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From innovative underground drones and weather satellites, to improving indoor air quality and climate prediction, researchers are finding new ways to look at the world.

Associate Professor Claire Monteleoni Computer Science

Monteleoni is a leading researcher in the new and interdisciplinary field of climate informatics, broadly defined as any research combining climate science with approaches from statistics, machine learning and data mining. She uses machine learning to combine climate models to get the best possible predictions of future outcomes and to forecast hurricane tracks to give communities more time to prepare. Her group also uses machine learning to explore how extreme weather events like drought are related to climate change overall. In September, Monteleoni brought to Boulder the eighth International Workshop on Climate Informatics, an event she co-founded in 2011.

Assistant Professor Marina Vance Mechanical Engineering

Vance recently led the largest collaborative study to date on indoor air quality at a research house at the University of Texas Austin. The project, titled HOMEChem, was conducted with 20 faculty members from 13 universities. Researchers outfitted the house with varying instrumentation and then performed everyday activities like cooking and cleaning, with the goal of understanding the chemical processes happening in indoor environments and how they may affect those inside.

Professor Rajagopalan Balaji Civil, Environmental and Architectural Engineering

Balajis research is an interdisciplinary effort to ensure sustainable water quantity and quality for growing populations under increasing climate variability. His current research looks at how past societies responded to climate variations and how the lessons learned there can be applied to current natural resource management problems. Other projects model climate extremes at national parks and examine the health effects of climate change, like the growing risk of epidemics of chronic kidney disease.

Professor Albin Gasiewski Electrical, Computer and Energy Engineering

Thanks to Gasiewskis work, there will soon be a fleet of mini-satellites orbiting the Earth, providing improved weather forecasting to people who need it most, including farmers, airlines and shipping companies. His teams work, licensed to space technology company Orbital Micro Systems, would allow for observation of the Earth every 15 minutes using microwave eyes. Unlike the more common infrared or optical satellites, these passive microwave frequencies can see through clouds, detect water vapor and precipitation, and track weather conditions as they evolve. The work has also provided learning opportunities for dozens of undergraduate students in electrical engineering and the Colorado Space Grant, who have contributed to both the microwave sensing systems and the vehicles that will take them to low-Earth orbit.

Professor Michael D. McGehee Chemical and Biological Engineering

McGehee and his team are developing windows that can switch from clear to tinted when voltage is applied, depending on the season or time of day. The windows dont need blinds, allow for more natural light and cut down on glare. Another new technique theyre working on could increase solar energy cell efficiency from 21 percent to 25 percent. It works by covering existing cells with a kind of perovskite created from salt solutions that offers great light absorption, among other properties prized in a variety of technologies. McGehee works closely with the National Renewable Energy Laboratory in Boulder.

Professor Sean Humbert Mechanical Engineering

Humbert is leading an interdisciplinary engineering team to design drones that can explore underground environments like subway tunnels, mines and caves. Its part of a $4.5 million grant from the U.S. Defense Advanced Research Projects Agency (DARPA) that challenges teams from across the country to complete three increasingly difficult underground tasks to discover the best systems and methods. The work may one day enable teams of flying and rolling drones to work together to search through dark and dangerous environments to find human survivors of earthquakes, chemical spills and more. The project starts in September, when Humberts group will begin testing its robot on a mock search and rescue operation in miles of steam tunnels.

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Earthly Exploration | College of Engineering & Applied Science - CU Boulder's College of Engineering & Applied Science

Princetons Jonathan Mayer has taken a new role as the inaugural chief science and technology adviser and chief artificial intelligence officer at the U.S. Department of Justice. In the newly created role, Mayer will advise on complex issues of technology, law and policy, including cybersecurity and artificial intelligence.

Mayer has committed to serve in this position for at least 12 months. He started at the end of January, and he plans to return to Princeton after the conclusion of his government service.

