Johnston, Chapman Family Awards [Kris Jordan receives Chapman Family Teaching Award]

March 4, 2021

One professor started his Zoom lectures with funny photo backdrops and the line “Broadcasting today from in front of a [insert photo quip],” while another teleported into the famous PBS artist studio of Bob Ross, complete with wig.

Today, The Well shares the fourth in a series of stories introducing the winners of the 2021 University Teaching Awards. Join us each day this week as we celebrate teaching achievements by sharing personal stories about the winners.

Johnston Teaching Excellence Awards

Created in 1991, these awards recognize excellence in undergraduate teaching. Winners are nominated by Johnston Scholars and selected by a special committee of scholars in the James M. Johnston Scholarship Program. Two winners will receive $5,000 and a framed citation.

Maya Berry

assistant professor, department of African, African American and diaspora studies in the College of Arts & Sciences

Maya Berry

Maya Berry, faculty member since 2017.

Excerpt from award citation: A student wrote: “Class activities were designed to draw on both knowledge obtained from course readings as well as personal thoughts on the topics at hand, and she encouraged us to use artwork and music to inspire our educational pursuits in her course. She did not tell students that we were wrong — she regarded every opinion and thought as valid.”

Who was the best teacher you had and why?

I’ve been fortunate to have so many great teachers in my life, which is what ultimately led me to this profession. A common characteristic they all shared was the ability to create an environment that motivated me to challenge my preconceived conceptions and limitations and discover my own potential. They were both demanding of the utmost rigor and simultaneously created a space for vulnerability and self-reflection (it’s such a delicate balance!), so that by the end of our time together I had learned as much about myself as I did about the course material.

What does it take to be a good professor in 2021?

Active listening, compassion and creative thinking. When we shifted to remote learning on Zoom in the spring of 2020, I relied on my self-administered mid-semester student evaluations to inform my strategic lesson planning for the remainder of the semester. With that data generated by the students themselves, I was able to customize a remote learning plan that was best suited to the specific dynamic of each class while still honoring the course’s learning objectives.

Tell us a story about something creative you’ve done to engage your students.

Art is a powerful teaching tool. One of the pillars of my teaching philosophy revolves around the core belief that the arts have a unique ability to make vivid and tangible otherwise abstract concepts, histories and theories. One year, I weaved in a special collaboration with Duke Forum for Scholars and Publics, Carolina Performing Arts and the Ackland Museum into my Afro-Cuban Dance: History, Theory & Practice (AAAD261) class. During that year’s collaboration, students engaged with guest artist-scholars from the University of the West Indies and right here at Carolina Performing Arts and participated in a series of visits to the Ackland Art Museum. These encounters, in conjunction with the course content, built up students’ capacity to choreograph their own site-specific performance inspired by an exhibit on display at the Power Plant Gallery in downtown Durham. The students performed their original creations at the closing celebration of the exhibit for the public. They later adapted the performance for the Ackland’s Student Showcase and engaged in a Q&A for that public audience as part of their final grade.

Hans Christianson

associate professor, department of mathematics in the College of Arts & Sciences

Hans Christianson, faculty member since 2010.

Excerpt from award citation: Dr. Christianson’s classroom is also a collaborative space, where students work with him to consider, reconsider and parse through strategies to approach and solve a problem. Dr. Christianson’s students also see that he is committed to meeting them where they are to ensure they get as much out of his class as possible.

Who was the best teacher you had and why?

As an undergraduate at the University of Minnesota, I had two great professors who influenced me a lot. Dennis Hejhal and Victor Reiner both taught me that education does not end outside the classroom, and an “A student” goes to office hours at least four times a semester. I tell this to all my students. They both also taught me that original research in mathematics is attainable as an undergraduate and can be one of the most influential parts of education.

What does it take to be a good professor in 2021?

Teaching in 2021 is so intertwined with the pandemic that it is difficult to separate what parts of the job constitute teaching and what parts constitute student support. It is always important to respect and listen to the students and even more so with remote instruction. Taking time to listen to the concerns and struggles of students helps make sure they know there is a human being on the other end of the line whose top priorities are the health and safety of the students, as well as their academic success, and informs the instructor about the pace and content of lectures. With so many unknowns with remote teaching, being flexible and patient with students (and colleagues!) is essential.

Tell us a story about something creative you’ve done to engage your students.

Teaching evolves constantly, and remote instruction presented us all with new obstacles. I like to interact with my students a lot during lectures. One thing I tried (that failed) last semester was to get a laugh track going that I could play whenever I tell a joke. One thing I tried (that succeeded) was to frequently change my Zoom background with photos I have taken in the last few years. I started my lectures with “Broadcasting today from in front of [insert photo quip].” My favorite was a giant apple pie at Thanksgiving. At the end of the semester, a student posted on our Piazza forum: “Full Collection: ‘Today we are broadcasting from … ’” with a list of my quotes — they had been keeping track all semester! Knowing I was reaching my students, if only for a laugh, during the most difficult semester any of us have had was one of the high points in my career.

Chapman Family Teaching Awards

Created in 1993 with a gift during the Bicentennial Campaign from Max Carrol Chapman Jr. ’66 on behalf of the Chapman family, these awards honor distinguished teaching of undergraduate students. The award carries a stipend of $30,000 to be used over the period of five years.

Todd Austell

teaching professor, associate director of undergraduate studies, STEM academic adviser, department of chemistry in the College of Arts & Sciences

Todd Austell, faculty member since 1998.

Excerpt from award citation: From a student: “Professor Austell provided so much support, encouragement and tools for students to succeed that I not only understood concepts but enjoyed and thrived in my learning. I consistently felt challenged, driven and excited to plunge myself deeper into the subject.”

Who was the best teacher you had and why?

My high school chemistry teacher, Dick Hamrick, who was the most dynamic, motivating and caring teacher I’ve ever encountered. He massively influenced many to pursue careers in science and medicine.

What does it take to be a good professor in 2021?

Patience, persistence and true understanding of how to love and care for students during one the most challenging times of all our lives.

Tell us a story about something creative you’ve done to engage your students.

I realized a long time ago my role at Carolina and in life is far more than just teaching students. I’m blessed to be where I am on this campus and in my life. With great blessings come great responsibilities. I’m called to love my students in a Christ-like way every minute of every day, and that’s what I (most often imperfectly) try to do. I believe in letting my students know early on that I am more than just their instructor for the semester, that I do love them and feel blessed to get to be in my role with them. Lastly, I desire to be in their corner far beyond the time they are my class. I AM FOR THEM … and try to make that clear every day in my communications.

