��̽̽ - Mathematics and Statistics

Instant Evolution: AI designs robots from scratch in seconds. And they walk.

saa — Wed, 11 Oct 2023 19:02:33 +0000

One has three legs and rear fins. No engineer would come up with such a robot. But in seconds, an AI running a new algorithm did—and it walks.

A team of scientists from ��̽̽, Northwestern University, and MIT created this new approach: the first artificial intelligence that can design unique robots from scratch.

“AI is exploding in so many fields right now. We figured out how to apply it to designing robots very efficiently,” says ��̽̽’s Josh Bongard, a professor the Department of Computer Science and senior author on the new study. “Instead of running a program for two weeks on a supercomputer, if you have an off-the-shelf laptop—running with our approach—within 30 seconds the AI produces a design. An entirely original, functional design.”

The research was published on October 3 in the Proceedings of the National Academy of Sciences.

David Matthews tests a prototype of a robot entirely designed by artificial intelligence. It walks. Matthews graduated from ��̽̽ in 2021 and is now a research scientist at Northwestern University—in the lab of assistant professor Sam Kriegman who completed his masters and PhD at ��̽̽ with professor Josh Bongard. The three of them, with two other colleagues, teamed up on new research published in the Proceedings of the National Academy of Sciences. (Photo courtesy: Sam Kreigman, Northwestern)

Evolution in Seconds

AI systems have been making dramatic advances in fields from artwork to protein structures—but “have yet to master the design of complex physical machines,” the scientists write.

To test the AI, the team gave their new system a simple prompt: Design a robot that can walk across a flat surface. While it took nature billions of years to evolve the first walking species, the novel algorithm compresses evolution to lightning speed — and successfully designed a walking robot in seconds.

Until now, “the main methods of designing robot bodies have relied on random chance,” says David Matthews, ��̽̽ class of 2021, the lead author on the new study and primary inventor of the new algorithm. Unlike a brute-force method where a supercomputer blindly tests shapes—inching forward through millions of versions until something finally works—the new method learns by looking back at its own mistakes. By considering specific failures or inefficiencies in each progressive robot design—say a leg that is too long or short—the method improves the design quickly, optimizing interdependent parts of the robot over just a few test generations.

“This advance incorporates the mathematic tools which have revolutionized AI software, such as ChatGPT,” Matthews notes, “to perform efficient design of robot bodies.” Matthew’s mathematical discovery “opens the way toward bespoke AI-driven design of robots for a wide range of tasks,” the team writes in the PNAS study, “rapidly and on demand.”

“David is truly a genius,” says Josh Bongard. “I bet our David Matthews is going to become more famous than the other David Matthews.”

But the AI program is not just fast. It can run on a low-cost personal computer which “the lowers the barrier for designing robots,” says Matthews, now a research scientist in Kriegman’s lab. And it stands in sharp contrast to other AI systems, which often require energy-hungry supercomputers and colossally large datasets. And even after crunching all that data, those systems are tethered to the constraints of human creativity — only mimicking humans’ past works without an ability to generate new ideas.

“Animals come in all shapes and sizes, and excel in many different situations,” says Matthews, while human-designed robot forms have been homogeneous, and have excelled only in limited environments.

“We discovered a very fast AI-driven design algorithm that bypasses the traffic jams of evolution, without falling back on the bias of human designers,” said co-author Sam Kriegman—one of Josh Bongard’s former PhD students in ��̽̽’s Morphology, Evolution & Cognition Laboratory, and now a professor at Northwestern University. “We told the AI that we wanted a robot that could walk across land. Then we simply pressed a button and presto! It generated a blueprint for a robot in the blink of an eye that looks nothing like any animal that has ever walked the earth. I call this process ‘instant evolution.’”

From xenobots to new organisms

Over the last several years, Bongard, Kriegman and their colleagues garnered widespread media attention for developing Xenobots, the first living robots made entirely from biological cells. Now the team views this new AI as the next advance in their quest to explore the potential of artificial life. The robot itself is unassuming — small, squishy and misshapen. And, for now, it is made of inorganic materials—the output of a 3-D printer. But the scientists believe it represents the first step in a new era of AI-designed tools that, like animals, can act directly on the world.

