, Boston University (United States)
18:35COIMG-077
Image reconstruction of static and dynamic scenes through anisoplanatic turbulence, Zhiyuan Mao, Nicholas Chimitt, and Stanley Chan, Purdue University (United States)
18:55COIMG-078
Simulating anisoplanatic turbulence by sampling inter-modal and spatially correlated Zernike coefficients, Nicholas Chimitt and Stanley Chan, Purdue University (United States)
Imaging through Turbulent & Scattering Mediums II
Session Chair:
Casey Pellizzari, United States Air Force Academy (United States)
19:45 – 20:45
Red Room
19:45COIMG-079
LUCID: Multi-frame blind deconvolution accelerated with graphical processing units, Michael Werth1, Brandoch Calef1, Kevin Roe1, and Amanda Conti2; 1Boeing Defense Space and Security and 2Air Force Research Laboratory (United States)
20:05COIMG-080
Recovering atmospheric image motion in the extreme faint limit, Michael Hart, HartSCI LLC (United States)
20:25COIMG-081
Long range tracking with computational 2.5-D imagery, Jason Schmidt1, Mitchell Grose1, Yakov Diskin1, Joseph Riley1, Matthias Banet2, and James Fienup2; 1MZA Associates Corporation and 2University of Rochester (United States)
Wednesday 20 January 2021
11:15 – 11:45 SESSION BREAK: Join speakers in the EI2021 Discord Voice Channel corresponding to the color of the room in which the session occurs or join an Open Discord Channel of your choice. After a plenary, join the Plenary Discord Voice Channel.
11:15 – 11:45 Women-in-Engineering Speed Networking (Morning) - take a break from technical sessions to make new connections and greet old friends. Look for the ZOOM link in Discord #announcements.
14:15 – 18:00 Break in program to accommodate time zones.
Imaging through Turbulent & Scattering Mediums III
Session Chair:
Casey Pellizzari, United States Air Force Academy (United States)
19:45 – 20:45
Red Room
19:45COIMG-125
Single-shot 3D holographic particle localization using deep priors trained on simulated data, Waleed Tahir1, Simon Gilbert1, Hao Wang1, Jiabei Zhu1, Ulugbek Kamilov2, and Lei Tian1; 1Boston University and 2Washington University in St. Louis (United States)
20:05COIMG-126
Experiments on active imaging through fog, Samuel Thurman1, Andrew Bratcher1, Bruce Tiemann1, Dawson Chung1, Samuel Park2, James Lindle3, Abbie Watnik2, and Paul Lebow4; 1Lockheed Martin Coherent Technologies, 2U.S. Naval Research Laboratory, 3DCS Corporation, and 4Alaire Technologies Inc. (United States)
20:25COIMG-127
Revealing subcellular structures with live-cell and 3D fluorescence nanoscopy, Fang Huang, Purdue University (United States)
Thursday 21 January 2021
PLENARY: The Development of Integral Color Image Sensors and Cameras
Session Chair: Jonathan B. Phillips, Google Inc. (United States)
10:00 – 11:10
Plenary Room
The development of integral color image sensors and cameras
Kenneth A. Parulski, Expert Consultant: Mobile Imaging (United States)
Kenneth Parulski is an expert consultant to mobile imaging companies and leads the development of ISO standards for digital photography. He joined Kodak in 1980 after graduating from MIT and retired in 2012 as research fellow and chief scientist in Kodak's digital photography division. His work has been recognized with a Technical Emmy and other major awards. Parulski is a SMPTE fellow and an inventor on more than 225 US patents.
11:10 – 11:40 SESSION BREAK: Join speakers in the EI2021 Discord Voice Channel corresponding to the color of the room in which the session occurs or join an Open Discord Channel of your choice. After a plenary, join the Plenary Discord Voice Channel.