Mayer is an assistant professor of computer science and an assistant professor in theSchool of Public and International Affairs (SPIA). He is associated faculty in theCenter for Information Technology Policy (CITP), which is a joint initiative between SPIA and the School of Engineering and Applied Science.

According to Arvind Narayanan, director of CITP and professor of computer science, the center has a long tradition of going beyond research to engage directly with policy makers. We have our intellectual center of gravity in computer science and engineering, he said, but we focus on research that can answer societal and policy questions.

Jonathan Mayers work exemplifies what we do at CITP, Narayanan said.

Mayer studies the intersection of technology and law, with emphasis on national security, criminal procedure and consumer privacy. His recent publications include research on using machine learning to automate detection of misinformation, user perceptions of social media verification, methods for locating network censorship devices, and a case study on the effects of Hong Kongs National Security Law.

Mayer joined Princetons faculty in 2018. He previously served as the technology law and policy adviser to then-Senator Kamala Harris. Before that, he was chief technologist of the Federal Communications Commission Enforcement Bureau and a technology adviser at the California Office of the Attorney General. He holds a Ph.D. in computer science from Stanford University, a J.D. from Stanford Law School, and an A.B. from Princeton.

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Justice Department designates Mayer to serve as first chief science and technology adviser and chief AI officer ... - Engineering at Princeton...

ROCHESTER, N.Y. Jaime Campanelli loves being a part of community outreach, especially when it has to do with cybersecurity.

So today were gonna become our own cyber superheroes. Is everyone excited?" said Campanelli, a Rochester Institute of Technology fifth-year cybersecurity student.

Campanelli was speaking to a local Girl Scout troop that was participating in Cyber Security Badge Day at RIT.

I came here and learned about women in computing and they had an outreach committee and I thought oh my gosh," she said.

In high school, she took every technology and computer science class her school offered.

In my computer science class, I was one of four girls out of the class of 30, she said.

Now, she is trying to spread a message both about cybersecurity and representation.

The reason why Im passionate about it is because I didn't get the opportunity to have stuff like this, to have events that come to campus to learn about cybersecurity before I got here, Campanelli said. Making those connections with other women in the class but also saying no, I deserve to be here.

As part of RITs Women in Computing program, she gets the opportunity to teach younger generations about being safe online.

The world nowadays is so tech-involved and tech-heavy," she said. "All of my little cousins have their tablets and their iPhones. I didn't get an iPhone until I was 12 and now my 5-year-old cousin has one and it's like yes that's amazing, but teaching them how to use it and using it properly is really important."

She's educating youth on things from phishing emails to coding.

I just see the lights flash in their head or the idea pops up in their head and its interesting because again everything in their lives is tech now, Campanelli said.

She has hopes of it having an even bigger impact.

Now having events like Girl Scout Badge Day and all our other outreach events where theres at least 50 girls coming. That's 50 people whose lives we just inspire and at least help hopefully get them into the field, she said.

Campanelli has been impacted herself.

It's very humbling because again, I didnt have those experiences as a child and it just makes my heart tingle, she said.

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RIT student working to create safer community one click at a time - Spectrum News

USC researchers have created a low-cost, accessible learning kit to help college and high school students build their own robot friend. Photo/James Kim.

From smart virtual assistants and self-driving cars to digital health and fraud prevention systems, AI technology is transforming almost every aspect of our daily livesand education is no different. For all its promise, the rise of AI, like any new technology, raises some pressing ethical and equity questions.

How can we ensure that such a powerful tool can be accessed by all students regardless of background?

Inspired by this call to action, USC researchers have created a low-cost, accessible learning kit to help college and high school students build their own robot friend. Students can personalize the robots body, program the robot to mimic their head posture, and learn about AI ethics and fairness in an engaging, accessible way.

The system is outlined in a new study, titled Build Your Own Robot Friend: An Open-Source Learning Module for Accessible and Engaging AI Education, presented this week at the AAAI Conference on Artificial Intelligence, education symposium track.