Glenn Hinson

associate professor, departments of anthropology and American studies in the College of Arts & Sciences

Glenn Hinson, faculty member since 1989.

Excerpt from award citation: Professor Hinson’s community-engaged project has impacted students profoundly. One student nominator described the experience as “truly transformative” and elaborated further to say, “He taught me that reckoning and reconciliation are only possible if we conjure the most vulnerable aspects of our own lives and experiences. Research does not have to be cold and impersonal. It can be deeply human.”

Who was the best teacher you had and why?

Hands down, it was the folklore professor Kenny Goldstein, who taught in the graduate department of folklore and folklife at the University of Pennsylvania. Kenny was an activist and engaged scholar, someone who encouraged students to step beyond the limits of the academy and to engage broad publics in their scholarship, working with communities as equal partners in the pursuit of shared intellectual/programmatic/political ends. For Kenny — who came to the academy from a background as an activist — scholarship was all about contribution. He wasn’t interested in how many articles you had published or how many books you had written; he wanted to know how you had changed the world, and how the change had bettered the lives of the disempowered, of those who had been strategically and systematically oppressed.

What does it take to be a good professor in 2021?

Awareness, engagement and a willingness to listen to — and, when needed, be guided by — the wisdom of our students.

Tell us a story about something creative you’ve done to engage your students.

Before the pandemic, in the “By Persons Unknown: Race and Reckoning in North Carolina” first-year seminar (first taught in Spring 2020), students investigated the heretofore untold story of the Norlina 18, a group of Black men in Warren County who were arrested in January 1921 after defending their community from an advancing white mob. Within 24 hours of their arrest, two of these men were lynched; the others were imprisoned in the state penitentiary for periods ranging from four months to eight years. Our job was to learn who these men were, what impact these murders and imprisonments had on their families and what happened to them and their descendants. To be able to tell their stories, we had to do more than comb through archival records; we needed to visit the site of the gunfight that led to their arrest, to view the communities in which they lived, to step into the fields where they labored, to visit the jail where they were imprisoned, to stand in the courtroom where they were tried. So we did, traveling by bus for a long day in Warren County, moving from site to site. At each stop, Black community members guided our way, offering trenchant stories about oppression and resilience and inviting our reflections. The wisdom of these community guides — coupled with the experience of actually stepping into the spaces of the stories we were investigating — brought the archival research alive, inspiring all of us to recognize our responsibility as chroniclers of untold stories and as contributors to community efforts to recover erased histories.

Kris Jordan

teaching assistant professor, department of computer science in the College of Arts & Sciences

Kris Jordan, faculty member since 2015.

Excerpt from award citation: He is engaging to each of his students, creating a comfortable in-class atmosphere, and he has an incredible awareness of the different backgrounds that his students have come from. This awareness has allowed Professor Jordan to help students who may not have the necessary background in math or technology, and he has propelled students to continue in the computer science field who otherwise would have chosen different courses of study.

Who was the best teacher you had and why?

I studied computer science as an undergraduate at Carolina, and the best teachers I ever had are faculty members here. Many were fantastic but three were instrumental in supporting me in independent studies and research: Prasun Dewan, Gary Bishop and Diane Pozefsky. When I returned to Chapel Hill nearly a decade later, these three were once again great role models and mentors in becoming an educator. Each treated me as a respected colleague, both as an undergraduate student and as junior faculty, which is a cultural tradition in Carolina’s Department of Computer Science that I work to carry forward.

What does it take to be a good professor in 2021?

To be a good teacher in 2021 requires creativity and flexibility. During the COVID-19 pandemic, our “classrooms” changed, our modes of instruction and content delivery changed and our means for assessment changed. Success requires adapting to those changes and looking for opportunities to take on new challenges previously unthinkable. Around 50 of my students this past year participated in Carolina Away and completed my courses from China, India, Japan, Turkey and other international locations. Adapting my courses to equitably serve students participating in time zones 12 hours offset from Eastern Standard Time has led to my teaching team improving its practices by becoming more flexible without losing its high structure design. Many of the innovations required to make the most of teaching in 2021 will improve what University teaching and learning looks like after the pandemic.

Tell us a story about something creative you’ve done to engage your students.

I teach Computer Science 110, a course that introduces students to the fundamentals of programming and data science at Carolina. One of the most notoriously challenging topics taught is recursion. A classic example of recursion is the definition of a factorial function, but factorial is so dull that someone made its symbol an exclamation point to try and keep students awake for it!

I find recursive art to be a more engaging, visually exciting and intellectually stimulating means to introduce students to recursive thinking. A favorite lecture activity of mine is tasking students with writing code to procedurally generate trees with computer graphics. When we reach that segment of lecture, I put on my Bob Ross wig and we “paint” some happy, little trees together using recursion as our brush. This year, teaching in front of a green screen instead of a lecture hall, I was able to “teleport” to the iconic PBS show’s set to host “The Joy of Programming” for the first time. Learning how to code is often frustrating and error-prone, so I hope to impart the wisdom and energy of the late Bob Ross in my course: “We don’t make mistakes [in programming]; we have happy accidents.”

Lisa Woodley

clinical associate professor, School of Nursing

Lisa Woodley, faculty member since 2003.

Excerpt from award citation: Students in her class do not passively receive information but are actively and affectively engaged through a range of teaching tools including humorous YouTube videos, emotional patient narratives and personal stories of success and failure from Professor Woodley’s own nursing career.

Who was the best teacher you had and why?

I have had many exemplary teachers over my lifetime, but the one who rises to the top is my dad. Don Woodley is a retired high school Latin teacher living in Southern Ontario, Canada. He taught me that the key to effective teaching centers on relationships built with students. From a young age, I watched how he cared for and about his students as individuals. This in turn fueled their enthusiasm and excitement for the subject he taught. His unwavering work ethic, attention to detail and creativity were ever-present, and his passion and love for his career was obvious to everyone around him. He never hesitated to go the extra mile for his students and regularly served as a mentor for those struggling with life crises. He taught me how to make a difference in students’ lives far beyond the classroom and what it means to be a true teacher.

What does it take to be a good professor in 2021?

