Pitt | Swanson Engineering

Join With Us In Celebrating Our 2020 Graduating Class! 

Since its founding in 1893 by two legends, George Westinghouse and Reginald Fessenden, the Department of Electrical and Computer Engineering at Pitt has excelled in education, research, and service.  Today, the department features innovative undergraduate and graduate programs and world-class research centers and labs, combining theory with practice at the nexus of computer and electrical engineering, for our students to learn, develop, and lead lives of impact.


Read our latest newsletter below




Jul
2
2020

The Department of Energy Awards $1.9M to Swanson School Faculty and Students for Nuclear Energy Research

Electrical & Computer, MEMS, Student Profiles, Nuclear

PITTSBURGH (July 2, 2020) … Humankind is consuming more energy than ever before, and with this growth in consumption, researchers must develop new power technologies that will address these needs. Nuclear power remains a fast-growing and reliable sector of clean, carbon-free energy, and four researchers at the University of Pittsburgh received awards to further their work in this area. The U.S. Department of Energy (DOE) invested more than $65 million to advance nuclear technology, announced June 16, 2020. Pitt’s Swanson School of Engineering received a total of $1,868,500 in faculty and student awards from the DOE’s Nuclear Energy University Program (NEUP). According to the DOE, “NEUP seeks to maintain U.S. leadership in nuclear research across the country by providing top science and engineering faculty and their students with opportunities to develop innovative technologies and solutions for civil nuclear capabilities.” “Historically, our region has been a leader in the nuclear energy industry, and we are trying to keep that tradition alive at the Swanson School by being at the forefront of this field,” said Heng Ban, Richard K. Mellon Professor of Mechanical Engineering and director of the Swanson School’s Stephen R. Tritch Nuclear Engineering Program. “I’m thrilled that the Department of Energy has recognized the innovative work from our faculty, and I look forward to seeing the advancements that arise from this research.” The DOE supported three projects from the Swanson School. High Temperature Thermophysical Property of Nuclear Fuels and MaterialsPI: Heng Ban, Richard K. Mellon Professor of Mechanical Engineering, Director of Stephen R. Tritch Nuclear Engineering Program$300,000 Ban, a leading expert in nuclear material thermal properties and reactor instrumentation and measurements, will use this award to enhance research at Pitt by filling an infrastructure gap.  He will purchase key equipment to strengthen core nuclear capability in the strategic thrust area of instrumentation and measurements. A laser flash analyzer and a thermal mechanical analyzer (thermal expansion) will be purchased as a tool suite for complete thermophysical property information. Fiber Sensor Fused Additive Manufacturing for Smart Component Fabrication for Nuclear Energy PI: Kevin Chen, Paul E. Lego Professor of Electrical and Computer EngineeringCo-PI: Albert To, William Kepler Whiteford Professor of Mechanical Engineering and Materials Science$1,000,000 The Pitt research team will utilize unique technical capabilities developed in the SSoE to lead efforts in sensor-fused additive manufacturing for future nuclear energy systems. Through integrated research efforts in radiation-harden distributed fiber sensor fabrication, design and optimization algorithm developments, and additive manufacturing innovation, the team will deliver smart components to nuclear energy systems to harness high spatial resolution data. This will enable artificial intelligence based data analytics for operation optimization and condition-based maintenance for nuclear power systems. Multicomponent Thermochemistry of Complex Chloride Salts for Sustainable Fuel Cycle TechnologiesPI: Wei Xiong, assistant professor of mechanical engineering and materials scienceCo-PIs: Prof. Elizabeth Sooby Wood (University of Texas at San Antonio), Dr. Toni Karlsson (Idaho National Laboratory), and Dr. Guy Fredrickson (Idaho National Laboratory)$400,000 Nuclear reactors help bring clean water and reliable energy to communities across the world. Next-generation reactor design, especially small modular reactors, will be smaller, cheaper, and more powerful, but they will require high-assay low-enriched uranium (HALEU) as fuel. As the demand for HALEU is expected to grow significantly, Xiong’s project seeks to improve the process of recovering uranium from spent nuclear fuels to produce HALEU ingots. Part of the process involves pyrochemical reprocessing based on molten salt electrolysis. Hence, developing a thermodynamic database using the CALPHAD (Calculation of Phase Diagrams) approach to estimate the solubilities of fission product chloride salts into the molten electrolyte is essential for improving the process efficiency. The results will help in estimating the properties that are essential for improving the HALEU production and further support the development of chloride molten salt reactors. Two Swanson School students also received awards from NEUP. Jerry Potts, a senior mechanical engineering student, received a $7,500 nuclear energy scholarship, one of 42 students in the nation. Iza Lantgios (BS ME ‘20), a matriculating mechanical engineering graduate student, was one of 34 students nationwide to be awarded a $161,000 fellowship. Swanson School students have secured 20 NEUP scholarships and fellowships since 2009. # # #

Jun
25
2020

Making a Sustainable Impact Throughout Pitt and Our Communities

All SSoE News, Bioengineering, Chemical & Petroleum, Civil & Environmental, Electrical & Computer, Industrial, MEMS, Student Profiles, Office of Development & Alumni Affairs

"MCSI remains committed to addressing global sustainability issues, connecting our domestic and international pursuits to create synergies locally, nationally, and internationally. We hope you enjoy this summary of the past year’s impacts, and we'd be happy to answer any questions you might have about the report's contents and MCSI's programs."