We believe it is important for students to learn about fairness and ethics in AI in the same way that we learned about math and physics in K-12, said co-lead author Zhonghao Shi, a doctoral student in computer science who conducts his research in the USC Interaction Lab led by Professor Maja Matari. We may not use these subjects every day, but having a basic understanding of these concepts helps us do better work and be mindful of new technologies.

Supported by the National Science Foundation, the paper is co-lead-authored by Amy OConnell, a USC computer science doctoral student and Shis labmate, andZongjian Li, a software engineer working withMohammad Soleymani, a research associate professor at the USC Institute for Creative Technologies. Soleymani and Matari are co-authors, in addition to Guy Hoffman from Cornell University, and USC computer science undergraduate students Siqi Liu and Jennifer Ayissi.

Members of the USC Interaction Lab and Professor Maja Matari with customized versions of Blossom the robot. Photo/James Kim.

The three-part open-source learning module provides students with hands-on experience and introductory instruction about various aspects of AI, including robotics, machine learning, software engineering, and mechanical engineering. It helps to address a gap in the market for AI education, said Shi and OConnell.

Currently, pre-built robots, such as the NAO, are unaffordable for schools with limited resources, while educational robot kits, such as LEGO Mindstorms, though affordable, do not adapt to students at different levels.

The NAO robot, while commonly found in research labs, is costly, running at around $15,000.

Were proposing this open-source model to not only improve education in AI for all students but also to make human-interaction research more affordable for labs and research institutions, said Shi. Ultimately, we want to increase access to human-centered AI education for college students and create a pathway to more accessible research.

To reduce costs and development time for learners, the team customized and simplified Blossom, a small, open-source robot originally developed by Hoffman at Cornell University. Blossom is a common fixture in USCs Interaction LabShi previously used the robot to design better AI voices for mindfulness exercises, while OConnell programmed it to act as a study buddy for students with ADHD symptoms.

Last year, the duo began to devise ways to use the robot for educational purposes and set to work creating a low-cost, customizable and human-focused module that could mirror some of the ways that students will interact with technology in their everyday lives.

USC computer science doctoral student Amy OConnell and undergraduate student Jennifer Ayissi customize Blossom the robot. Photo/James Kim.

To make the robot more affordable, they developed strategies to subsidize its cost. In the version of Blossom presented in the study, the materials are created using 3D printers, instead of more costly laser printing. Currently, one of the teams customizable robots costs around $250 to make.In comparison, a NAO robot runs at around $15,000.

OConnell, who learned to crochet during the pandemic, designed five new Blossom exteriors and created detailed, easy-to-follow patterns and tutorials for each version, including a baby onesie, knitted and crocheted options, which are all low-cost and customizable.

We want to increase access to human-centered AI education for students. Zhonghao Shi.

After constructing their robot friend, students are encouraged to further customize Blossom with, for instance, mechanical eyebrows, color-changing lights, or even an expressive face screen. For OConnell, creativity has been a crucial part of her own engineering journey.

Crafting and engineering require similar strengths like counting, planning, and spatial reasoning, said OConnell. By incorporating crafting into this project, we hope to draw in creative students who might not have considered how their skills align with robotics and engineering.

The system was piloted in a 2-day workshop in May 2023 with 15 undergraduate college students from a local minority-serving institution. Four teams of students constructed Blossom robots following the learning module assembly guide with blank knitted exterior to personalize with accessories. On the second day, the students used pre-trained head pose tracking and gesture recognition models to detect and mimic nodding behaviors from the user.

In part one of the module, study participants (anonymized) construct a simplified version of the Blossom open-source robot platform.

From post-workshop surveys, they found that 92% of the participants believed that the workshop helped them learn more about the topics covered and all the participants believed that the workshop encouraged them to study more about robotics and AI in the future.

Equipping users with AI literacy, including an understanding of AI ethics and fairness, is crucial to avoid unintended discrimination against marginalized groups, said Shi.