Good professors serve as role models and guides in our disciplines. Our words and actions matter. Especially now as we continue to battle the COVID-19 pandemic and national strife, our students must feel like their learning spaces are safe and welcoming. Good professors are passionate about what they teach and are student-centered, seeking to engage, inspire and challenge their learners and genuinely care about how they best learn. They offer clear explanations and cutting-edge information, help students connect concepts and push students to new heights, while remaining humble and approachable. In my experience, the magic happens when these conditions are present.

Tell us a story about something creative you’ve done to engage your students.

In week one of my undergraduate pediatric nursing class, I introduce the story of “Stone Soup.” This centuries-old story tells of a stranger who comes to a remote village with only a large cooking pot, seeking to make soup.

Within the class, we discuss how the story of Stone Soup relates to student engagement and learning. I point out that faculty-based lectures are akin to single-ingredient soups, unlike the rich depth of flavors that arise when students and faculty from a variety of backgrounds share experiences and ideas. Next, using the Poll Everywhere online platform, all class members (including faculty) anonymously indicate on a global map their family’s country of origin, providing an immediate visual cue about the collective geographical diversity in the classroom. We also discuss how collectively we represent other aspects of diversity, such as religion, class and sexual identity. These activities provide a platform upon which discussions of culturally responsive pediatric nursing care are subsequently based in the course.

Alumni Profile: Mentor Katherine Griffin (B.S. 2020), mentee Tarini Ramesh reflect on Alumni Mentor Program experience

March 3, 2021
Tarini Ramesh (top) and Katherine Griffin meet as part of the UNC CS Alumni Mentor Program
Tarini Ramesh (top) and Katherine Griffin meet as part of the UNC CS Alumni Mentor Program

Designed to facilitate a professional development relationship between alumni industry mentors and current students in the Department of Computer Science, the UNC CS Alumni Mentor Program launched in the fall of 2019 with over 80 participants. Since then, the program has continued to grow in number, with both alumni and students eager to participate. 

Relying almost entirely on virtual interactions over the past year has made it more challenging to maintain meaningful connections and collaborations with others. But perhaps more than ever, these relationships and interactions provide valuable guidance and camaraderie that can help students learn and grow during this difficult time.

Despite the challenges of building a mentor/mentee relationship virtually, sophomore computer science and economics double-major Tarini Ramesh and alumna Katherine Griffin (B.S. 2020) have forged a bond through this experience that will extend beyond their year-long structured mentoring relationship.

Having graduated only months into the COVID-19 pandemic, Griffin experienced an abrupt end to her final semester at UNC. For the Class of 2020, everything moved online in a few weeks. To make things even more difficult, Griffin and her peers also had to adapt to an all-online environment as they began their professional careers. After departing under such unusual circumstances, Griffin sought out opportunities to give back to the department and stay connected. The Alumni Mentor Program seemed like a great fit. As a woman in tech and a software engineer at GitHub, she was eager to connect with an undergraduate student who could benefit from her experiences.

Ramesh, a sophomore double-major interning at Lenovo, has never shied away from opportunities to get involved and network across industry. After reading about the opportunity to join the mentorship program in a student newsletter, she decided to apply.

Coincidentally, upon being paired, Griffin and Ramesh realized that Griffin had served as a teaching assistant for one of Ramesh’s courses in the spring. Having a previous connection has served them well in developing a trusting and supportive mentoring relationship. After a semester and a half in the mentoring program, both look back with incredible fondness regarding their experiences. 

Ramesh admitted jokingly, “I came hoping at-minimum I’d find a future reference, but now I’ve found a friend.” 

The two meet weekly via Zoom, where Griffin shares real-world experiences of a software engineer and Ramesh shares about her future goals and classroom experiences and asks questions. Ramesh appreciates that she is “learning all the little things that I’d be doing, including some of the not-so-glamorous tiny details.” 

Reflecting on the importance of technology and careers in the field, Griffin always reminds Ramesh that through all aspects of this journey, no matter how minimal, this work impacts millions of people around the world. 

As a mentor, Griffin reflects on all the ways she’s grown and learned from the experience and what it means to be able to share it with Ramesh.

“It is so hard to find women in computer science, let alone women in computer science that are willing to sit and talk with you about the real experience,” Griffin said. “I have enjoyed sharing all I’m learning professionally, and while I never want to discourage her from following her dreams, I want to share the realities of the experience.”

Griffin has also enjoyed watching Ramesh learn and grow. From sharing advice on college courses to recounting day-to-day challenges on the job, Griffin finds mentorship to be an incredibly rewarding experience. After Ramesh secured an internship with Microsoft Explore this summer, both relished the opportunity to celebrate her success together. It was exciting for both to see all of Ramesh’s hard work come to fruition. In these moments, the two say that they are grateful to be a part of this type of program.

Acknowledging that building a mentoring relationship takes a lot of dedication and effort, particularly in a virtual environment, both are proud of the work they have put in over the last two semesters and encourage others to make the decision to go all-in and invest in the experience. 

“Mentoring is a big mix of rewards,” Griffin said. “I’ve learned that if you give it your all, you get out what you put in. If willing to give it a chance and lean in to the experience, the additional work is worth it.” 

If you are interested in serving as an Alumni Mentor in the UNC CS Alumni Mentor Program, learn more here on the program website.

Nirjon receives NSF CAREER Award

February 22, 2021

Shahriar Nirjon has received an NSF CAREER AwardShahriar Nirjon, assistant professor of computer science at UNC-Chapel Hill and director of the UNC Embedded Intelligence Lab, has received a Faculty Early Career Development (CAREER) Award from the National Science Foundation (NSF). The CAREER program is a Foundation-wide activity that offers NSF’s most prestigious awards in support of junior faculty who exemplify the role of teacher-scholars through outstanding research, excellent education and the integration of education and research within the context of the mission of their organizations.

This five-year, $561,000 grant, titled “CAREER: Toward Embedding Perpetual Intelligence into Ultra-Low-Power Sensing and Inference Systems,” will support his continued research on making small, portable,  resource-constrained, embedded systems capable of sensing, learning, adapting, and evolving over an extended period of time.

