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.


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Oct
22
2020

Pitt to collaborate on new artificial intelligence study of Alzheimer’s

Bioengineering, Electrical & Computer

Heng Huang, John A. Jurenko Endowed Professor of Electrical and Computer Engineering at the Swanson School of Engineering, will lead the University of Pittsburgh research on a collaborative study awarded to the University of Southern California's Mark and Mary Stevens Neuroimaging Informatics Institute. “Current analytic methods have not kept pace with the vast amount and high complexity of data that is being collected on Alzheimer’s disease,” said Huang, who also holds an appointment in the Department of Biomedical Informatics at Pitt. “As a pioneer scientist with more than 15 years of experience in machine learning and biomedical data science, I am the main leader of the advanced AI and machine learning techniques developed in this project.” His award is in collaboration with Liang Zhan, assistant professor of electrical and computer engineering at Pitt. The joint project has six dedicated core teams that will focus on ultra-scale genomics, imaging, and cognitive data analysis. The Pitt team will lead the AI&ML core and the Genomic Sequencing Data Analysis core while also contributing to the Imaging Genetics core. # # # Reposted with permission. Click here to view the University of Southern California's original story. USC leads massive new artificial intelligence study of Alzheimer’s By Zara Greenbaum A massive problem like Alzheimer’s disease (AD)—which affects nearly 50 million people worldwide—requires bold solutions. New funding expected to total $17.8 million awarded to USC’s Mark and Mary Stevens Neuroimaging Informatics Institute and its collaborators is one key piece of that puzzle. The five-year National Institutes of Health (NIH)-funded effort, “Ultrascale Machine Learning to Empower Discovery in Alzheimer’s Disease Biobanks,” known as AI4AD, will develop state-of-the-art artificial intelligence (AI) methods and apply them to giant databases of genetic, imaging and cognitive data collected from AD patients. Forty co-investigators at 11 research centers will team up to leverage AI and machine learning to bolster precision diagnostics, prognosis and the development of new treatments for AD. “Our team of experts in computer science, genetics, neuroscience and imaging sciences will create algorithms that analyze data at a previously impossible scale,” says Paul Thompson, associate director of the USC INI and project leader for the new grant. “Collectively, this will enable the discovery of new features in the genome that influence the biological processes involved in Alzheimer’s disease.” Predicting a diagnosis The project’s first objective is to identify genetic and biological markers that predict an AD diagnosis—and to distinguish between several subtypes of the disease. To accomplish this, the research team will apply sophisticated AI and machine learning methods to a variety of data types, including tens of thousands of brain images and whole genome sequences. The investigators will then relate these findings to the clinical progression of AD, including in patients who have not yet developed dementia symptoms. The researchers will train AI methods on large databases of brain scans to identify patterns that can help detect the disease as it emerges in individual patients. “As we get older, each of us has a unique mix of brain changes that occur for decades before we develop any signs of Alzheimer’s disease–changes in our blood vessels, the buildup of abnormal protein deposits and brain cell loss”, says Thompson, who also directs the USC INI’s Imaging Genetics Center. “Our new AI methods will help us determine what changes are happening in each patient, as well as drivers of these processes in their DNA, that we can target with new drugs.” The team is even creating a dedicated “Drug Repurposing Core” to identify ways to repurpose existing drugs to target newly identified segments of the genome, molecules or neurobiological processes involved in the disease. “We predict that combining AI with whole genome data and advanced brain scans will outperform methods used today to predict Alzheimer’s disease progression,” says Thompson. Advancing AI The AI4AD effort is part of the “Cognitive Systems Analysis of Alzheimer's Disease Genetic and Phenotypic Data” and “Harmonization of Alzheimer’s Disease and Related Dementias (AD/ADRD) Genetic, Epidemiologic, and Clinical Data to Enhance Therapeutic Target Discovery” initiatives from the NIH’s National Institute on Aging. These initiatives aim to create and develop advanced AI methods, and apply them to extensive and harmonized rich genomic, imaging, and cognitive data. Collectively, the goals of AI4AD leverage the promise of machine learning to contribute to precision diagnostics, prognostication, and targeted and novel treatments. Thompson and his USC team will collaborate with four co-principal investigators at the University of Pennsylvania, the University of Pittsburgh and the Indiana University School of Medicine. The researchers will also host regular training events at major AD neuroimaging and genetics conferences to help disseminate newly developed AI tools to investigators across the field. Research reported in this publication will be supported by the National Institute on Aging of the National Institutes of Health under Award Number U01AG068057. Also involved in the project are INI faculty members Neda Jahanshad, PhD, and Lauren Salminen, PhD, as well as consortium manager Sophia Thomopoulos. # # #
Zara Greenbaum
Oct
21
2020