“When people look at this robot, they might see a useless gadget,” Kriegman said. “I see the birth of a brand-new organism.”

(Video courtesy Sam Kriegman, Northwestern)

Zero to walking within seconds

While the AI program can start with any prompt, the team began with a simple request to design a physical machine capable of walking on land. That’s where the researchers’ input ended and the AI took over.

“The AI tracks all of the interdependencies,” explains Bongard. “To improve the robot, it might consider making one muscle bigger. But then it realizes that, ‘if I make that muscle bigger, it's going to affect the front part of the robot and it's going to tip over on its nose and slide to a stop. So actually that's not the right answer. Instead, I should change that muscle over there by a small amount.’ Being able to rectify its mistakes, the AI can see ahead, which is very hard for humans to do.”

The computer started with a block about the size of a bar of soap. It could jiggle but definitely not walk. Knowing that it had not yet achieved its goal, the AI quickly iterated on the design. With each iteration, the AI assessed its design, identified flaws and whittled away at the simulated block to update its structure. Eventually, the simulated robot could bounce in place, then hop forward and then shuffle. Finally, after just nine tries, it generated a robot that could walk half its body length per second — about half the speed of an average human stride.

The entire design process — from a shapeless block with zero movement to a full-on walking robot — took just 26 seconds on a laptop. “Because the AI can design the robot so fast, you can actually watch it create in real time,’ says ��̽̽’s Bongard. “It’s like a video game, watching the simulator making a muscle bigger or shortening a leg—you can see the AI in action,” unlike the black box experience many people have with ChatGPT where you don’t know what it’s doing.

“Before any animals could run, swim or fly around our world, there were billions upon billions of years of trial and error,” says Sam Kriegman. “This is because evolution has no foresight. It cannot see into the future to know if a specific mutation will be beneficial or catastrophic. We found a way to remove this blindfold, thereby compressing billions of years of evolution into an instant.”

Rediscovering legs

All on its own, the AI surprisingly came up with the same solution for walking as nature: Legs. But unlike nature’s decidedly symmetrical designs, artificial intelligence took a different approach. The resulting robot has three legs, fins along its back, a flat face and is riddled with holes.

“It’s interesting because we didn’t tell the AI that a robot should have legs,” Kriegman said. “It rediscovered that legs are a good way to move around on land. Legged locomotion is, in fact, the most efficient form of terrestrial movement.”

To see if the simulated robot could work in real life, the team used the AI-designed robot as a blueprint. First, they 3D printed a mold of the negative space around the robot’s body. Then, they filled the mold with liquid silicone rubber and let it cure for a couple hours. When the team popped the solidified silicone out of the mold, it was squishy and flexible.

Now, it was time to see if the robot’s simulated behavior — walking — was retained in the physical world. The researchers filled the rubber robot body with air, making its three legs expand. When the air deflated from the robot’s body, the legs contracted. By continually pumping air into the robot, it repeatedly expanded then contracted — causing slow but steady locomotion.

Unfamiliar design

While the evolution of legs makes sense, the holes are a curious addition. AI punched holes throughout the robot’s body in seemingly random places. The scientists aren’t sure, but it may be that porosity removes weight and adds flexibility, enabling the robot to bend its legs for walking. “We don’t really know what these holes do, but we know that they are important,” Kriegman said. “Because when we take them away, the robot either can’t walk anymore or can’t walk as well.”

“When humans design robots, we tend to design them to look like familiar objects,” Kriegman said. “But AI can create new possibilities and new paths forward that humans have never even considered. It could help us think and dream differently. And this might help us solve some of the most difficult problems we face.”

Potential future applications

Although the AI’s first robot can do little more than shuffle forward, the scientists imagine a world of possibilities for tools designed by the same program. Someday, similar robots might be able to navigate the rubble of a collapsed building, following thermal and vibrational signatures to search for trapped people and animals, or they might traverse sewer systems to diagnose problems, unclog pipes and repair damage. The AI also might be able to design nano-robots that enter the human body and steer through the blood stream to unclog arteries, diagnose illnesses or kill cancer cells.

