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Electrical and Computer Engineering
Refining data into knowledge, turning knowledge into action
Penn Engineering researchers are using data science to answer fundamental questions that challenge the globe—from genetics to materials design.
New atomically-thin material could improve efficiency of light-based tech
A new photodetector design from Penn Engineering is not only extremely thin, making it lightweight and cost effective, it can also emit light, not just detect it.
Putting community first, in a new social justice initiative
The Community Collaboratory for Co-Creation, led by Penn Nursing and Penn Engineering, will focus on research, education, and community engagement and outreach.
Penn Engineering’s ENIAD sets new world record for energy-efficient supercomputing
ENIAD, named after ENIAC, the world’s first digital computer, which was developed at Penn 75 years ago, took the top spot among a list of 500 of the most energy-efficient supercomputers reported in the world.
Simulation of glacial calving and tsunami waves predicts climate change consequences
Researchers at the School of Engineering and Applied Science have created a computer model that can accurately simulate tsunamis caused by glacial calving, critical to hazard assessments and mitigation measures in coastal regions regarding climate change.
‘I Look Like an Engineer’
For the third year in a row, Penn Engineering’s Advancing Women in Engineering program, dedicated to recruiting, retaining and promoting all female-identified students in the School, participated in the “I Look Like an Engineer” social media movement.
Engineers pave way for chip components that could serve as both RAM and ROM
The hurdle for making individual chip component devices has always been in manufacturing high-temperature ferroelectric materials. Now a team of researchers at the School of Engineering and Applied Science has shown a potential way around this problem.
Five Penn faculty named 2021 Sloan Research Fellows
The fellowship recognizes extraordinary U.S. and Canadian researchers whose creativity, innovation, and research accomplishments make them stand out as the next generation of scientific leaders.
The world’s first general purpose computer turns 75
The Electronic Numerical Integrator and Computer (ENIAC), built at the Moore School of Electrical Engineering, sparked the “birth of the computer age” thanks to a team of women programmers.
Brandon Gonzalez finds creativity in engineering energy efficiency
From a Nintendo Gameboy to engineering, a passion for energy engineering and creative problem solving has been the path for the Penn Engineering student.
In the News
Penn professor on gen AI’s rapacious use of energy: ‘One of the defining challenges of my career’
Benjamin Lee of the School of Engineering and Applied Science says that hardware and infrastructure costs are growing at high rates for generative AI.
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How the solar eclipse will affect solar panels and the grid
Benjamin Lee of the School of Engineering and Applied Science says that the electrical grid will have to figure out how to match supply and demand during brief windows where the energy source goes away.
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Students can soon major in AI at this Ivy League university—it’ll prepare them for ‘jobs that don’t yet exist’
The Raj and Neera Singh Program in Artificial Intelligence at Penn will be the first AI undergraduate engineering major at an Ivy League school, led by George Pappas of the School of Engineering and Applied Science.
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Penn to become first Ivy League to offer AI degree, looks to ‘train the leaders’ in emerging field
Penn is the first Ivy League university to offer a degree in artificial intelligence, with remarks from Robert Ghrist of the School of Engineering and Applied Science.
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These origami-inspired microbots could fix damaged nerves
Researchers at the School of Engineering and Applied Science led by Marc Miskin have built folding microrobots that could potentially go into human bodies to reconnect damaged nerve endings.
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A.I. could soon need as much electricity as an entire country
Benjamin Lee of the School of Engineering and Applied Science says there are many dramatic statements about the rapid growth of A.I., but it’s actually dependent on how quickly Nvidia chips can be distributed.
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