Years of technological advancements have made it possible for small, portable, electronic devices to last for years on battery power, and run forever when powered by harvesting energy from their surrounding environment. Unfortunately, the prolonged life of these ultra-low-power systems poses a fundamentally new problem. Although these devices last for an extended period of time, programs that run on them become obsolete when the nature of sensory input or the operating conditions change. The effect of continued execution of such an obsolete program can be catastrophic. For example, if a cardiac pacemaker fails to recognize an impending cardiac arrest because the patient has aged or their physiology has changed, these devices will cause more harm than good. Hence, being able to react, adapt, and evolve is necessary for these systems to guarantee their accuracy and response time.

This CAREER project is aimed at devising algorithms, tools, systems, and applications that will enable ultra-low-power, sensor-enabled, computing devices capable of executing complex machine learning algorithms while being powered solely by harvested energy. As opposed to common practices where a fixed classifier runs on a device, this project takes a fundamentally different approach, wherein a classifier is constructed in a manner that allows it to adapt and evolve to changes in the sensory input or application-specific requirements, such as the time, energy, and memory constraints, during the extended lifetime of the system.

More details on this award can be found on the NSF website.

Nirjon joined the Department of Computer Science in 2015. Prior to joining UNC, he was a research scientist at Hewlett-Packard (HP) Labs. He received his Bachelor of Science and Master of Science in computer science and engineering from the Bangladesh University of Engineering and Technology (BUET) and received his Doctor of Philosophy in computer science from the University of Virginia, Charlottesville.

‘Changing the game’: Black in Technology works to support Black students in computer science

February 2, 2021
Former UNC student, Charlie Helms poses for a virtual portrait with his old college laptop in his Seattle apartment on Jan. 27, 2021. Helms co-founded Black in Technology, an organization dedicated to helping students of color in Computer Science.

Photo by Chase Cofield | The Daily Tar Heel

Former UNC student, Charlie Helms poses for a virtual portrait with his old college laptop in his Seattle apartment on Jan. 27, 2021. Helms co-founded Black in Technology, an organization dedicated to helping students of color in Computer Science.

Prior to arriving at UNC, 2020 graduate Charlie Helms had only briefly heard about the field of computer science. But when he attended UNC’s admitted students day, he was immediately drawn to the Black and Latinx computer science group that the computer science department advertised.

“I was like, ‘Oh my God, I’m gonna have people that look like me that are coders,’” Helms said. “I’ve never met a Black computer scientist before, so I was like, ‘This is amazing. It’s a perfect match.’”

But after initially struggling in coursework for COMP 110: Intro to Programming at UNC, he began searching for the club that initially drew him to the University. To his disappointment, Helms discovered that the club had been inactive for nearly two years.

For Helms, the next logical step was to start his own organization. And after connecting with Olivia McPhaul, another UNC graduate who now works as a cyber risk analyst at Deloitte, Black in Technology was born.

Black in Technology has planned numerous events to support Black UNC students in STEM and collaborated with other groups, including Xcel, queer_hack and the National Society of Black Engineers.

The organization has also planned events with companies including Cisco and Microsoft, hosted Black software engineers and developers to talk to BiT members about their experiences working in those roles and offered opportunities for resume workshops and mock interviews.

“These are things that we need to help connect us with these professionals,” Helms said. “Putting your application in a portal is only seeing so much, but when you’re in person talking to them, it’s changing the game completely.”

After one event with Cisco, some members got internship and full-time job offers — including one of McPhaul’s closest friends.

“He said to me: ‘This is what I see as my dream job. I am doing something that I enjoy, so thank you for having this opportunity,’” she said. “Hearing something like that and actually seeing it come to fruition was amazing.”

In addition to professional development events, BiT has partnered with the Black Student Movement at UNC to help get more Black students interested in technology and the computer science major.

For McPhaul, the co-founder of Black in Technology, the drive behind wanting to support Black students at UNC came from attending a conference for students to learn more about career paths and technology.

She met Helms through Brandi Day, the former diversity and inclusion coordinator for the department of computer science. Day eventually became the group’s adviser.

“I can say this, and maybe Charlie can agree, that we can attribute a lot of our success to her, because she cares so much,” McPhaul said. “Sometimes just having that one faculty member supporting you gives you that confidence and boost to say, ‘I’m doing what I need to be doing.’”

Helms said he advises other students to reach out to others when they need help. He said once he reached out for help himself, he saw a huge shift in his grades and class experiences.

“I was understanding the material better, and I feel like I had better friendships established by actually reaching out and leaning on my community more,” Helms said.

McPhaul said BiT and other organizations for people of color are important because without them, voices will be stifled. Since UNC is a predominantly white institution, she said students of color will continue to feel unseen and unheard until action is taken on the student and University level.

“Lifetime success starts with our foundation,” she said. “I want something to define every single person in a way that they feel like it can propel them exactly where they need to be in life.”

Amanda Harris, a UNC junior and president of Black in Technology, said she joined the organization during her first year after meeting Helms in the Chancellor’s Science Scholars Program.

Harris said being the president of BiT during the pandemic involved a shift in ideas and events for members.

“We definitely have seen a decrease in numbers and our events, unfortunately, so we’re trying to come up with new ideas to keep our members engaged,” Harris said.

Harris said it is important for Black students to be involved in technology because products are often made by white people — and not with people of color in mind. She said this often results in products that are inherently biased and do not cater to everyone’s needs, which further widens a gap that already exists between opportunities of races.

“We really want to be a support system to uplift people who are interested in technology, and hopefully even pursue it so that we can have a world with technological devices that cater to everyone,” she said.

For Black students, Helm said there are many different obstacles to face when going into STEM. The advice he gives to future members or other Black students in STEM is to stick with it.

“Until you know it, you won’t love it,” he said. “I had to keep that in mind myself: the reason I don’t love it is because I don’t know it well. I have to fully take the time to study it and become more comfortable with it for it to feel like second nature.”

university@dailytarheel.com

Three College faculty, including James Anderson, named fellows of the American Association for the Advancement of Science

November 30, 2020
November 24, 2020
scene of the Old Well peaking through the leaves of a tree with red berries across Cameron Ave. from the Well.
(photo by Donn Young)
James Anderson
James Anderson

Three faculty members of the College of Arts & Sciences at UNC-Chapel Hill have been named fellows of the American Association for the Advancement of Science (AAAS).

Fellows are recognized for their research; teaching; services to professional societies; administration in academia, industry and government; and communicating and interpreting science to the public. They are elected annually.