“The only thing standing in our way of these new tools and therapies is that we have no idea how to design them,” Kriegman said. “Lucky for us, AI has ideas of its own.” The new AI algorithm described in the PNAS study is just one beginning example. “This AI, running on a laptop, designing the robot, has no training data. It's not like ChatGPT scraping the internet to look for every robot that was ever made, for example, and knowing what humans did wrong and doing it better,” says Josh Bongard. “It’s exploring and optimizing its own designs and making something new.”

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��̽̽ and Northwestern team creates robots on a laptop and 3D printer

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This simple robot was designed by an AI—using a new and ingenious algorithm invented by David Matthews, ��̽̽ Class of 2021 (shown in background, left). The AI's instructions: make a robot that can walk. Its training data: none. Its beginning body form: random. Running on an off-the-shelf laptop, the AI created this design in 26 seconds.Then to prove that it works in the real world, scientists made the device on a 3D printer—as shown here—out of silicone. The interior simulated muscles and external legs, pumped with air, work in coordinated fashion. And the robot walks. The potential: custom robots, on demand, at high speed. (Photo: courtesy Northwestern)

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Mathematics Graduate Student's NASA Internship

saa — Tue, 22 Feb 2022 15:46:05 +0000

We spoke with Mathematics Graduate Student, Hunter Rehm, regarding his internship with NASA Glenn Research Center:

"Over the past summer and fall, I interned with NASA GRC where I had the opportunity to work on two separate projects; one related to medical risk and another on satellite communication. My mentor, Lauren McIntyre, works as the technical lead for the MEDPRAT team at NASA. Our goal was to determine a risk metric which allows us to accurately compare medical conditions. We were able to use techniques from graph theory and linear algebra to understand how each medical condition progresses, which lead us to the rick metric that we are using today. We are currently writing a technical manuscript on these results to be published with NASA.

Additionally, I worked with Dr. Robert Short to determine which satellites are the most important for lunar and terrestrial communication. We are developing an algorithm which allows each satellite to calculate their own importance at any given time. We recently applied for a grant to continue this work over the next year. Future work on this topic will involve my advisor, Dr. Puck Rombach, and will be a part of my PhD dissertation. Overall, my internship at NASA was amazing and I would recommend that anyone who is interested should apply for one!"

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��̽̽ Mathematics Colloquium - Taras Lakoba

saa — Wed, 02 Feb 2022 15:37:10 +0000

Please join the Department of Mathematics and Statistics on Thursday, February 3rd at 4:30pm on Microsoft Teams for a fascinating colloquium featuring our very own, Professor Taras Lakoba.

Iterative numerical methods for solving nonlinear equations,and techniques for their acceleration

Taras Lakoba, University of Vermont
Thursday, February 3rd, 4:30pm to 5:30pm, Microsoft Teams

Abstract: This talk will consist of two parts. First, I will review the concept behind iterative methods for obtaining solutions of linear and nonlinear (systems of) equations. One prominent application is finding stationary solitary wave solutions of nonlinear wave equations.

In the second part of the talk, I will consider three techniques to accelerate these methods. The first of these techniques eliminates the numerical stiffness of the system of equations caused by the need to include high Fourier harmonics. The second technique eliminates the slowest-decaying mode in the error of the iterative solution. The third technique is known as the Momentum method in Machine learning and consists of modifying the iterated matrix so as to greatly decrease its condition number.

I will try to make most of the talk accessible to the MS-level graduate and upper-level undergraduate students.

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New Survey Findings Released from Innovative Prison Research Project

saa — Thu, 27 Jan 2022 14:56:00 +0000

��̽̽, the Vermont Department of Corrections, and the Urban Institute have released initial findings from the first phase of the Prison Research and Innovation Network (PRIN) in Vermont, one of five states participating in the five-year effort (with support from Arnold Ventures) to build evidence and spur innovation to make prisons more humane, safe, and rehabilitative.