AI-driven Imaging Instruments I
Session Chair:
Doga Gursoy, Argonne National Laboratory Advanced Photon Source (United States)
11:40 – 13:00
Red Room
11:40COIMG-145
The physical search engine: AI for explorative 3D imaging, Joost Batenburg, University of Leiden (the Netherlands)
12:00COIMG-146
Data versus physical models in computational optical imaging, Demetri Psaltis, Ecole Polytechnique Federale de Lausanne (Switzerland)
12:20COIMG-147
Deep learning and image restoration: A match made in heaven or hell?, Sabine Süsstrunk, Ecole Polytechnique Federale de Lausanne (Switzerland)
12:40COIMG-148
Self-supervised deep learning for ptychography without reference data, Selin Aslan, Zhengchun Liu, Tekin Bicer, and Doga Gursoy, Argonne National Laboratory (United States)
Imaging through Turbulent & Scattering Mediums IV
Session Chair:
Casey Pellizzari, United States Air Force Academy (United States)
13:30 – 14:30
Red Room
13:30
Conference Introduction
13:35COIMG-351
Reconstruction problems in medical and optical imaging: Evaluating filters for suppression for Gibbs Ringing, Yue Wang, University College Dublin (Ireland)
13:50COIMG-165
Imaging through deep turbulence using digital holography experiments, Mark Spencer1 and Casey Pellizzari2; 1Air Force Research Laboratory Directed Energy Directorate and 2United States Air Force Academy (United States)
14:10COIMG-166
Robustness of Fourier ptychographic imaging to variation of system parameters, Moritz Siegel1,2, Lukas Traxler1, and Laurin Ginner1; 1AIT Austrian Institute of Technology GmbH and 2Technische Universitat Wien (Austria)
14:30 – 18:00 Break in program to accommodate time zones.
AI-driven Imaging Instruments II
Session Chair:
Singanallur Venkatakrishnan, Oak Ridge National Laboratory (United States)
18:00 – 19:15
Red Room
18:00
Conference Introduction
18:35COIMG-150
Modeling brain structure and organization across many spatial scales, Eva Dyer, Georgia Institute of Technology (United States)
18:55COIMG-347
Stability analysis of data and image domain learning-based reconstruction approaches, Muhammad Usman Ghani and W. Clem Karl, Boston University (United States)
KEYNOTE: AI-driven Imaging Instruments
Session Chair: Gregery Buzzard, Purdue University (United States)
19:45 – 20:25
Red Room
COIMG-169
KEYNOTE: Deep networks from first principles, Yi Ma, University of California at Berkeley (United States)
Keynote speaker Yi Ma received his BS in automation and applied mathematics from Tsinghua University, China (1995), an MS in EECS (1997), an MA in Mathematics (2000), and a PhD in EECS (2000) all from UC Berkeley. He was on the faculty of ECE Department of the University of Illinois at Urbana-Champaign from 2000 to 2011. He was the manager of the Visual Computing Group and a principal researcher of Microsoft Research in Asia from 2009 to 2013. He was then a founding professor and the executive dean of the School of Information Science and Technology of ShanghaiTech University from 2014 to 2017. He joined the faculty of EECS of UC Berkeley in 2018.
Monday 25 January 2021
PLENARY: Making Invisible Visible
Session Chair: Jonathan B. Phillips, Google Inc. (United States)
10:00 – 11:10
Plenary Room
Making invisible visible
Ramesh Raskar, Associate Professor, MIT Media Lab (United States)
Ramesh Raskar is an associate professor at MIT Media Lab and directs the Camera Culture research group. His focus is on AI and imaging for health and sustainability. They span research in physical (e.g., sensors, health-tech), digital (e.g., automated and privacy-aware machine learning), and global (e.g., geomaps, autonomous mobility) domains. He received the Lemelson Award (2016), ACM SIGGRAPH Achievement Award (2017), DARPA Young Faculty Award (2009), Alfred P. Sloan Research Fellowship (2009), TR100 Award from MIT Technology Review (2004), and Global Indus Technovator Award (2003). He has worked on special research projects at Google [X] and Facebook and co-founded/advised several companies.
11:10 – 11:40 SESSION BREAK: Join speakers in the EI2021 Discord Voice Channel corresponding to the color of the room in which the session occurs or join an Open Discord Channel of your choice. After a plenary, join the Plenary Discord Voice Channel.