Gregory Copenhaver
Gregory Copenhaver

New fellows from the College include:

  • James Anderson (computer science): For contributions to the implementation and analysis of multiprocessor and multicore real-time systems and for service to the real-time systems research community.
  • Gregory Copenhaver (biology): For distinguished contributions to the field of plant molecular genetics, particularly for novel insights into plant reproductive biology.
  • Richard Smith (statistics and operations research): For distinguished contributions to statistics, particularly the statistical analysis of extreme events and environmental applications, including climate change and air pollution. Smith holds a joint appointment in biostatistics in the Gillings School of Global Public Health.

This year 489 members have been awarded the honor by AAAS because of their scientifically or socially distinguished efforts to advance science or its applications.

The new fellows will be formally announced in the AAAS News & Notes section of the journal Science on Nov. 27. A virtual fellows forum — an induction ceremony for the new fellows — will be held on Feb. 13, 2021.

Richard Smith
Richard Smith

The tradition of AAAS fellows began in 1874. The honor comes with an expectation that recipients maintain the highest standards of professional ethics and scientific integrity.

AAAS is the world’s largest general scientific society and publisher of the journal Science, as well as Science Translational MedicineScience Signaling; a digital, open-access journal, Science AdvancesScience Immunology; and Science Robotics. AAAS was founded in 1848 and includes more than 250 affiliated societies and academies of science, serving 10 million individuals. The nonprofit AAAS is open to all and fulfills its mission to “advance science and serve society” through initiatives in science policy, international programs, science education, public engagement and more.

For additional information about AAAS, see www.aaas.org.

For more on the AAAS fellows, visit www.aaas.org/fellows/listing.

This could lead to the next big breakthrough in common sense AI

November 10, 2020

Researchers are teaching giant language models how to “see” to help them understand the world.

November 6, 2020

You’ve probably heard us say this countless times: GPT-3, the gargantuan AI that spews uncannily human-like language, is a marvel. It’s also largely a mirage. You can tell with a simple trick: Ask it the color of sheep, and it will suggest “black” as often as “white”—reflecting the phrase “black sheep” in our vernacular.

That’s the problem with language models: because they’re only trained on text, they lack common sense. Now researchers from the University of North Carolina, Chapel Hill, have designed a new technique to change that. They call it “vokenization,” and it gives language models like GPT-3 the ability to “see.”

It’s not the first time people have sought to combine language models with computer vision. This is actually a rapidly growing area of AI research. The idea is that both types of AI have different strengths. Language models like GPT-3 are trained through unsupervised learning, which requires no manual data labeling, making them easy to scale. Image models like object recognition systems, by contrast, learn more directly from reality. In other words, their understanding doesn’t rely on the kind of abstraction of the world that text provides. They can “see” from pictures of sheep that they are in fact white.

AI models that can parse both language and visual input also have very practical uses. If we want to build robotic assistants, for example, they need computer vision to navigate the world and language to communicate about it to humans.

But combining both types of AI is easier said than done. It isn’t as simple as stapling together an existing language model with an existing object recognition system. It requires training a new model from scratch with a data set that includes text and images, otherwise known as a visual-language data set.

The most common approach for curating such a data set is to compile a collection of images with descriptive captions. A picture like the one below, for example, would be captioned “An orange cat sits in the suitcase ready to be packed.” This differs from typical image data sets, which would label the same picture with only one noun, like “cat.” A visual-language data set can therefore teach an AI model not just how to recognize objects but how they relate to and act on one other, using verbs and prepositions.

But you can see why this data curation process would take forever. This is why the visual-language data sets that exist are so puny. A popular text-only data set like English Wikipedia (which indeed includes nearly all the English-language Wikipedia entries) might contain nearly 3 billion words. A visual-language data set like Microsoft Common Objects in Context, or MS COCO, contains only 7 million. It’s simply not enough data to train an AI model for anything useful.

“Vokenization” gets around this problem, using unsupervised learning methods to scale the tiny amount of data in MS COCO to the size of English Wikipedia. The resultant visual-language model outperforms state-of-the-art models in some of the hardest tests used to evaluate AI language comprehension today.

“You don’t beat state of the art on these tests by just trying a little bit,” says Thomas Wolf, the cofounder and chief science officer of the natural-language processing startup Hugging Face, who was not part of the research. “This is not a toy test. This is why this is super exciting.”

From tokens to vokens

Let’s first sort out some terminology. What on earth is a “voken”?

In AI speak, the words that are used to train language models are known as tokens. So the UNC researchers decided to call the image associated with each token in their visual-language model a voken. Vokenizer is what they call the algorithm that finds vokens for each token, and vokenization is what they call the whole process.

The point of this isn’t just to show how much AI researchers love making up words. (They really do.) It also helps break down the basic idea behind vokenization. Instead of starting with an image data set and manually writing sentences to serve as captions—a very slow process—the UNC researchers started with a language data set and used unsupervised learning to match each word with a relevant image (more on this later). This is a highly scalable process.

The unsupervised learning technique, here, is ultimately the contribution of the paper. How do you actually find a relevant image for each word?

Vokenization

Let’s go back for a moment to GPT-3. GPT-3 is part of a family of language models known as transformers, which represented a major breakthrough in applying unsupervised learning to natural-language processing when the first one was introduced in 2017. Transformers learn the patterns of human language by observing how words are used in context and then creating a mathematical representation of each word, known as a “word embedding,” based on that context. The embedding for the word “cat” might show, for example, that it is frequently used around the words “meow” and “orange” but less often around the words “bark” or “blue.”

This is how transformers approximate the meanings of words, and how GPT-3 can write such human-like sentences. It relies in part on these embeddings to tell it how to assemble words into sentences, and sentences into paragraphs.

There’s a parallel technique that can also be used for images. Instead of scanning text for word usage patterns, it scans images for visual patterns. It tabulates how often a cat, say, appears on a bed versus on a tree, and creates a “cat” embedding with this contextual information.

The insight of the UNC researchers was that they should use both embedding techniques on MS COCO. They converted the images into visual embeddings and the captions into word embeddings. What’s really neat about these embeddings is that they can then be graphed in a three-dimensional space, and you can literally see how they are related to one another. Visual embeddings that are closely related to word embeddings will appear closer in the graph. In other words, the visual cat embedding should (in theory) overlap with the text-based cat embedding. Pretty cool.