Goals of the network include:

Understanding prison environments and the safety and well-being of those who live and work there.
Helping prisons collect data to promote transparency and accountability.
Supporting evidence-based changes to improve prisons, such as ensuring safe and humane environments for all.

In pursuit of these goals, the project enlisted the input of people confined and working in Southern State Correctional Facility (SSCF) in the research study design and the initial review of findings and will continue to do so toward the development of recommendations for improvements.

Survey findings:

Among the results, researchers at ��̽̽ found that there is much work to be done on top of the efforts already underway, including around the issues of correctional staffing and programming opportunities for incarcerated people. Of particular importance is the concerning mental health status and exposures to trauma experienced by both incarcerated persons and correctional staff. The survey results show high rates of self-reported depression, anxiety, PTSD, and suicidal thoughts. To read more about the survey findings, visit: go.uvm.edu/prinsurveys2021

��̽̽ researchers, as part of phase 2 of the PRIN project, are now collecting feedback and further insights on the survey results from the correctional staff and incarcerated persons in SSCF. This information will be particularly helpful as the Department of Corrections considers what can be done to address these challenges.

The ��̽̽ team used community based participatory research, a method that prioritizes the inclusion of those who work and are confined in prisons, to develop two prison surveys – one for correctional staff and one for incarcerated people. The surveys are a unique opportunity to gain an understanding of what it is like to be incarcerated, or work, in a Vermont prison from the perspective of those who know the system best. Surveys were administered in Southern State Correctional Facility, the PRIN pilot facility, in June 2021 with over 70% of correctional staff and incarcerated persons completing the surveys.

Entrance to Southern State Correctional Facility, where surveys were administered. (Photo courtesy of Vermont Department of Corrections)

“I am extremely proud of Vermont DOC’s participation in the Prison Research Innovation Network initiative,” said Vermont Department of Corrections Commissioner Nicholas Deml. “Vermont is a national leader in so many public policy areas, and I am committed to ensuring that corrections is at the top of that list. It starts with an across-the-board pledge to transparency as a central tenet in all that we do, and it will be ensured by a commitment to evidence-based approaches to make our facilities more humane, safe, and rehabilitation focused. I deeply appreciate the hard work done by our colleagues at ��̽̽ and the Urban Institute and I look forward to our continued collaboration on this important work.”

Kathy Fox and Abigail Crocker, co-founders of ��̽̽’s Justice Research Initiative, are the researchers working with the Department of Corrections on this effort. Crocker says, “As researchers who are committed to supporting the land-grant mission of the university and applying research toward positive social change, we are grateful for the opportunity to contribute to this important project.” Fox added, “The survey results begin to show a clearer picture of what it’s like to work or be confined in prison in Vermont and highlight the significant challenges associated with incarceration. We are hopeful that the participatory nature of this project, prioritizing the voices of correctional staff and incarcerated persons, will help to drive real, meaningful change.”

“Getting to the point where we can share this rich data on the perspectives, needs and challenges facing corrections staff and incarcerated people at SSCF took tremendous openness and commitment from DOC leadership, the leadership at SSCF and the ��̽̽ research team. To carry that out in the face of the COVID-19 pandemic makes the commitment all the more impressive. We look forward to continuing to support Vermont in its efforts to build on this research and data to make meaningful changes that improve prison culture, operations, and design and create more humane and rehabilitative correction environments,” said Jesse Jannetta, senior policy fellow at the Urban Institute.

The survey findings confirmed and highlighted the mental health issues faced by staff and incarcerated individuals. Vermont DOC has been actively building its capacity to support staff in several ways: developing the Peer Support Team; contracting with a licensed clinician who is available to staff; creating a Family Support Network. In 2021, the Legislature passed Act 37, an act related to establishing the Emergency Service Provide Wellness Commission. The department advocated that probation and parole officers and correctional officers be included in the definition of “emergency responder” so they can benefit from the work of the Commission.