Jun
23
2020

Five Pitt Researchers Receive PA Department of Community and Economic Development Grants

Electrical & Computer, MEMS

PITTSBURGH (June 23, 2020) — Five researchers at the University of Pittsburgh Swanson School of Engineering have received grants from the Pennsylvania Department of Community and Economic Development (DCED) through the Manufacturing PA initiative. The DCED has approved more than $2.8 million in grants to 43 projects that will “spur new technologies and processes in the manufacturing sector,” according to their press release. “As engineers, we are applied scientists, and our singular goal in performing research is to produce public impact,” said David Vorp, associate dean for research and John A. Swanson Professor of bioengineering. “I am proud that the Commonwealth of Pennsylvania saw the potential of these projects by our Swanson School faculty and their industrial partners to have benefit to their citizens.” The five researchers to receive funding at the Swanson School are: Kevin Chen, Paul E. Lego Professor of Electrical and Computer Engineering$67,991—Femtosecond Laser Manufacturing of 3D Photonics Components in Nonlinear Optical Substrates for Electro-Optic Applications Markus Chmielus, associate professor of mechanical engineering and materials science$70,000—Improving 3D Binder Jet Printed Tungsten-Carbide Parts via Strategies to Increase Green Density and Strength Jung-Kun Lee, professor of mechanical engineering and materials science$70,000—Smart Crucible: Monitoring Damage of Crucibles by Embedded Electric Resistance Sensor Albert To, associate professor of mechanical engineering and materials science$69,450—A Computational Tool for Simulating the Sintering Behavior in Binder Jet Additive Manufacturing Xiayun Zhao, assistant professor of mechanical engineering and materials science$70,000—Pushing the Boundaries of Ceramic Additive Manufacturing (CAM) with Visible light initiated Polymerization (ViP)
Maggie Pavlick
Jun
18
2020

Researching resilience

Electrical & Computer

Grid and infrastructure resilience are increasingly important, while a relatively ‘new concept’ in terms of today’s modern grid, and its dynamic environment. With the increase in natural disasters, and as the northern hemisphere goes into what is commonly known as ‘storm season’, Smart Energy International spoke with Dr. Alexis Kwasinski, Associate Professor at the Department of Electrical and Computer Engineering at the University of Pittsburgh. Kwasinski specializes in grid resilience research in areas prone to natural disasters and extreme weather. Read the full article.
Smart Energy International Issue 3 2020
Jun
10
2020

Pitt ECE Professor Receives $300K NSF Award to Develop 2D Synapse for Deep Neural Networks

Electrical & Computer

PITTSBURGH (June 10, 2020) — The world runs on data. Self-driving cars, security, healthcare and automated manufacturing all are part of a “big data revolution,” which has created a critical need for a way to more efficiently sift through vast datasets and extract valuable insights. When it comes to the level of efficiency needed for these tasks, however, the human brain is unparalleled. Taking inspiration from the brain, Feng Xiong, assistant professor of electrical and computer engineering at the University of Pittsburgh’s Swanson School of Engineering, is collaborating with Duke University’s Yiran Chen to develop a two-dimensional synaptic array that will allow computers to do this work with less power and greater speed. Xiong has received a $300,000 award from the National Science Foundation for this project. “Deep neural networks (DNN) work by training a neural network with massive datasets for applications like pattern recognition, image reconstruction or video and language processing,” said Xiong. “For example, if airport security wanted to create a program that could identify firearms, they would need to input thousands of pictures of different firearms in different situations to teach the program what it should look for. It’s not unlike how we as humans learn to identify different objects.” To do this, supercomputing systems transfer data back and forth constantly from the computation and memory units, making DNNs computationally intensive and power hungry. Their inefficiency makes it impractical for them to be scaled up to the level of the complexity needed for true artificial intelligence (AI). In contrast, computation and memory in the human brain uses a network of neurons and synapses that are closely and densely connected, resulting in the brain’s extremely low power consumption, about 20W. “The way our brains learn is gradual. For example, say you’re learning what an apple is. Each time you see the apple, it might be in a different context: on the ground, on a table, in a hand. Your brain learns to recognize that it’s still an apple,” said Xiong. “Each time you see it, the neural connection changes a bit. In computing we want this high-precision synapse to mimic that, so that over time, the connections strengthen. The finer the adjustments we can make, the more powerful the program can be, and the more memory it can have.” With existing consumer electronic devices, the kind of gradual, slight adjustment needed is difficult to attain because they rely on binary, meaning their states are essentially limited to on or off, yes or no. The artificial synapse will instead allow a precision of 1,000 states, with precision and control in navigating between each. Additionally, smaller devices, like sensors and other embedded systems, need to communicate their data to a larger computer to process it. The proposed device’s small size, flexibility and low power usage could make it able to run those calculations in much smaller devices, allowing sensors to process information on-site. “What we’re proposing is that, theoretically, we could lower the energy needed to run these algorithms, hopefully by 1,000 times or more. This way, it can make power requirement more reasonable, so a flexible or wearable electronic device could run it with a very small power supply,” said Xiong. The project, titled “Collaborative Research: Two-dimensional Synapatic Array for Advanced Hardware Acceleration of Deep Neural Networks,” is expected to last three years, beginning on Sept. 1, 2020.
Maggie Pavlick

Upcoming Events


back
view more