Research

New Computer Science Faculty, 2024

Alexandra Grace Wilson — Mon, 07 Oct 2024 19:16:46 +0000

New Computer Science Faculty, 2024 Alexandra Grac… Mon, 10/07/2024 - 13:16

Join us in welcoming our new Department of Computer Science faculty and learn about what they're excited to pursue.

Fruzsina Agocs, Assistant Professor

At CU Boulder I’ll be working on the design and implementation of efficient numerical methods for challenging problems (mostly presenting as differential equations) in science and engineering. I’m particularly looking forward to being able to work with people from computer since, applied math, physics, and beyond in the interdisciplinary, collaborative setting offered by the university.

Ramin Ayanzadeh, Assistant Professor

I am excited to work on trustworthy quantum computing to enhance the reliability and security of quantum computers and emerging accelerators, as well as exploring quantum intelligence to pursue synergistic opportunities between quantum computing, machine learning, AI, and optimization.

Mona ElHelbawy, Associate Teaching Professor, CS Post-Baccalaureate

I am excited to be joining the Computer Science Department at the �鶹��Ƶ! My goal is to ensure that students from all backgrounds feel supported by our programs. I believe it is important to address learning needs both inside and outside the classroom, and to celebrate the diversity that each student brings as a valuable strength. I am looking forward to working alongside the wonderful faculty and staff at CU Boulder to strengthen our programs and build meaningful partnerships

Curry Guinn, Associate Teaching Professor, CS Post-Baccalaureate

I’m thrilled to join the teaching faculty in the post-baccalaureate program in Applied Computer Science at CU Boulder. One of the most rewarding aspects of this position is engaging with passionate, motivated students who are eager to learn and grow. I'm especially excited to introduce the latest advancements in artificial intelligence to the classroom. Over the past five years, AI has undergone rapid transformations, and I’m eager to help students understand the inner workings of these technologies, apply them to real-world problems, and innovate for the future. My goal is to empower students to not only grasp the concepts of computer science but also to become contributors to the evolution of this ever-changing field.

Esther Rolf, Assistant Professor

I am thrilled to start my new research lab at CU Boulder CS and tackle some of the most challenging and impactful problems in geospatial and statistical machine learning. Along with the PhD students in my lab, I am excited to push the frontiers of fundamental machine learning research for practical social and scientific impacts, and to find new collaborators in this mission across the University of Colorado.

Join us in welcoming our new Department of Computer Science faculty and learn about what they're excited to pursue.

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Who's on the list? How award nominations can support diversity

Alexandra Grace Wilson — Fri, 27 Sep 2024 20:30:19 +0000

Who's on the list? How award nominations can support diversity Alexandra Grac… Fri, 09/27/2024 - 14:30

Grace Wilson

Associate Professor Daniel Acuna

Daniel Acuna, an associate professor in computer science, is part of a group advocating for the broader computer science community to help increase the diversity of nominees for scientific awards.

"Science Needs You: Mobilizing for Diversity in Award Recognition," an opinion piece Acuna and his coauthors wrote for the Association of Computing Machinery (ACM), outlines how nominators can help broaden recognition of diverse contributors in science.

Acuna's Science of Science and Computational �鶹��Ƶy Lab focuses, among other themes, on who has the opportunity to make scientific discoveries and how those discoveries are acknowledged. This lens is useful in considering how to promote broader recognition.

Awards start with a nomination process, which means that only those submitted for nomination have a chance of receiving the award, Acuna explains. Changing this simple lever by encouraging people to nominate holistically and thoughtfully could change the landscape of scientific recognition and discovery.

The article highlights some of the work that the ACM has done to help broaden representation, including the ACM Shepherds program, which connects nominators with people familiar with the process who are willing to help.

Not just a trophy

In the competitive world of academic grants and tenure, scientific awards and their accompanying visibility can motivate aspiring scientists.

The article explains this can be especially impactful to "persons from populations underrepresented in computing who may view awardees as inspirational trailblazers and role models."

The awards can also have practical benefits to awardees, who can use them as evidence of service requirements for tenure consideration.

"While many organizations would like to broaden the populations of people who get recognized," Acuna said, "we should also consider the process by which recognition happens. It is usually a community effort, and change can happen through all of us."

In an opinion piece published by the Association of Computing Machinery, associate professor Daniel Acuna and his co-authors advocate for the wider computer science community to consider who and how they nominate for scientific awards.