In addition, Commissioner Deml recently established a Suicide Prevention Task Force, which is coordinating with the Departments of Health and Mental Health on available resources. The aim of this effort is to create a shared understanding of the suicide problem set within the Vermont DOC, to include the issue as it relates to Department staff and the incarcerated population; to prepare recommendations the Department may take to educate, mitigate, and prevent suicides and suicide contemplation; and to oversee initial implementation of recommendations within the system.

The PRIN Steering Committee is now forming innovation councils at SSCF to dive into the survey results and develop innovations. Some innovations will be able to start immediately, and others may take more time to plan. The project continues through March 2024. During that time, the three parties expect to try a variety of new ideas and will assess their effectiveness. The project will also move into the “participatory research” aspect, which allows the staff and incarcerated population to drive the changes with support from Vermont DOC and the PRIN Steering Committee.

To learn more about the Prison Research and Innovation Initiative and the network of 5 states, visit: urban.org/transform-prison.

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Survey results from staff, incarcerated people at Southern State Correctional Facility highlight issues around correctional staffing, programming for incarcerated people, and high rates of mental health concerns

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Mathematics and Statistics Research Assistant Professor Abigail Crocker (left) and Sociology Professor Kathy Fox review findings of the Vermont Prison Climate Surveys. (Photo: Bailey Beltramo)

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��̽̽ Mathematics Colloquium - Alex Iosevich

saa — Wed, 19 Jan 2022 13:11:56 +0000

Please join the Department of Mathematics and Statistics on Thursday, January 20th at 4:30pm on Microsoft Teams for a fascinating colloquium featuring University of Rochester’s Alex Iosevich.

Analytic, Number-Theoretic, and Combinatorial Aspects of Finite Point Configurations, and Applications to Data Science

Alex Iosevich, University of Rochester
Thursday, January 20th, 4:30pm to 5:30pm, Microsoft Teams

Abstract: The basic question we are going to address is, does a sufficiently "large" subset of Euclidean space contain a point configuration of a given type, such as an equilateral triangle, a long chain, or an arbitrary angle? The notion of large can be measured in terms of Hausdorff dimension, Lebesgue density, or even the number of points in the discrete case. This simple-sounding question has attracted the attention of many mathematicians in the past 75 years or so, with the flagship problems being the Erdos distance conjecture in geometric combinatorics and the Falconer distance conjecture in geometric measure theory. We are going to discuss these problems, the variety of techniques and ideas that are used to approach them, and, towards the end of the talk, describe some ongoing efforts to apply the resulting technology to the study of dimensionality of large data sets.

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Student Research Takes Aim At Brighter, Greener Future

saa — Thu, 08 Apr 2021 14:03:58 +0000

It's true: there’s no shortage of problems in our world that need solving. And in our little corner of the world at ��̽̽, there’s no shortage of talented minds that understand this truth: the time to start solving those problems is now. It's an "all-hands-on-deck" mindset shared by students and faculty that make it possible for hands-on learning opportunities to lead to new discoveries, innovations and research across every discipline. Here are just a few ways our students and faculty are working together to bring a brighter, greener, better future into focus.

Feeding Vulnerable Vermonters: Anitra Conover '21

Between her internship, data collection, surveys, interviews and questionnaires about food insecurity among Vermont’s refugees, junior global studies student Anitra Conover '21 hardly has a moment to consider that she’s never actually worked with the professor who’s been by her virtual side in this research for the better part of a year. For her, the work she and Professor Pablo Bose do to improve food security for resettled refugees in Chittenden County is all about making an impact, fast.

“These surveys and these interviews aren't just contributing to scholarship on food insecurity. They’re to benefit the participants of these surveys and interviews in a very immediate sense,” she says.

As a research assistant to Bose — a professor of global and regional studies and the 2021 George V. Kidder Outstanding Faculty Award winner — and as an intern with the Association of Africans Living in Vermont, Conover has been gathering information from hundreds of New Americans in the greater Burlington area about their access to nutritious, culturally appropriate foods and experiences with food assistance programs such as food banks, community pantries or delivery services.

When it comes to successfully serving these Vermonters, dietary restrictions, food preparation and cooking methods, for example, are all factors that could and should be considered alongside health and nutrition standards. Together, Conover and Bose are working to identify best practices and policies that might help bridge the gap between meals served to resettled refugees versus meals consumed.

