School of Computational Science and Engineering

Campus Connection Inspires Mother and Son to Find Purpose and Passion

admin — Fri, 09 May 2025 14:00:41 +0000

Campus Connection Inspires Mother and Son to Find Purpose and Passion admin Fri, 05/09/2025 - 10:00

When Andrew Rush started at Georgia Tech last fall, he already had a sense of direction as soon as he set foot on campus. His mother, Holly Rush, is a longtime Georgia Tech staff employee, and this exposure influenced Andrew to study at the Institute.

We caught up with Holly and Andrew to learn more about what makes Georgia Tech so appealing to students and employees alike, and the unique perspective their mother-son relationship brings to campus.

How long have you worked at Georgia Tech? What do you do as a financial operations assistant director?

[Holly] I have been at Georgia Tech since 2000 and joined the College of Computing in early 2005. Ironically and very memorably, I found out I was expecting Andrew right after I started in Computing. I still recall being very nervous about telling my new boss that I was expecting, but she was happy for me and very accommodating. I went to the bookstore right after our meeting and bought Andrew his first Georgia Tech t-shirt, which I plan to pass down to him one day.

Being part of the College for this long, I have watched it grow from having divisions to schools. I began as a financial administrator and steadily grew into my current role as assistant director of financial operations for the School of Computational Science and Engineering (CSE). In my current role, I oversee financial operations for the School of CSE, including budgeting, forecasting, financial reporting, and ensuring compliance with Institute and sponsor guidelines. I work closely with faculty, staff, and leadership to support our financial programs and other initiatives. It is a rewarding role that allows me to contribute to the success of the college while watching it grow, just like my own journey here.

How much influence did your mom’s work at Georgia Tech have on your interest in coming here for college?

[Andrew] It definitely played a role. I grew up a fan of all things Georgia Tech, so this was always my dream school. When I got in, all the stars aligned. Tech was my dream school, my mom worked there, and I was close to home. It was perfect.

What is it about Georgia Tech that has kept you here for more than two decades?

[Holly] From the beginning, I have always felt that my work contributes to something bigger – supporting faculty who offer world-class education and innovation. I have had the opportunity to grow professionally and work alongside very talented colleagues.

How has your first year gone? What do you like best about attending Georgia Tech?

[Andrew] Overwhelming. I wasn’t sure what to expect from attending college. The college lifestyle was a big change for me, and I had to learn how to navigate it. I knew Georgia Tech would be challenging, and I thought I was ready for it, but it was still harder than I expected. However, I managed to get through my first year with great resilience and finish stronger than I started.

What do you each like best about being on campus together?

[Holly] I enjoy being nearby and getting to share this chapter of his life. There are many times that Andrew is focused on his studies or his fraternity commitments, so he doesn’t get to come home as often as I would like. But with me being on campus, we can grab a quick lunch or have a short visit. I also like knowing he is a short walk from my office if I want to drop off a homemade meal. Even when we are both too busy for a visit, sometimes I find myself looking out the window across campus. Just seeing the top of a building where he is attending class gives me comfort knowing he is there.

[Andrew] Bouncing off of what my mom said, it has been great. It is comforting that I can go to her office just to say “hey,” and not drive all the way home. It’s nice that when I’m having a rough patch with school, she drops by to offer some reassurance.

What has been the key to reaching the milestones of a fulfilling career and witnessing your children achieve their goals?

[Holly] The key to reaching these milestones has really been maintaining a healthy work-life balance. Georgia Tech has given me the space and support to grow professionally while also being present as a parent. That balance has been everything. It allowed me to build a fulfilling career that I’m proud of, while also being there to watch my children grow and pursue their dreams, including Andrew becoming a Georgia Tech student himself. Being able to do both, without having to choose one over the other, has truly been the foundation of my success and happiness.

What do you look forward to in the next few years studying computer engineering at Georgia Tech? And after graduating?

[Andrew] I am most excited for my threads and starting my career. I have learned so much that I am already applying my studies. I recently used Raspberry Pi to build a circuit that enabled a motion detector to work and set off an LED indicating motion. This was a part of my discovery class for my major, and it was the most fun I have had at Georgia Tech so far. It was very new and exciting to learn about, and it motivates me to put my skills to work.

After graduating, I want to work in cybersecurity, possibly as a hardware security engineer for the government or even my own startup. The project I mentioned opened my eyes to my threads and really motivated me to continue in this field.

Rush is one of more than 150 College of Computing staff members who support the College and its five schools. Staff members are the backbone of the College. From managing operations to providing essential services, their dedication ensures the seamless delivery of education, research, and community support, making them integral to the College's success.

Summary sentence

Holly Rush has worked at Georgia Tech since 2000. Her employment influenced her son, Andrew, to attend the Institute and study computer engineering.