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Orit Peleg selected as a 2024 Schmidt Science Polymath

Alexandra Grace Wilson — Tue, 10 Sep 2024 16:17:13 +0000

Orit Peleg selected as a 2024 Schmidt Science Polymath Alexandra Grac… Tue, 09/10/2024 - 10:17

Grace Wilson

Orit Peleg, associate professor of computer science and Biofrontiers Institute faculty member at CU Boulder is one of six researchers recognized for their boundary-pushing work by the prestigious Schmidt Sciences Polymath Program.

Each researcher will receive a total of up to $2.5 million over five years, joining a global community of 21 Polymaths from six countries.

The Polymath Program provides significant, flexible multi-year grants to enable awardees to pursue risky, novel theories that would otherwise be difficult to fund.

Peleg will focus on the evolutionary origins and diversification of communication across different animal species and how it manifests in group cognition of social animals.

"This award validates my belief that some of the most exciting discoveries lie at the intersections of diverse fields," Peleg said. "I am deeply grateful to my mentors and mentees for their inspiration and guidance along the way, and to Schmidt Sciences for their generous support."

This year, the program received 117 applications from 65 nominating universities and partners that were evaluated by senior scientists, prior Polymath awardees and other experts.

The six recipients were selected based on both their past achievements—including a demonstrated capacity for high-impact research and high-variance thinking—and their ideas for boundary-breaking future projects.

In Peleg's lab, her mentees research how biological communication signals are generated and interpreted. While the channel may change - whether chemical, sound, or light - the living creatures of our world all encode high-dimensional biological features into low-dimensional communication patterns.

“Curiosity doesn’t operate in a silo, and neither should science,” said Wendy Schmidt, co-founder of Schmidt Sciences. “That’s why we support several initiatives to enable researchers to pursue interdisciplinary hypotheses, in collaboration. The Schmidt Sciences Polymath Program allows bold, creative thinkers to pursue knowledge across boundaries and in doing so, to help all of us better understand the deep interconnections between people, planet and universe.”

The Polymaths benefit from a network of winners that convenes annually to develop ideas for collaboration, funding and further study. The recipients represent the top 5 percent of applicants who are given funding to pursue research within three years after being awarded tenure.

“We are delighted to support the Polymaths to pursue what excites them. Through our funding, we hope to achieve breakthroughs and transform the way science is conducted,” said Stu Feldman, chief scientist at Schmidt Sciences.

�鶹��Ƶ Schmidt Sciences

Schmidt Sciences supports interdisciplinary researchers across scientific fields, geographies and career levels through Schmidt Science Fellows, Schmidt Polymaths and other initiatives. The Polymath program began in 2021 with awards to two scientists.

Peleg will receive a total of up to $2.5 million over five years to pursue the origins of animal communication and how it influences the group cognition of social animals.

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Protecting our data from quantum hackers

Alexandra Grace Wilson — Mon, 09 Sep 2024 22:03:27 +0000

Protecting our data from quantum hackers Alexandra Grac… Mon, 09/09/2024 - 16:03

Grace Wilson

Assistant Professor Huck Bennett is working to keep our data safe from hackers when the quantum revolution comes.

Bennett has been funded by the National Science Foundation to investigate the feasibility of lattice-based cryptography to protect against the threat of quantum computers.

"Quantum computers have the ability to break the cryptography we currently use on the internet to shield our emails from prying eyes and protect our financial information from hackers," Bennett explained.

Solving for tomorrow

This is not just an issue for the future when quantum computers come online. Even today, bad actors are gathering encrypted data to crack in anticipation of the quantum revolution.

The security of cryptography derives from a set of challenging math problems that take computers a long time to solve—or at least we hope it does.

Because quantum computers can quickly solve some problems that serve as the basis of current cryptography, researchers have been in search of new classes of problems that are both suitable for use in cryptography and secure against quantum computers—problems that are "post-quantum."

Bennett's work is to pressure-test one of the suggested new post-quantum cryptography methods, lattice-based cryptography.

Hard enough?

Bennett explained that a lattice is a geometric object that looks like a regular “grid” of points in high-dimensional space: often 100 or more.

We can create math problems from this multidimensional lattice that are a great fit for cryptography. They are quick to solve if you have the right information, but without it, they take a huge amount of time and computing power.

Bennett's focus is on how "hard" problems on lattices are, or how much time it takes to solve them.