“It's an issue that has been sharpened by the pandemic, but existed before and will exist afterwards,” Bose says. And for emergency food responders working through a global crisis, this research could help feed more community members when challenges arise and demand increases.

From her experience alongside Bose, Conover has come to realize that — just as her own, rich research experience can persist through a pandemic — the lifespan and impact of undergraduate reports and research can become so much more than simple grades on class papers. “What you do with a paper after a professor has graded it — based on its feasibility to enact the changes you want to see — has been something I learned with Professor Bose through this research that I wouldn’t have in class.”

Turning Wastewater into a Warning Whistle: Ben Page '21

Ben Page ’21 holds two glass jars containing water samples. “This is from the east Burlington wastewater treatment plant and this one is from the main treatment plant,” he says. Floating in the water are “some solids,” says Page, and traveling with the solids may be a few bits of RNA from COVID-19. Under the bright lights of ��̽̽’s Water Treatment and Environmental Nanotechnology Laboratory, Page will spin out samples from these jars in a nearby centrifuge to see if he can find any traces of the world-stopping virus.

When Page, a biomedical engineering student and Barrett Scholar, talks about his “love of transport phenomena,” he’s not daydreaming of race cars. Instead, he’s part of an ambitious research program, led by professor of civil and environmental engineering Raju Badireddy, to understand how flows of water, waste and life move through pipes, treatment plants and other parts of the built and natural environment. In this experiment, Page is helping Badireddy explore how wastewater might serve as an early-warning system for a spike in diseases. “Some viruses and other pathogens can take days or weeks to show symptoms,” Badireddy says, but antibodies and other traces of diseases may show up much sooner in the waste stream.

Using magnetic nanoparticles to bind virus fragments, Badireddy and his students are developing a system that they expect will be able to detect diseases in less than an hour after the water has been sampled — giving a rapid snapshot of how a community’s health may be changing.

In his first weeks as a freshman at ��̽̽, Page emailed Professor Badireddy to see if there were opportunities to help in his lab. “He instantly invited me to stop by — and I ended up staying for three hours and missed two classes,” Page recalls. And he’s been working on research in the lab ever since, with projects ranging from advanced membranes to extract phosphorus pollution, to better approaches to making wastewater and seawater drinkable. In the fall, Page will begin a PhD program in chemical engineering at UMass Amherst. “I see myself using chemistry and an understanding of fluid mechanics,” Page says, “to help solve some of the problems facing society.”

Preserving Trees in the Chesapeake: Dayna Ullathorne '21

When Dayna Ullathorne ’21 arrived at ��̽̽ four years ago, she joined the Outing Club. She loved hiking up into the mountains, where she could see the forest rolling into the distance. She’d decided to major in environmental sciences at the Rubenstein School, so she asked another member of the club — a junior in the same program — what courses he’d enjoyed. “He told me: working with GIS and geospatial technology,” Ullathorne says. “So I did that. And loved it.”

Ullathorne has kept hiking and skiing in the Green Mountains, but this year she’s also been soaring — remotely — over the forests and waters of the Chesapeake Bay. After taking a demanding class on GIS and remote sensing with Jarlath O’Neil-Dunne, director of ��̽̽’s Spatial Analysis Lab, Ullathorne was hired by the lab to help its scientists with a research project mapping the tree canopy across thousands of square miles surrounding the bay.

Now she’s part of a small army of undergraduate students in the lab — some as work-study, some as interns — who are turning aerial photographs and satellite images into land-use planning tools. The goal of the Chesapeake project: help landowners and decisionmakers understand how the forests in the bay area are changing. “Trees have so many benefits,” Ullathorne says — providing shade in cities, soaking up carbon in the fight against climate change and protecting the much-troubled Chesapeake Bay from pollution and headwaters erosion. “We’re figuring out where the trees are,” she says, “where new ones are growing, where they’ve been cut down.”