Pitt Engineering Alumnus Dedicates Major Gift Toward Undergraduate Tuition Support

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

PITTSBURGH (October 21, 2020) …  An eight-figure donation from an anonymous graduate of the Swanson School of Engineering and spouse to the University of Pittsburgh Swanson School of Engineering in their estate planning to provide financial aid to undergraduate students who are enrolled in the Pitt EXCEL Program. Announced today by Pitt Chancellor Patrick Gallagher and US Steel Dean of Engineering James R. Martin II, the donors beques will provide tuition support for underprivileged or underrepresented engineering students who are residents of the United States of America and in need of financial aid. “I am extremely grateful for this gift, which supports the University of Pittsburgh’s efforts to tackle one of society’s greatest challenges—the inequity of opportunity,” Gallagher said. “Put into action, this commitment will help students from underrepresented groups access a world-class Pitt education and—in doing so—help elevate the entire field of engineering.” “Our dedication as engineers is to create new knowledge that benefits the human condition, and that includes educating the next generation of engineers. Our students’ success informs our mission, and I am honored and humbled that our donors are vested in helping to expand the diversity of engineering students at Pitt,” Martin noted. “Often the most successful engineers are those who have the greatest need or who lack access, and support such as this is critical to expanding our outreach and strengthening the role of engineers in society.” A Gift to Prepare the Workforce of the Future Martin noted that the gift is timely because it was made shortly after Chancellor Gallagher’s call this past summer to create a more diverse, equitable, and inclusive environment for all, especially for the University’s future students. The gift – and the donors’ passion for the Swanson School – show that there is untapped potential as well as significant interest in addressing unmet need for students who represent a demographic shift in the American workforce.  “By 2050, when the U.S. will have a minority-majority population, two-thirds of the American workforce will require a post-secondary education,” Martin explained. “We are already reimagining how we deliver engineering education and research, and generosity such as this will lessen the financial burden that students will face to prepare for that future workforce.” A Half-Century of IMPACT on Engineering Equity In 1969 the late Dr. Karl Lewis (1/15/1936-3/5/2019) founded the IMPACT Program at the University of Pittsburgh to encourage minority and financially and culturally disadvantaged students to enter and graduate from the field of engineering. The six-week program prepared incoming first year students through exposure to university academic life, development of study skills, academic and career counseling, and coursework to reinforce strengths or remedy weaknesses. Many Pitt alumni today still note the role that Lewis and IMPACT had on their personal and professional lives.  Under Lewis’ leadership, IMPACT sparked the creation of two award-winning initiatives within the Swanson School’s Office of Diversity: INVESTING NOW, a college preparatory program created to stimulate, support, and recognize the high academic performance of pre-college students from groups that are historically underrepresented in STEM majors. Pitt EXCEL, a comprehensive undergraduate diversity program committed to the recruitment, retention, and graduation of academically excellent engineering undergraduates, particularly individuals from groups historically underrepresented in the field. “Dr. Lewis, like so many of his generation, started a movement that grew beyond one person’s idea,” said Yvette Wisher, Director of Pitt EXCEL. “Anyone who talks to today’s EXCEL students can hear the passion of Dr. Lewis and see how exceptional these young people will be as engineers and individuals. They and the hundreds of students who preceded them are the reason why Pitt EXCEL is game-changer for so many.”  Since its inception, Pitt EXCEL has helped more than 1,500 students earn their engineering degrees and become leaders and change agents in their communities. Ms. Wisher says the most important concept she teaches students who are enrolled in the program is to give back however they can once they graduate—through mentorship, volunteerism, philanthropy, or advocacy.  Supporting the Change Agents of Tomorrow “Pitt EXCEL is a home - but more importantly, a family. The strong familial bonds within Pitt EXCEL are what attracted me to Swanson as a graduating high school senior, what kept me going throughout my time in undergrad and what keeps me energized to this very day as a PhD student,” explained Isaiah M. Spencer Williams, BSCE ’19 and currently a pre-doctoral student in the Swanson School’s Department of Civil and Environmental Engineering. “Pitt EXCEL is a family where iron sharpens iron and where we push each other to be the best that we can be every day. Beyond that, it is a space where you are not only holistically nurtured and supported but are also groomed to pave the way for and invest into those who are coming behind you.  “Pitt EXCEL, and by extension, Dr. Lewis' legacy and movement are the reasons why I am the leader and change agent that I am today. This generous gift will ensure a bright future for underrepresented engineering students in the Pitt EXCEL Program, and will help to continue the outstanding development of the change agents of tomorrow.”  Setting a Foundation for Community Support “Next year marks the 51st anniversary of IMPACT/EXCEL as well as the 175th year of engineering at Pitt and the 50th anniversary of Benedum Hall,” Dean Martin said. “The Swanson School of Engineering represents 28,000 alumni around the world, who in many ways are life-long students of engineering beyond the walls of Benedum, but who share pride in being Pitt Engineers. “The key to our future success is working together as a global community to find within ourselves how we can best support tomorrow’s students,” Martin concluded. “We should all celebrate this as a foundational cornerstone gift for greater engagement.” ###