Specifically, his goal is to show that lattice-based cryptography is secure by showing that certain computational problems on lattices get exponentially harder as the dimensions grow—even for quantum computers.

But, he said, it's also important to play “hacker's advocate” and think about whether this complex cryptographic idea could fall apart.

Assistant Professor Huck Bennett is working to keep our data safe from hackers when the quantum revolution comes.

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Novel AI system awarded $2 million in Cyber Challenge, advances to finals

Alexandra Grace Wilson — Thu, 05 Sep 2024 20:16:14 +0000

Novel AI system awarded $2 million in Cyber Challenge, advances to finals Alexandra Grac… Thu, 09/05/2024 - 14:16

A team spanning six universities and including assistant professor Yueqi Chen and PhD candidate Qinrun Dai from the CU Boulder Department of Computer Science are advancing to the final competition of the 2-year DARPA and ARPA-H AI Cyber Challenge.

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CS professor receives grant to help treat patients with ovarian cancer

Anonymous — Mon, 29 Jul 2024 14:30:30 +0000

CS professor receives grant to help treat patients with ovarian cancer Anonymous (not verified) Mon, 07/29/2024 - 08:30

Professor Aaron Clauset has received funding from the AB Nexus program, which funds interdisciplinary research teams between CU Boulder and CU Anschutz.

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Women of color disproportionately targeted by book bans, study finds

Anonymous — Mon, 08 Jul 2024 16:41:39 +0000

Women of color disproportionately targeted by book bans, study finds Anonymous (not verified) Mon, 07/08/2024 - 10:41

Computer Science PhD candidate Katie Spoon and her collaborators analyzed over 2,500 books removed in the 2021-2022 school year.

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Think you might have COVID? Wait 2 days to test

Anonymous — Tue, 25 Jun 2024 21:23:14 +0000

Think you might have COVID? Wait 2 days to test Anonymous (not verified) Tue, 06/25/2024 - 15:23

CS professor Dan Larremore's lab builds new model to see when to test for COVID.

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Maria Pacheco empowers LGBTQ+ community through service leadership

Anonymous — Thu, 13 Jun 2024 14:47:39 +0000

Maria Pacheco empowers LGBTQ+ community through service leadership Anonymous (not verified) Thu, 06/13/2024 - 08:47

Charles Ferrer

Assistant Professor Maria Pacheco is driven to connect LGBTQ+ individuals with opportunities both in and outside of the classroom.

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Understanding the Broader Picture: The Image and Video Computing Group

Anonymous — Tue, 11 Jun 2024 17:53:35 +0000

Understanding the Broader Picture: The Image and Video Computing Group Anonymous (not verified) Tue, 06/11/2024 - 11:53

Grace Wilson

Assistant Professor Danna Gurari's research revolves around using computers to analyze images and videos. Much of her recent work focuses on improving digital privacy for people who are blind or have low vision (BLV) as well as on analyzing medical images.

When asked what motivates her research, Gurari said she's driven by the desire to make an impact on people's lives.

"I try to find problems based on real-world data in real-world applications. That kind of data is difficult to get, but that's what really excites me. That and mentoring students," Gurari said.

Let's learn more about the research her lab members are pursuing:

Atharva Peshkar, second-year PhD student

Atharva Peshkar is improving radiation treatment for cancer patients by creating a personalized avatar that models each patient's body and breathing patterns.

The small movements of a patient's body are used to minutely adjust the position of the radiation gun in real time. This ensures the radiation stream moves with the body and stays directed on the tumor, as opposed to targeting surrounding tissue.

This innovation was recently recognized by the American Association of Physicists in Medicine as a "Best in Physics" abstract, an honor received by less than 1 percent of submissions.

When asked why he chose Gurari as his advisor, Peshkar said he talked to lab members before joining.

"They said she was really supportive and I thought I should go to her lab because a PhD is going to take five years, and I need an advisor who understands my goals," Peshkar said.

He said Gurari has been a great guide, and so have his group mates, like Myers-Dean, who helped him with CU's computing infrastructure when he first arrived.

Everley Tseng, third-year PhD student

Everley Tseng's research largely focuses on supporting visual privacy preservation for people with low vision and blind people using AI.

One project she contributed to involves a contrived dataset of private content. The team, which has researchers from the �鶹��Ƶ, University of Illinois and the University of Washington, created fake "private" items, like pregnancy tests, prescription pill containers and bills that BLV people took photos of.

This dataset is useful for research aimed at preserving blind and low-vision people's right to privacy.