You can see where this is going. Once the embeddings are all graphed and compared and related to one another, it’s easy to start matching images (vokens) with words (tokens). And remember, because the images and words are matched based on their embeddings, they’re also matched based on context. This is useful when one word can have totally different meanings. The technique successfully handles that by finding different vokens for each instance of the word.

For example:

Here is her contact.
Some cats love human contact.

The token is the word “contact” in both examples. But in the first sentence, context suggests that the word refers to contact information, so the voken is the contact icon. In the second sentence, the context suggests the word refers to touch, so the voken shows a cat being stroked.

The researchers used the visual and word embeddings they created with MS COCO to train their vokenizer algorithm. Once trained, the vokenizer was then able to find vokens for the tokens in English Wikipedia. It’s not perfect. The algorithm only found vokens for roughly 40% of the tokens. But that’s still 40% of a data set with nearly 3 billion words.

With this new data set, the researchers retrained a language model known as BERT, an open-source transformer developed by Google that predates GPT-3. They then tested the new and improved BERT on six different language comprehension tests, including SQuAD, the Stanford Question Answering Dataset, which asks models to answer reading comprehension questions about a series of articles, and SWAG, which tries to trip up models with subtleties of the English language to probe whether it’s merely mimicking and memorizing. The improved BERT performed better on all of them, which Wolf says is nothing to sneeze at.

The researchers, Hao Tan, a PhD student, and Mohit Bansal, his advisor, will be presenting their new vokenization technique in two weeks at the Conference on Empirical Methods in Natural Language Processing. While the work is still early, Wolf sees their work as an important conceptual breakthrough in getting unsupervised learning to work for visual-language models. It was a similar spark that helped dramatically advance natural-language processing back in the day.

“In NLP, we had this huge breakthrough over two years ago, and then suddenly NLP was a field where a lot of things were happening and it kind of got ahead of all the other AI fields,” he says. “But we have this problem of connecting text with other things. So it’s like this robot that is only able to talk but cannot see, cannot hear.”

“This paper is one example where they managed to connect it to another modality and it works better,” he says. “You could imagine that maybe some of these techniques could be reused when you want to leverage this really powerful language model in a robot. Maybe you use the same thing to connect the robot’s senses to text.”

NC Begins Smartphone Coronavirus Contact Tracing, But Will Enough People Use The App? [Prof. Samarjit Chakraborty interviewed]

November 6, 2020

WFAE | By Greg Barnes | North Carolina Health News
Published October 31, 2020 at 8:51 AM EDT

This story originally appeared in North Carolina Health News.

About a quarter of a million people in North Carolina have now downloaded a cell phone app that alerts them when they come into close contact with someone who has tested positive for the coronavirus.

The idea behind the app, launched by the N.C. Department of Health and Human Services on Sept. 22, is to help quickly track infections and slow the spread of COVID-19, which is increasing dramatically across the state and the country as the weather turns colder.

The app, called SlowCOVIDNC, relies on users to voluntarily and anonymously report a close contact with an infected person and to then get tested and self-quarantine if necessary. The app can be downloaded for free on iPhone or Android cell phones through the Apple App Store and the Google Play Store.

Since the app’s launch, DHHS has focused its use at the state’s colleges and universities and is now also seeking to involve more businesses, DHHS spokeswoman Kelly Haight Connor said in an email last week.

So far, Haight Connor wrote, the app has sent 346 exposure notifications, most of those beginning Oct. 3. The app has led 46 people to anonymously notify others of their positive COVID-19 test results.

It is not clear where those 346 exposure notifications came from or whether the bulk of people downloading the app are college students.

“I don’t think we have any demographic info about those who have downloaded the app since it’s completely anonymous,” Haight Connor said in another email.

Kimberly Powers, an associate professor at UNC’s Gillings School of Public Health, sees issues with the app, including whether people who use it will get tested and self-quarantine if necessary. But she says the benefits outweigh any issues.

“As with any single intervention against COVID-19, apps like these are unlikely to be, you know, a miracle or a silver bullet or a panacea, but, again, I think they offer an additional tool to help us combat the spread,” Powers said.

Bluetooth Reliability
Reliability of the app could also be an issue, said Samarjit Chakraborty, a professor in UNC’s Department of Computer Science.

“The contact tracing app should be used, and it will certainly help, so it is a good thing,” Chakraborty said. “The only pitfall is that we have to, all of us, and especially the doctors and policymakers, realize that these contact tracing apps are not 100% reliable.”

Chakraborty was among the authors of a report that studied why smartphone-based contact tracing could be unreliable, and what steps could be taken to improve their reliability.

In it, the researchers explain that contact tracing apps rely on a mechanism called Neighbor Discovery, which involves smartphones transmitting and scanning for Bluetooth signals to record their mutual presence whenever they are in close proximity.

“The hardware support and the software protocols used for ND in smartphones, however, were not designed for reliable contact tracing,” the researchers reported. “Even though their Bluetooth radios support the essential features necessary for contact tracing, tracing reliability will always be limited, potentially leading to false positives and/or missed contacts.”

Chakraborty explained that Bluetooth works by sending out beacons, searching to pair with another Bluetooth device in close proximity. It can take up to 5 minutes for two cell phones to pair, he said.

“You know, you have your phone and I have my phone and both our phones are in our pockets or in our bags, and we cross each other and the phones are supposed to register this and that registration process will not happen with 100% reliability,” he said.

Chakraborty’s paper concludes that an as-yet-developed wearable device, such as a wristband, could eliminate many of the shortcomings of a smartphone app and be much more effective at contact tracing.

Chakraborty acknowledges that such a wearable device would face logistical hurdles, including speed of development and access to the masses. But he said it could be beneficial to use in places such as schools, where children share close spaces and might not be able to use smartphones.

SlowCOVIDNC.jpg

NCDHHS
Both private citizens and some computer science experts are nervous that the SlowCOVIDNC app is too invasive.

Privacy Concerns
Privacy concerns are the biggest reason people might not use the app.

Scientists in the United States and around the globe are taking the issue of anonymity — and privacy — extremely seriously. In April, hundreds of scientists from 28 countries signed a memo stating their privacy concerns with apps that use GPS as a tracking device.

“Research has demonstrated that solutions based on sharing geolocation (i.e., GPS) to discover contacts lack sufficient accuracy and also carry privacy risks because the GPS data is sent to a centralized location,” the memo states. ”For this reason, Bluetooth-based solutions for automated contact tracing are strongly preferred when available.”