Summary

We caught up with Holly and Andrew to learn more about what makes Georgia Tech so appealing to students and employees alike, and the unique perspective their mother-son relationship brings to campus.

Dateline

Thu, 05/08/2025 - 12:00

Contact

Bryant Wine, Communications Officer
bryant.wine@cc.gatech.edu

Keywords

College of Computing

college of engineering

School of Computational Science and Engineering

College of Engineering; School of Electrical and Computer Engineering

Daily Digest

The Whistle

whistle

Georgia Tech News Center

Mother's Day

News room topics

Campus and Community

Categories

Community

Computer Science/Information Technology and Security

Engineering

Student and Faculty

Mercury ID

682285

Source updated

Fri, 05/09/2025 - 09:59

Computing Framework Could Reveal Signs of Neuro Disorders Hidden within Brain Data

admin — Mon, 05 May 2025 13:58:41 +0000

Computing Framework Could Reveal Signs of Neuro Disorders Hidden within Brain Data admin Mon, 05/05/2025 - 09:58

A Georgia Tech doctoral student’s dissertation could help physicians diagnose neuropsychiatric disorders, including schizophrenia, autism, and Alzheimer’s disease. The new approach leverages data science and algorithms instead of relying on traditional methods like cognitive tests and image scans.

Ph.D. candidate Md Abdur Rahaman’s dissertation studies brain data to understand how changes in brain activity shape behavior.

Computational tools Rahaman developed for his dissertation look for informative patterns between the brain and behavior. Successful tests of his algorithms show promise to help doctors diagnose mental health disorders and design individualized treatment plans for patients.

“I've always been fascinated by the human brain and how it defines who we are,” Rahaman said.

“The fact that so many people silently suffer from neuropsychiatric disorders, while our understanding of the brain remains limited, inspired me to develop tools that bring greater clarity to this complexity and offer hope through more compassionate, data-driven care.”

Rahaman’s dissertation introduces a framework focusing on granular factoring. This computing technique stratifies brain data into smaller, localized subgroups, making it easier for computers and researchers to study data and find meaningful patterns.

Granular factoring overcomes the challenges of size and heterogeneity in neurological data science. Brain data is obtained from neuroimaging, genomics, behavioral datasets, and other sources. The large size of each source makes it a challenge to study them individually, let alone analyze them simultaneously, to find hidden inferences.

Rahaman’s research allows researchers and physicians to move past one-size-fits-all approaches. Instead of manually reviewing tests and scans, algorithms look for patterns and biomarkers in the subgroups that otherwise go undetected, especially ones that indicate neuropsychiatric disorders.

“My dissertation advances the frontiers of computational neuroscience by introducing scalable and interpretable models that navigate brain heterogeneity to reveal how neural dynamics shape behavior,” Rahaman said.

“By uncovering subgroup-specific patterns, this work opens new directions for understanding brain function and enables more precise, personalized approaches to mental health care.”

Rahaman defended his dissertation on April 14, the final step in completing his Ph.D. in computational science and engineering. He will graduate on May 1 at Georgia Tech’s Ph.D. Commencement.

After walking across the stage at McCamish Pavilion, Rahaman’s next step in his career is to go to Amazon, where he will work in the generative artificial intelligence (AI) field.

Graduating from Georgia Tech is the summit of an educational trek spanning over a decade. Rahaman hails from Bangladesh where he graduated from Chittagong University of Engineering and Technology in 2013. He attained his master’s from the University of New Mexico in 2019 before starting at Georgia Tech.

“Munna is an amazingly creative researcher,” said Vince Calhoun, Rahman’s advisor. Calhoun is the founding director of the Translational Research in Neuroimaging and Data Science Center (TReNDS).

TReNDS is a tri-institutional center spanning Georgia Tech, Georgia State University, and Emory University that develops analytic approaches and neuroinformatic tools. The center aims to translate the approaches into biomarkers that address areas of brain health and disease.

“His work is moving the needle in our ability to leverage multiple sources of complex biological data to improve understanding of neuropsychiatric disorders that have a huge impact on an individual’s livelihood,” said Calhoun.

Summary sentence

A Georgia Tech doctoral student’s dissertation could help physicians diagnose neuropsychiatric disorders, including schizophrenia, autism, and Alzheimer’s disease.

Summary

Ph.D. candidate Md Abdur Rahaman’s dissertation studies brain data to understand how changes in brain activity shape behavior.