Her part of the research involves hours of looking at photos and LIDAR images — checking and correcting maps the ArcGIS software has automatically labeled. “Sometimes it will label shadows of trees as canopy, or there will be a building under the trees that needs to be identified,” she explains. Clicking between pictures, “It’s awesome to see how drastically a landscape can change in just four years — new agricultural areas, trees planted, a new pipeline.”

“Now when I go hiking," she says, "I wonder what the trail or woods looks like, from above.”

Empowering Data-driven Democracy: Clay Lerner '22

When it comes to making real, meaningful changes in our communities, there’s nothing more powerful than policy. And from Clay Lerner’s perspective, policy begins with people — informed people. But if there’s one thing his internship at an analytical consulting group and his research in POLS 230: Vermont Legislative Research Service (VLRS) have revealed, it’s that being informed is flat out hard.

For both his internship and VLRS class — a course designed in 1998 by Political Science Department Chair Anthony "Jack" Gierzynski to aid Vermont’s working General Assembly with non-partisan research and policy reports — Lerner ’22 is wading through public records, databases, legislation and voting records to help state lawmakers and national clients make informed, data-driven decisions and strategies.

And while those types of documents are legally accessible, “It's interesting how much information is publicly out there, yet it’s so difficult to get and to understand. I think it's made me more interested in trying to make information more accessible and easier to understand,” says the business administration student.

Outside the classroom, Lerner is chipping away at those barriers at his internship with The Burr Project, which aims to make politicians and government more transparent through a powerful database that centralizes information ranging from a politician’s voting record to their bill proposals. “There really is so much influential data out there,” he says. “While we can't prevent data from falling into the wrong hands, I think it's very important that we use it for good.”

Lerner is referring to the Cambridge Analytica scandal — which broke in 2018, revealing that personal data of Facebook users had been nefariously collected and used to influence elections years earlier — when he says “wrong hands.” But for all the data sleuthing that can go on behind computer screens, Lerner is researching and collecting public information the old-fashioned way.

“Honestly, it's a lot of reading through scholarly reports that somebody else has done, going into the footnotes or the work cited, and then seeing where that takes me. It's sort of going down a rabbit hole to find information from the first source.”

Farming of the Future: Shervin Razavi '21

When asked what he does with his time, Shervin Razavi '21 pauses, then says, “I spend a lot of time counting things, mostly organisms.” Which, as a double major in mathematics and biology, makes perfect sense. Earlier this year, he was working in a lab counting fruit flies. “I count larvae, mites, all kind of creatures,” he says, “and that takes a lot of time.” Instead of sliding into boredom, he began to dream of a technology that could do the counting for him. “It would probably just take a handful of code, and, theoretically, could do it faster and, eventually, be more accurate than me,” he says.

This is just one of several research efforts the Honors College student has underway, ranging from the purely imaginary to down-to-earth. One of them, close to the ground, is counting geese. Though he’s aiming to go to medical school, Razavi has been hard at work during the pandemic on a project to help farmers deal with the nuisance of Canada geese. With support from the student-led Catamount Innovation Fund, Razavi has been developing a system that would use infrared sensors to detect pests that might be chowing down on a farmer’s crop. “We’re starting by testing it on geese,” he says. An AI would be trained to read the thermal signature of the avian pests — and distinguish them from other critters on the farm. When the unwanted birds are remotely sensed, a computerized system could deploy drones that would swoop in, scare off the birds and leave the farmer, and their crops, undisturbed.

Working with ��̽̽ Plant and Soil researcher Arash Ghalehgolabbehbahani, a ��̽̽ engineering doctoral student and a local engineer, Razavi would like this Smart Farm project to aid regular farmers in the U.S. and beyond. “There’s a growing field of agritech called ‘precision agriculture,’ powered by satellites,” he says. “It’s very high-tech, but it’s often ridiculously expensive.” In the prototype experiments the team is testing at the ��̽̽ Horticulture Research Center, “we’re trying to develop a service that will be a reasonable price for mid-size farms,” he says.

Across his years at ��̽̽, Razavi has signed on to help with a staggering array of research projects. “It’s made me realize how big of a gap there is between the biological research world and the computational research world,” he says, “and how much potential there is for integration.”