The researchers agreed that the apps “must only be used to support public health measures for the containment of COVID-19. The system must not be capable of collecting, processing, or transmitting any more data than what is necessary to achieve this purpose.”

Among those who signed the memo was Anupam Das, an assistant professor in N.C. State’s Department of Computer Science who specializes in privacy issues. Although Das said he has not analyzed the app that DHHS is using, he suspects it was developed by Google and Apple.

“If so, it should be fine,” Das said in an email.

The app uses Bluetooth technology based on the Exposure Notification System developed by Google and Apple. Many other states and countries are using the same system.

Regardless, people may be reluctant to download the app because of privacy concerns.

SlowCOVIDNC_LINE.jpg

NCDHHS
About a quarter of a million people in North Carolina have now downloaded a cell phone app that alerts them when they come into close contact with someone who has tested positive for the coronavirus.

Model Gives Promising Data
At the University of Oxford, researchers developed a model that found that in Washington state, coronavirus infections could be reduced by 8% and deaths by 6% if just 15% of the population used the tracing smartphone app in addition to traditional contact tracing.

“Our models show we can stop the epidemic if approximately 60% of the population use the app, and even with lower numbers of app users, we still estimate a reduction in the number of coronavirus cases and deaths,” Oxford professor Christophe Fraser said in a university new release in September.

That may sound great on paper, but getting a large percentage of people to download the app could be a major challenge.

survey conducted by Avira, a computer security software company, found that more than 71% of Americans who responded said they don’t plan to download a contact tracing app, mostly because of concerns over digital privacy.

This article first appeared on North Carolina Health News and is republished here under a Creative Commons license.

CS hackathons find new home online

October 30, 2020

When classes at UNC shifted fully online, so did events, such as corporate recruiting and annual hackathons. In October, UNC Computer Science student leaders and staff worked together to hold two popular hackathons, Carolina Data Challenge and HackNC, all-online for the first time.

A hackathon is a coding competition in which participants team up to develop brand new software projects. At the end of a short competition period, typically only 24 to 48 hours, the finished projects are presented to a panel of faculty and industry judges for prizes. For in-person events, the goal is to drive community and hands-on learning opportunities with social activities and skill development workshops. This fall, student leaders worked to recreate those events in a virtual environment – requiring creativity and determination to combat the fatigue associated with long periods on telecommunication platforms.

COVID calls for creative solutions

Carolina Data Challenge held its fourth annual 24-hour datathon on October 5-6. Participants worked on a dataset from either the financial, technology, or non-profit sector, and prizes were awarded to the teams who provide the best data visualization, most valuable insights, and best use of outside data, as well as to the top beginner team.

HackNC, North Carolina’s largest hackathon, was held on October 16-18. For its seventh annual event, HackNC organized its projects into four tracks: accessibility and inclusivity, education, healthcare, and sustainability, with an additional non-profit challenge.

The past seven months have demonstrated how teams can adapt to online work. The collaboration tools we use daily were creatively incorporated into both hackathons. For workshops, the team at HackNC coordinated a live stream via multiple video conferencing software on Twitch, allowing students to access content both synchronously and asynchronously on HackNC’s YouTube channel.

To foster community, Carolina Data Challenge created social events around the clock and launched a meme sharing competition, all accessible in real time via Discord.

While the department’s in-person hackathons typically draw participants from the East Coast and the southeast, the virtual editions of Carolina Data Challenge and HackNC saw participants from all over the United States and even other countries.

Project submissions reflect current times

The two hackathons brought together more than 1,300 students and mentors, with more than 100 unique projects submitted.

Projects drew inspiration from our current environment, including submissions from COVID tracking to self-care apps. Carolina Data Challenge awarded winners based each submission category: finance, health & sciences, humanities, and pop culture. Winners were also selected for best data visualization and use of visual data tools. LoganNehaLucySilas, winner of the health & sciences category, observed the relationship between the August Complex Fires, a group of 38 fires in California, and the levels of particulate matter < 2.5 in the San Fransisco area. The team demonstrated a relationship between the August Complex Fires and increased particulate matter < 2.5 levels, as well as increased levels of carbon monoxide and black carbon, in the area from August 21-23 as the fires spread. The team developed a variety of data visualizations based on different hypotheses, examining the connection between wind direction, sensor proximity to the fires, and the peak readings for particulate mater < 2.5 levels.

Drizzle, the first place hack at HackNC, produced a customized lo-fi hip-hop music creator that worked by combining a library of instrumental samples and machine learning algorithms. Lo-fi hip-hop music has become popular background music for studying, and the program creates a sample and customizes it further by using location data to match current time and weather forecasts to project corresponding images with the music. For optimal study conditions, the development team also added automatic reminders for users to look away from the screen every 20 minutes and to look 20 feet away for 20 seconds, implementing the 20/20/20 rule designed to reduce eye strain.

To redirect funding typically spent on a venue and food, HackNC supported donations to the winning hackers’ charity of choice. In total, $10,000 was raised and split among a variety of non-profits serving underserved and marginalized communities.

To see all projects, check out the Carolina Data Challenge site and HackNC DevPost page.

In addition to the support from the UNC Department of Computer Science, Carolina Data Challenge and HackNC were made possible by the following sponsors: CapTech, EY, NCSU’s Institute for Advanced Analytics, Metlife, NCDS, RENCI, SAS, Visual Data Tools, Credit Suisse, Capital One, Genesys, John Deere, Postman, Square, IQVIA, Optum, CoStar, Lionode, Millennium Advisors, Vanguard, and Deutsche Bank.

Looking forward to more virtual hackathons

With the findings and best practices from these events, student leaders are collaborating on more upcoming virtual hackathons. December 2020 will bring the inaugural queer_hack, a hackathon serving LGBTQ+ community, and Pearl Hacks, one of the nation’s longest-running hackathons for women and non-binary students, will return for its eighth event in February 2021.

Open Course: Extending COMP 110 beyond Carolina

October 30, 2020

Each year, over 1,000 students in COMP 110: Introduction to Programming are introduced to computer science by Teaching Professor and UNC CS alumnus Kris Jordan and his team of 45 enthusiastic Undergraduate Teaching Assistants (UTAs). Jordan and his dedicated UTA team have driven COMP 110 to become one of the most popular courses at UNC.