Oct
1
2020

Pitt ECE Alumni Organize Indy Autonomous Challenge Entry

Electrical & Computer

Reposted with permission from Robotics Institute Summer Scholars. Original story here. ### Two members of the RISS Alumni Share Their Latest Robotics Project & Invite Your Participation Led by a group of motivated CMU Masters in Robotics students (MSR) and RI Summer Scholars (RISS) alumni, Panther AV RAS-ing is the University of Pittsburgh’s entry, a city-wide effort with virtual partners beyond our region’s borders,  in the Indy Autonomous Challenge, a competition devoted to developing software for an autonomous high-speed Indy car. We hope that by participating in this challenge, we can bring more people into the Pittsburgh robotics community. Our team is led by Nayana Suvarna, Josh Spisak, and Andrew Saba. Nayana, the University of Pittsburgh’s Robotics & Automation Society (RAS) President and a RISS 2020 Scholar, is the project lead and manages the project. Andrew, a former RAS officer, RISS 2019 Scholar, and future MSR student, provides technical mentorship to team members. Josh, an MSR student, also helps mentor the project technically. Relying on their experiences making robots at CMU and in RAS, our leaders believe our team is uniquely qualified to win this challenge, while also recognizing the importance of fostering robotics at Pitt and elsewhere. As part of the Indy Autonomous Challenge, our algorithms will be deployed on an Indy race car traveling over 120 mph on the Indianapolis Motor Speedway in 2021. This isn’t a single car race; instead, we will be racing head to head against other vehicles from schools such as MIT, TUM, ETH, and others. We feel that this competition will spark a greater interest in robotics at the University of Pittsburgh. We value participation for anyone and everyone, including those working remotely due to COVID, and students who may not have access to universities with dedicated robotics programs. There are many areas in which our team is skilled, including autonomous unmanned aerial and ground vehicles, SLAM and localization, motion planning and controls, perception, systems development, multi-agent systems, and fast aerial-flight. Our members developed this experience while participating in RAS projects such as the International Aerial Robotics Competition (IARC), which won first place at the American Venue in 2017 and 2018. Our members have also worked on many competitions at CMU, such as the DARPA Subterranean Challenge, MBZIRC, and AlphaPilot. In pursuing this challenge we are following in the footsteps of RAS alumni who have gone on to top-tier graduate schools, including CMU, UC Berkeley, University of Maryland, and the University of Pittsburgh. In addition, our members and alumni, including our team leads and mentors, have worked at cutting-edge robotics companies including Uber ATG, Argo AI, Aurora Innovations, Carnegie Robotics, IAMRobotics, Near Earth Autonomy, Neya Systems, RE2, Four Growers, Redzone Robotics, and Gecko Robotics, among many others. We are looking forward to continuing to lay the groundwork for our future endeavors, expanding our experience into the realm of high-speed vehicles, and bringing robotics to as many people as possible. Pushing the frontier of self-driving vehicles and artificial intelligence is not an easy task. Bringing our car over the finish line will take the support of many passionate roboticists and sponsors. Join the mission and bring autonomous high-speed head-to-head racing to Pittsburgh! In the age of Covid-19, there are many opportunities to contribute remotely or socially distanced. Technical expertise, communications, media, and sponsors are key to building, communicating, and supporting this journey. Connect with us and contribute your skills and resources to drive Pittsburgh autonomous racing to success! Reach out to us (Nayana Suvarna, Josh Spisak, or Andrew Saba) at [nsuvarna, jspisak, asaba]@andrew.cmu.edu. We look forward to hearing from you!