Image Modeling for Inverse Problems
Session Chair:
Charles Bouman, Purdue University (United States)
11:40 – 13:00
Red Room
11:40COIMG-202
Deep probabilistic imaging: Uncertainty quantification and multi-modal solution characterization for computational imaging, He Sun and Katherine Bouman, California Institute of Technology (United States)
12:00COIMG-200
One size fits all: Can we train one denoiser for all noise levels?, Abhiram Gnanasambandam and Stanley Chan, Purdue University (United States)
12:20COIMG-201
Model-based Bayesian deep learning architecture for linear inverse problems in computational imaging, Canberk Ekmekci and Mujdat Cetin, University of Rochester (United States)
12:40COIMG-199
Plug-and-play and equilibrium methods demystified, Gregery Buzzard1, Charles Bouman1, and Brendt Wohlberg2; 1Purdue University and 2Los Alamos National Laboratory (United States)
Computational Imaging for Materials Applications I
Session Chair:
Mary Comer, Purdue University (United States)
13:30 – 14:30
Red Room
13:30COIMG-187
Self-supervised curriculum learning for fiber tracking in composite materials, Hongkai Yu, Cleveland State University (United States)
13:50COIMG-188
3D fiber detection using deep center regression and geometric clustering, Camilo Aguilar Herrera1 and Mary Comer2; 1INRIA, Sophia Antipolis (France) and 2Purdue University (United States)
14:10COIMG-189
Stochastic plug-and-play algorithms for solving image reconstruction problems for analyzing microscope imagery, Vincent Monardo1, Sean Donegan2, Marc De Graf1, and Yuejie Chi1; 1Carnegie Mellon University and 2Air Force Research Laboratory, Wright-Patterson AFB (United States)
14:30 – 18:00 Break in program to accommodate time zones.
Computational Imaging for Materials Applications II
Session Chair:
Emine Gulsoy, Northwestern University ()
18:00 – 19:15
Red Room
18:00
Conference Introduction
18:15COIMG-190
Multi-resolution data fusion for transmission electron microscopy, Emma Reid1, Gregery Buzzard1, Lawrence Drummy2, and Charles Bouman1; 1Purdue University and 2Air Force Research Laboratory (United States)
18:35COIMG-191
Physics-regularization in machine learning, Stephen Niezgoda, The Ohio State University (United States)
18:55COIMG-192
GANs for synthetic microstructure generation, Megna Shah, Austin Gerlt, Jeffrey Simmons, and Eric Payton, Air Force Research Laboratory (United States)
Computational Imaging for Materials Applications III
Session Chair:
Jeffrey Simmons, Air Force Research Laboratory (United States)
19:45 – 20:45
Red Room
19:45COIMG-193
Computer vision and machine learning for image data in materials science, Elizabeth Holm, Ryan Cohn, Nan Gao, Katelyn Jones, Bo Lei, and Srujana Yarasi, Carnegie Mellon University (United States)
20:05COIMG-194
JIST-first: Evaluating the utility of Mueller matrix imaging for diffuse material classification, Meredith Kupinski and Lisa Li, The University of Arizona (United States)
20:25COIMG-195
JIST-first: Limitations of CNNs for approximating the ideal observer despite quantity of training data or depth of network, Khalid Omer, Luca Caucci, and Meredith Kupinski, The University of Arizona (United States)
Tuesday 26 January 2021
11:15 – 11:45 SESSION BREAK: Join speakers in the EI2021 Discord Voice Channel corresponding to the color of the room in which the session occurs or join an Open Discord Channel of your choice. After a plenary, join the Plenary Discord Voice Channel.
14:15 – 18:00 Break in program to accommodate time zones.