With the move to remote learning, Jordan quickly pivoted coursework to allow for streaming of all lectures, as well as make them freely and publicly available. Now, anyone wishing for a primer on introductory programming can access pre-recorded lessons, slides, and hands-on lab tutorials by subscribing to Jordan’s YouTube channel.

“As a student in western North Carolina, I did not have access to any programming courses at my high school. The same is true for many of my LAs who help me run the course. My hope with offering these learning experiences more broadly to the state of North Carolina is that it might spark an early interest,” stated Jordan.

Increased access to programming curriculum has been a long-time goal for Jordan.

“A small silver lining in the move to remote learning due to the COVID-19 pandemic,” Jordan said, “is that it provided the impetus to make this happen.”

Guided by strategies to support increased access and opportunity in computer science, Jordan is committed to finding ways for all interested students to find their place in tech. In this truncated fall semester alone, visitors to Jordan’s YouTube channel have spent more than 10,000 hours viewing his instructional videos. For more information about the course and to access the online materials, check out Jordan’s dedicated COMP 110 site.

Islam, Embedded Intelligence Lab develop for a future with fewer batteries

October 29, 2020
Members of the Embedded Intelligence Lab work in Sitterson Hall (Jon Gardiner/UNC-Chapel Hill)

Continuous health monitoring is the future of healthcare, and wearable technology is helping to lead the charge by collecting useful baseline data between check-ups and detecting changes that are early signs of illness. Wearable devices can even help detect signs that would be missed in traditional health screenings.

Similarly, the Internet of Things (IoT) has enabled us to increase efficiency and monitor the world using always-on devices in our homes, our places of work, and even in remote areas of the world. We use IoT devices to detect pollutants in our air and water, lower our energy consumption in buildings, and act as personal assistants.

Unfortunately, the current trend in embedded and wearable systems is unsustainable. Nearly a decade ago, tech experts predicted that the world would reach 1 trillion connected devices in the coming years. If each of those trillion devices has a battery that lasts 10 years, we would need to replace nearly 274 million batteries every day.

Lithium-ion batteries are used in portable electronic devices, electric vehicles, and even in aerospace applications due to their high energy density and long discharge cycles. Only a small percentage of these batteries are recycled correctly, however, and most of the metals and other valuable materials that can be harvested from used batteries end up in landfills. It is estimated that the world will produce 2 million metric tons of used lithium batteries per year by 2030, and most of that waste will likely not be recycled. Furthermore, experts predict an impending shortage of lithium by the mid-2020s, so alternative materials and methods for storing energy and powering devices will be necessary. And those alternatives will be needed soon.

One obvious solution to the problem of batteries is to build devices without them, but the concept is much simpler than the implementation. The Embedded Intelligence (EI) Lab in the Department of Computer Science designs and programs batteryless systems that are optimized for low-power operation. These devices can power themselves by harvesting energy from changes in light or temperature, from vibrations, and even from radio-frequency (RF) microwaves. The issue with these systems, though, is that power can be sporadic. A solar powered device, for example, must be able to operate as intended through long, daily periods of darkness as well as less predictable intermittent periods of cloud cover. Lower power in a device means that processing takes longer. More compute-intensive tasks have to wait to run until sufficient power can be harvested. During periods where energy is scarce, tasks may not be able to run at all.

Undaunted by these limitations, doctoral student Bashima Islam and her advisor and EI Lab director Shahriar Nirjon have developed task scheduling frameworks to enable tasks to be run effectively on batteryless systems. Additionally, these frameworks have been optimized in order to operate within defined time constraints, making their implementation consistent and predictable.

Bashima Islam
Bashima Islam

The first scheduling algorithm, Celebi, balances the trade-off between mutually exclusive cycles of power charging and computation in batteryless systems. Because these systems are unable to charge while executing computational tasks, the time needed to complete a job is a function of both the time needed to compute each task and the time needed to harvest enough energy to power the device through the computations. Harvesting more energy than is necessary adds to the runtime. Celebi focuses on both sets of constraints to maximize efficiency by determining exactly how much energy is necessary for each task and optimizing the schedule to accommodate as many tasks as possible in a given time frame. In testing, the online version of Celebi was able to schedule between 8 and 22 percent more jobs than existing algorithms.

The second scheduling algorithm, Zygarde, focuses on the computational demand of deep neural networks (DNNs) on a microcontroller in an embedded system. Monitoring systems like security cameras, toxin detectors, and voice assistant devices are an ideal implementation of batteryless systems. Unfortunately, running video and audio recognition tasks requires a relatively large amount of energy on these devices, and getting meaningful results with unpredictable energy availability can be complicated. When given a deep learning job to execute, Zygarde simplifies the job by determining the minimum set of tasks that need to run in order to make an accurate inference. Zygarde prioritizes those tasks to ensure that the mandatory tasks will finish on time in the event of an energy shortage. After prioritizing the mandatory tasks, the optional tasks are executed to improve the accuracy of the inference as time allows. Sacrificing a small amount of processing time and accuracy can make a large difference in the runtime of a machine learning task through intermittent power.

Bashima is excited about the range of applications for her work. IBM’s project Rhino, for example, monitors a herd of impalas as an early warning for rhino poachers. Motion detectors on the impalas could be powered by kinetic energy as the animals move, and Celebi would ensure that energy harvest is sufficient to keep the sensors active. Zygarde would optimize the systems to notify the rangers as quickly as possible to a poacher threat with minimal trade-off in accuracy. The frameworks could also be useful in continuous monitoring of industrial machinery and HVAC systems, enabling preventive maintenance that minimizes unplanned downtime and costly repairs. There are numerous other applications, including methane gas monitoring in underground mines and temperature and humidity monitoring in warehouses.

The pioneering work of the EI Lab will hopefully reduce our reliance on batteries in embedded and wearable sensor systems. In addition to task scheduling research, the group has projects related to low power communication, sustainable energy harvesting, low power recognition optimization, in-home assistive healthcare, and more.

Islam’s research prompted her selection to UC Berkeley’s Rising Stars Workshop 2020, a highly selective academic career workshop for women in computer science, computer engineering, and electrical engineering. In recognition of her work, Islam was named a finalist for the Gaetano Borriello Outstanding Student Award at the ACM International Joint Conference on Pervasive and Ubiquitous Computing and International Symposium on Wearable Computers (UbiComp/ISWC) 2020. More information about Islam’s research can be found at cs.unc.edu/~bashima/research.