Sep
30
2020

Powering AI in Sensors with Energy Harvested from Nature

Electrical & Computer

In a city with 446 bridges, how do you effectively monitor the health of the structures that help residents navigate above Pittsburgh’s three rivers? Experts rely on remote sensors fastened beneath a bridge that continuously detect vibrations and produce data for structural health monitoring. These kinds of wireless, battery-operated devices are often placed in hard-to-reach areas, complicating maintenance. Researchers from the University of Pittsburgh and the University of Notre Dame want to apply artificial intelligence to extend the lifetime of sensors and devices deployed in remote areas. They received a $500,000 award from the National Science Foundation to support their work. “One of the major challenges with these sensors is battery replacement. Many times, it is costly, inconvenient, or even infeasible to replace or charge these batteries after deployment,” said Jingtong Hu, lead researcher on the study and associate professor of electrical and computer engineering at Pitt’s Swanson School of Engineering. Hu and the research team want to develop a way to save power on the remote sensor device by leveraging energy-harvesting technology, which sources power from the environment, such as solar, thermal, or wind. They plan to add a second, small sensor that can trigger a more robust device, thus saving energy and allowing users to change the battery less frequently. The smaller sensor -- powered by energy harvested from the environment -- will run unattended, and with the help of AI, it can be trained to recognize patterns and signal the larger device to turn on during a specific event. “The main device is programmed to do all of the legwork,” explained Hu. “The smaller sensor is the watchdog that can monitor the environment and wake up the larger sensor when necessary.” These devices have many applications, including monitoring and predicting natural disasters. Sensor technology is currently used to observe gases emitted by active volcanoes in some of the most remote parts of the planet. This requires researchers to take long, arduous hikes to reach the location -- all while wearing protective equipment to prevent damage to the skin and lungs from the extreme heat and corrosive gases. With Hu’s improvements, the researchers may be able to make trips such as these – whether to the tops of volcanoes or under bridge trusses –  less frequently. If successful, the project may ultimately allow these devices to be powered by the environment to help protect the environment. He will collaborate with Yiyu Shi, associate professor of computer science and engineering at the University of Notre Dame. “One of the main challenges of running AI algorithms with energy harvested from the environment is that the energy from the environment is intermittent,” Hu explained. “Much like a laptop, if the sensor loses power, you lose the data, so we want to help AI algorithms reach an accurate decision, even with intermittent power. “By applying AI, we hope to increase the lifespan of unattended sensors and make them more reliable and useful,” he said. # # #

Sep
28
2020

Four Pitt Engineering Researchers Receive NSF CAREER Awards in 2020 Funding Cycle