In continued work, the team plans to further evaluate and improve the module for high school students and K-12 students. Ultimately, the researchers hope to expand access for students at different educational levels.

Were excited to share more about our project with people from around the world, Shi said. We want to make sure that people from different kinds of socioeconomic backgrounds have the opportunity to gain an education on AI and participate in the process of improving AI for future use.

Published on February 22nd, 2024

Last updated on February 22nd, 2024

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How to Build Your Own Robot Friend: Making AI Education More Accessible - USC Viterbi | School of Engineering - USC Viterbi School of Engineering

We know it when we see it, but what is creativity and can it be quantified? In a paper that could help guide future artificial intelligence (AI) development, a team from UC San Diegos Jacob School of Engineering, Department of Music and Qualcomm Institute (QI) has discovered answers in the context of musical collaboration.

Its a hard problem, because not a lot of people agree on what is creative, said study co-author Vignesh Gokul, a computer science and engineering Ph.D. candidate at UC San Diego. Our main hypothesis was that the musical score or output that is most creative is the one that conveys the most information. The contribution of this paper is a method to calculate this total information flow between a human and an agent (or another human) playing music.

The papers senior author Shlomo Dubnov, who is professor in both UC San Diegos Music Department and Computer Science and Engineering Department as well as a QI affiliate, added, This is a new concept that highlights the importance of communication and collaboration that occurs between musicians or between musicians and musical artificialintelligence agents as a fundamental factor in achieving music creativity.

The paper, Evaluating Co-Creativity Using Total Information Flow, is authored by Gokul, Dubnov and computer science and engineering masters student Chris Francis, who spearheaded experimental infrastructure and operation. The paper is being presented at this weeks Mathemusical Encounters in Singapore : a Diderot Legacy conference.

The project was funded by Project REACH : Raising Co-creativity in Cyber-Human Musicianship, a European Research Council Advanced grant that promotes the study of "shared musicality" at the intersection of the physical, human and digital spheres; it is designed to produce models and tools to better understand and encourage human creativity in a context where it is increasingly intertwined with computation.

In this research, the UC San Diego team decided to evaluate musical co-creativity by using an pre-trained large language neural network model called Multitrack Music Transformer to estimate the amount of interaction between different musical voices in tracks containing a piano melody and its piano accompaniment.

The team derived an equation to effectively compute the information flow between the two signals in this musical interaction system, as a quantitative score. According to the hypothesis, the higher the score, the greater the creativity. If one of the musical voices in a pair ignored or repeated the other, the score would go down because little information would be exchanged. If, however, the voices went back and forth integrating each others musical information with their own, the score would rise.

Next, the team looked for a way to check that this score was a meaningful measure of creativity.

The hardest part was definitely validating this framework, Gokul said. We had come up with the hypothesis; we had come up with a method to compute the score based on the hypothesis. But validating is hard because humans have different subjective preferences.

The team decided to lean into human subjectivity and compare the computed score with five expert musicians evaluations of 84 musical duets, including some that were randomly generated. The results demonstrated that the computational score matched human perception.

Gokul cautioned there is still work to be done. He notes theres a tendency for pre-trained models to prefer their own generations, and the team found that to be the case in this work with the Multitrack Music Transformer model. And, Gokul notes, this is only one step toward a musical system in which humans and AI can interact creatively.

However, the researchers are already planning future applications of the current work, including a collaboration with neuroscience researchers who investigate the cognitive load of listening to music or performing musical tasks.

As Gokul transitions from his Ph.D. studies to a job in the tech sector, he is grateful for all the human creative collaboration he experienced at UC San Diego, including with Dubnov. He has been a fantastic advisor, Gokul said. Hes very knowledgeable in information theory, music, generative AI, and we have published about seven works together. It's been great to receive his guidance on these projects.

Read more about UC San Diegos Qualcomm Institute, Department of Music or Department of Computer Science and Engineering.

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Capturing Creativity with Computation for Music AI - University of California San Diego