Discovery Continues: Learn more about the research ��̽̽ students pursue at the Virtual Student Research Conference, April 15.

Writing for this piece contributed by Josh Brown and Kaitie Catania. Photos by Josh Brown, Sally McCay, Kelly Schulze/Spacial Analysis Lab and courtesy of featured students.

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Could the contents of these murky wastewater samples provide a clear and early warning sign when disease strikes a community? Senior Ben Page will analyze these samples from two different wastewater treatment plants in the greater Burlington area for indications of COVID-19. (Photo by Josh Brown)

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Putnam Problem Solving Group

Anonymous — Wed, 23 Sep 2020 14:02:38 +0000

We will be hosting Putnam problem solving sessions for undergrads on the 1st and 3rd Thursdays of every month from 12:00pm to 1:00pm.

Our first meeting will be on October 1st, hosted by faculty members Spencer Backman, Dan Hathaway, and Taylor Dupuy. These meetings will take place on the Microsoft Teams group "Putnam".

The Putnam exam is tentatively planned to be held on February 20th, 2021 – for more information about this celebrated intercollegiate exam, visit the official Putnam exam website: https://www.maa.org/math-competitions/putnam-competition .

Please email Professor Spencer Backman at Spencer.Backman@uvm.edu if you are interested in joining.

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Mathematics and Statistics

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Department of Mathematics & Statistics

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Kiki.Reno@uvm.edu

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Congratulations Patrick Mullins!

Anonymous — Mon, 13 Apr 2020 20:18:47 +0000

MS student Patrick Mullins has earned the Graduate College GTA of the year award in the lecturing category. We congratulate him on this well-deserved honor and thank him for bringing recognition to our department.

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Mathematics and Statistics

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Department of Mathematics & Statistics

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Kiki.Reno@uvm.edu

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Graduate

Statistics/Data Science Career Panel Presentation Video

saa — Thu, 09 Apr 2020 23:00:00 +0000

Statistics/Data Science Career Panel Presentation

An informal presentation and Q&A from Tuesday, April 7 with panelists from: RSG, Mass Mutual, UTC Aerospace, National Life, and Fixed Point Analytics.

https://web.microsoftstream.com/video/b7653c52-82f0-4e69-9a23-810d014ef63f

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Department of Mathematics & Statistics

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Career

Data Science

Science

Statistics

Statistics/Data Science Career Panel Presentation

saa — Fri, 03 Apr 2020 23:00:00 +0000

Statistics/Data Science Career Panel Presentation

Join us on Tuesday, April 7, from 7:00 to 8:15pm for an informal presentation and Q&A with panelists from:

RSG, Mass Mutual, UTC Aerospace, National Life, and Fixed Point Analytics.

The event will take place on Microsoft Teams, on the ��̽̽ Statistics & Data Science Career Night Team.

The join code for this team is 8rf4q81

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Department of Mathematics & Statistics

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Career

Data Science

Science

Statistics

����̽̽ - Mathematics and Statistics

Instant Evolution: AI designs robots from scratch in seconds. And they walk.

Evolution in Seconds

From xenobots to new organisms

Zero to walking within seconds

Rediscovering legs

Unfamiliar design

Potential future applications

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news_robot1.jpg

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Mathematics Graduate Student's NASA Internship

hunter_rehm_2_3.jpg

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����̽̽ Mathematics Colloquium - Taras Lakoba

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New Survey Findings Released from Innovative Prison Research Project

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uvmprisonresearch_1.jpg

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����̽̽ Mathematics Colloquium - Alex Iosevich

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Student Research Takes Aim At Brighter, Greener Future

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Putnam Problem Solving Group

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Congratulations Patrick Mullins!

Primary News Group

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Author email

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Statistics/Data Science Career Panel Presentation Video

Groups audience

Social Media

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Statistics/Data Science Career Panel Presentation

Groups audience

Social Media

Keywords

��̽̽ - Mathematics and Statistics

��̽̽ Mathematics Colloquium - Taras Lakoba

��̽̽ Mathematics Colloquium - Alex Iosevich