"It's important for me to pursue this research because we're building assistive systems that, according to user feedback, can be very helpful for them in their daily lives," Tseng said.

Tseng also works on improving state-of-the-art algorithms for specific tasks that help people who are blind or with low vision.

One is a few-shot algorithm—an algorithm that only needs a few examples of a type of content—to identify and potentially obscure private parts of images, such as a prescription pill bottle or a pregnancy test.

This work will allow BLV people who show images to others to choose what private information others can see.

Tseng said that she appreciates working with Gurari. "She's great at guiding us to find what we're passionate about, what our research goals are, and how to make a good plan for the whole PhD," she said.

Jarek Reynolds, first-year PhD student

Jarek Reynolds' research involves developing datasets and algorithms that help BLV people better navigate their surroundings in their day-to-day lives, as well as protect their digital privacy.

Reynolds started by building a "salient object" dataset, which finds the most important objects in images taken by BLV photographers. He is now working on a privacy dataset, similar to Tseng's, but working on videos instead of images.

"Not only are you helping a demographic of people that are often marginalized, but the datasets and algorithms stem from authentic use cases, which makes the problems that much more interesting," he said.

Reynolds said he appreciates the brilliance and collaboration of the group.

"Dr. Gurari has a really good grasp of each of our strengths and weaknesses and how we can complement one another," he said.

Reynolds said that to be successful in a PhD, candidates should prepare to be humbled and take time to appreciate the journey.

"If there's something you would otherwise see as bad or a setback, that's not always the case. Every problem is an opportunity in disguise,'" he said.

Josh Myers-Dean, third-year PhD student

Josh Myers-Dean is making image editing tools easier to use by improving image segmentation, which entails breaking an image into discrete parts.

"I'm not working on generating fancy images, but, say, if you wanted to select a dog in a picture, I want to make that as easy as possible," he said.

Myers-Dean works specifically on interactive segmentation, which allows a model to determine if a user wants to segment a single object into its subparts, such as segmenting a chair into a back, a seat and legs, or finding the label part of a container of prescription pills. This could be useful for digital privacy, visual accessibility, and also creative applications such as image editing.

Myers-Dean received a National Science Foundation Graduate Research Fellowship, which he said has been an amazing advantage to his PhD journey by allowing him to focus on his research.

"Danna is great," Myers-Dean said. "She's super supportive. She helps keep me grounded and filter out the signal from the noise. She is also just a really kind person, and she's made me a better writer."

Myers-Dean recommended that anyone pursuing a PhD should try to focus on solving “problem A” before getting too excited about working on “problem B.”

"Try not to think too long on the horizon. Take the steps one at a time," he said.

Neelima Prasad, first-year PhD student

Neelima Prasad is researching how to track fast-moving objects in video footage. This involves self-supervised machine learning, which learns how to make sense of the data itself, rather than having already labeled data provided.

"It's actually a pretty hard problem," Prasad explained. "Let's say we have a soccer player. From one frame of a video to the next, they could be in a very different location, or they could go behind a goalie or a cameraman. How are we able to track them consistently over time?"

This problem has applications across many fields, including sports, autonomous driving and investigating natural phenomena, from the movements of bees to marine life.

Prasad said it's wonderful being a part of the group.

"Everyone has been so inclusive and supportive." she said. "We're all working on various aspects of computer vision. It's like we're all looking at different parts of the same elephant. I can talk to anybody about what I'm working on, and they are able to help me."

When asked what to consider when thinking about a PhD, Prasad said to have passion and some idea of where you want to end up.

"If you feel like there's something deeper you want to explore, a PhD is a great avenue to do that," she said.

Nick Cooper, first-year PhD student

Nick Cooper is working on untangling and demystifying deep learning classifiers.

"We send these neural networks into the field and when they come back, they can do amazing things, but what exactly have they learned? How are they doing it?" he said.

Deep neural networks, though able to perform very impressive feats, are often clunky, requiring vast amounts of electricity and time. This is because in order to "learn" something, they need to make many wrong choices.

As a metaphor, imagine taking a multiple choice test with no prior knowledge. You can take the test as many times as you wish and will be graded each time. Eventually, you can get an excellent score through trial and error, but this takes much more time and energy than if you were able to get the right answer the first time.

Cooper's research seeks to take these large, burdensome models that eventually learn how to provide correct answers, and streamline them into more compressed models that people can easily understand.

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