CT Imaging
Session Chair:
Selin Aslan, Argonne National Laboratory (United States)
18:00 – 19:15
Red Room
18:00
Conference Introduction
18:15COIMG-228
Modular X-ray CT reconstruction with coded exposure, Soumendu Majee1, Selin Aslan2, Charles Bouman1, and Doga Gursoy2; 1Purdue University and 2Argonne National Laboratory (United States)
18:35COIMG-229
Enhanced material estimation with multi-spectral CT, Sandamali Devadithya and David Castañón, Boston University (United States)
18:55COIMG-230
Sparse view CT with total variation priors in cylindrical coordinates, Maliha Hossain1, Charles Bouman1, Marc Klasky2, and Brendt Wohlberg2; 1Purdue University and 2Los Alamos National Laboratory (United States)
Physics-informed Reconstruction I
Session Chair:
Katherine Bouman, California Institute of Technology (United States)
19:45 – 20:45
Red Room
19:45COIMG-249
Diffusion imaging by Fourier transform fluorescence recovery after photobleaching, Andreas Geiger, Randy Akrofi, and Garth Simpson, Purdue University (United States)
20:05COIMG-250
Large-scale holographic 3D particle localization based on the multi-slice beam propagation model, Hao Wang, Waleed Tahir, Jiabei Zhu, and Lei Tian, Boston University (United States)
20:25COIMG-251
Imaging fluid-dynamics by stochastic model fitting, Aviad Levis1, Daeyoung Lee2, Charles Gammie2, and Katherine Bouman1; 1California Institute of Technology and 2University of Illinois Urbana-Champaign (United States)
Wednesday 27 January 2021
PLENARY: Revealing the Invisible to Machines with Neuromorphic Vision Systems: Technology and Applications Overview
Session Chair: Radka Tezaur, Intel Corporation (United States)
10:00 – 11:10
Plenary Room
Revealing the invisible to machines with neuromorphic vision systems: Technology and applications overview
Luca Verre, CEO and Co-Founder at Prophesee (France)
Luca Verre is co-founder and CEO of Prophesee, the inventor of the world’s most advanced neuromorphic vision systems. Verre is a World Economic Forum technology pioneer. His experience includes project and product management, marketing, and business development roles at Schneider Electric. Prior to Schneider Electric, Verre worked as a research assistant in photonics at the Imperial College of London. Verre holds a MSc in physics, electronic and industrial engineering from Politecnico di Milano and Ecole Centrale and an MBA from Institut Européen d'Administration des Affaires, INSEAD.
11:10 – 11:40 SESSION BREAK: Join speakers in the EI2021 Discord Voice Channel corresponding to the color of the room in which the session occurs or join an Open Discord Channel of your choice. After a plenary, join the Plenary Discord Voice Channel.
13:00 – 13:30 SESSION BREAK: Join speakers in the EI2021 Discord Voice Channel corresponding to the color of the room in which the session occurs or join an Open Discord Channel of your choice. After a plenary, join the Plenary Discord Voice Channel.
14:30 – 18:00 Break in program to accommodate time zones.
Physics-informed Reconstruction II
Session Chair:
Zachary Levine, National Institute of Standards and Technology (United States)
18:00 – 19:15
Red Room
18:00
Conference Introduction
18:15COIMG-288
Leveraging multi-agent consensus equilibrium for quantum chemistry, James Ulcickas1, Ziyi Cao2, Jiayue Rong2, Charles Bouman2, Lyudmila Slipchenko2, Gregery Buzzard2, and Garth Simpson2; 1Northrop Grumman Corporation and 2Purdue University (United States)
18:35COIMG-289
Physics-embedded deep learning for intensity diffraction tomography under multiple scattering, Alex Matlock and Lei Tian, Boston University (United States)
18:55COIMG-290
Deep learning approach for dynamic sparse sampling in mass spectrometry imaging, David Helminiak1, Hang Hu2, Julia Laskin2, and Dong Hye Ye1; 1Marquette University and 2Purdue University (United States)
19:15 – 19:45 SESSION BREAK: Join speakers in the EI2021 Discord Voice Channel corresponding to the color of the room in which the session occurs or join an Open Discord Channel of your choice. After a plenary, join the Plenary Discord Voice Channel.
19:15 – 19:45 Women-in-Engineering Speed Networking (Evening) - take a break from technical sessions to make new connections and greet old friends. Look for the ZOOM link in Discord #announcements.
Physics-informed Reconstruction III
Session Chair:
Garth Simpson, Purdue University (United States)
19:45 – 20:45
Red Room
19:45COIMG-291
Testing the goodness of model fit in tunable diode laser absorption tomography, Zeeshan Nadir1, Kristin Rice2, Michael Brown2, and Charles Bouman3; 1Samsung Research America, 2Air Force Research Labs, and 3Purdue University (United States)
20:05COIMG-292
X-ray computed tomography using partially coherent Fresnel diffraction with application to an optical fiber, Zachary Levine, National Institute of Standards and Technology (United States)
20:25COIMG-293
Reducing motion artifact in sequential-scan dual-energy CT imaging by incorporating deformable registration within joint statistical image reconstruction, Tao Ge1, Rui Liao1, David Politte2, Maria Medrano1, Jeffrey Williamson1, Bruce Whiting3, Tianyu Zhao2, and Joseph O’Sullivan1; 1Washington University in St. Louis, 2Washington University School of Medicine, and 3University of Pittsburgh (United States)