Bioengineering, Chemical & Petroleum, Electrical & Computer, MEMS

PITTSBURGH (September 28, 2020) … The University of Pittsburgh’s Swanson School of Engineering closed out the 2020 fiscal year with four faculty winning CAREER awards from the National Science Foundation. This brings the total to 15 CAREER awards received by Swanson School faculty since 2016. According to NSF, the Faculty Early Career Development (CAREER) Program is its most prestigious award in support of early-career faculty who have the potential to serve as academic role models in research and education and to lead advances in the mission of their department or organization. “I am incredibly proud of our young faculty for contributing to the Swanson School’s diverse research portfolio and achieving this important recognition in their early career,” said David Vorp, associate dean for research and the John A. Swanson Professor of Bioengineering. “Over the past few years, we have improved faculty resources for developing and applying for federal funding, and the number of CAREER recipients is a great indicator of our success.” The 2020 recipients include: Takashi D-Y Kozai, assistant professor of bioengineeringUncovering the Impact of Traditional and Novel Chronic Stimulation Modalities on Neural Excitability and Native Neuronal Network Function Dr. Kozai received a $437,144 CAREER award to improve the integration of the brain and technology in order to study long-standing questions in neurobiology and improve clinical applications of brain-computer interfaces. One of the challenges remaining with this technology is achieving long-term and precise stimulation of a specific group of neurons. Kozai has designed a wireless, light-activated electrodethat enables precise neural circuit probing while minimizing tissue damage. The funding will enable him to further improve this technology. Sangyeop Lee, assistant professor of mechanical engineering and materials science Machine Learning Enabled Study of Thermal Transport in Polycrystalline Materials from First Principles Dr. Lee’s $500,000 CAREER award will utilize machine learning to model thermal transport in polycrystalline materials. Developing materials with ultrahigh or ultralow thermal conductivity along a certain direction can enable new energy storage and conversion devices. However, grain boundaries - two-dimensional defects in crystal structures - exist in polycrystalline material and significantly affect thermal transport. Addressing the defects is currently not efficient - observing and experimenting with grain boundaries when creating materials can prove to be a lengthy and costly process. Machine learning may provide a more sustainable alternative. His research seeks to create a computer model that can predict the conductive properties of a material in real life, providing guidance to engineer defects for desired thermal properties. Jason Shoemaker, assistant professor of chemical and petroleum engineering Enabling Immunomodulatory Treatment of Influenza Infection using Multiscale Modeling When a person contracts a respiratory viral infection like COVID-19 or influenza, the immune system responds in a myriad of ways to eliminate the virus. Respiratory viral infections are so dangerous, however, because excessive immune responses may cause extreme lung inflammation. However, Dr. Shoemaker’s new modeling research may help doctors better predict and treat patients who are most at risk to that extreme response. His $547,494 CAREER Award will fund creation of computational models of the immune response to seasonal, deadly (avian) influenza viruses, which can help identify the best way to suppress immune activity and reduce tissue inflammation. Since this work targets the immune system and not the specific virus, the models are expected to impact many respiratory infections, including COVID-19. Feng Xiong, PhD, assistant professor of electrical and computer engineering Scalable Ionic Gated 2D Synapse (IG-2DS) with Programmable Spatio-Temporal Dynamics for Spiking Neural Networks In science fiction stories from “I, Robot” to “Star Trek,” an android’s “positronic brain” enables it to function like a human, but with tremendously more processing power and speed. In reality, the opposite is true: a human brain - which today is still more proficient than CPUs at cognitive tasks like pattern recognition - needs only 20 watts of power to complete a task, while a supercomputer requires more than 50,000 times that amount of energy. Dr. Xiong’s $500,000 CAREER award will fund research in neuromorphic computer and artificial neural networks to replicate the spatio-temporal processes native to the brain, like short-term and long-term memory, in artificial spiking neural networks (SNN). This “dynamic synapse” that will dramatically improve energy efficiency, bandwidth and cognitive capabilities of SNNs. ###

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