Dateline

Thu, 04/24/2025 - 12:00

Contact

Bryant Wine, Communications Officer
bryant.wine@cc.gatech.edu

Keywords

College of Computing

School of Computational Science and Engineering

Research Horizons

go-researchnews

artificial intelligence (AI)

go-ai

Daily Digest

Georgia Tech News Center

News room topics

Health and Medicine

Categories

Biotechnology, Health, Bioengineering, Genetics

Computer Science/Information Technology and Security

Life Sciences and Biology

Research

Student Research

Mercury ID

682026

Source updated

Mon, 05/05/2025 - 09:58

Faculty Earn Fellowships for Heart Modeling and Data Optimization Research

admin — Fri, 25 Apr 2025 14:42:41 +0000

Faculty Earn Fellowships for Heart Modeling and Data Optimization Research admin Fri, 04/25/2025 - 10:42

Two faculty members represented Georgia Tech as new fellows to the world’s leading organization dedicated to applied mathematics, computational science, and data science.

The Society for Industrial and Applied Mathematics (SIAM) selected Elizabeth Cherry and Katya Scheinberg as Class of 2025 fellows. The two Georgia Tech faculty join an illustrious class of 23 other researchers from around the globe in this year’s class.

SIAM selected Cherry to recognize her contributions to mathematical and computational modeling and extensive service to the SIAM community. She studies the electrical behavior of cardiac cells and tissue.

Cherry’s computer models and simulations improve understanding of cardiac dynamics in normal and diseased states. Using these tools, she designs advanced strategies for preventing and treating arrhythmias.

“SIAM has played a huge role in my professional development—the first conference I attended as a graduate student was a SIAM conference, and I’ve attended at least one SIAM conference almost every year since then,” Cherry said.

“Given this long history, it means a lot to me for SIAM to acknowledge my contributions in this way.”

Scheinberg, from Georgia Tech’s College of Engineering, was selected for her foundational contributions to derivative-free optimization and optimization applications in data science and her dedicated service to the optimization community.

Cherry is the fifth faculty member from the School of Computational Science and Engineering (CSE) to be selected as a SIAM Fellow.

Cherry’s announcement as a SIAM Fellow comes weeks after serving in a leadership role at a SIAM conference. She co-chaired the organizing committee of the SIAM Conference on Computational Science and Engineering (CSE25).

In 2023, SIAM members reelected Cherry to a second term as a council member-at-large. She began her three-year term in January 2024.

"SIAM Fellows are selected for deep mathematical contributions. Receiving Fellow status is a high honor for any applied mathematician," said Regents’ Professor Srinivas Aluru, senior associate dean of the College of Computing and Class of 2020 SIAM Fellow.

"Not only are Elizabeth's contributions technically outstanding, but her work also provides deep insights into the functioning of the heart and its abnormalities."

Cherry’s leadership and service extends outside of SIAM, influencing students and faculty across Georgia Tech.

In December, the College of Computing appointed Cherry as associate dean for graduate education. Before this appointment, she served as associate chair for academic affairs of the School of CSE.

With her new role as associate dean, Cherry continues serving as director of CSE programs at Georgia Tech.

In March 2024, Cherry was among five Georgia Tech faculty members selected for the ACC Academic Leaders Network (ACC ALN) Fellows program. The ALN program fosters cross-institutional networking and collaboration between ACC schools, increasing each institution’s academic leadership capacity.

Cherry was part of a team of Georgia Tech and Emory University researchers who won a Georgia Clinical and Translational Science Alliance award in 2023. The group earned the Team Science Award of Distinction for Early Stage Research Teams award for work that captures high-resolution visualizations of spiral waves that create heart arrhythmias.

SIAM will recognize Cherry, Scheinberg, and Class of 2025 fellows during a reception at the SIAM/CAIMS Annual Meetings this July in Montréal.

“It is such an honor to be recognized as a SIAM Fellow,” Cherry said. “I’m thrilled to join my CSE colleagues who have also received this recognition.”

Subtitle

Summary sentence

The Society for Industrial and Applied Mathematics (SIAM) selected Elizabeth Cherry and Katya Scheinberg as Class of 2025 fellows.

Summary

Two faculty members represented Georgia Tech as new fellows to the world’s leading organization dedicated to applied mathematics, computational science, and data science.

Dateline

Fri, 04/11/2025 - 12:00

Contact

Bryant Wine, Communications Officer
bryant.wine@cc.gatech.edu

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Keywords

College of Computing

School of Computational Science and Engineering

go-researchnews

Research Horizons

Daily Digest

Georgia Tech News Center

SIAM

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Science and Technology

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Biotechnology, Health, Bioengineering, Genetics

Computer Science/Information Technology and Security

Life Sciences and Biology

Student and Faculty

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681734

Source updated

Fri, 04/25/2025 - 10:41

School Award Winners Impress on World, National, and Institute Stages

dgivens8 — Fri, 25 Apr 2025 14:11:55 +0000

School Award Winners Impress on World, National, and Institute Stages dgivens8 Fri, 04/25/2025 - 10:11

The dictionary is the only place where success comes before work. The College of Computing’s 34th Annual Awards Celebration on April 8 offered a venue to honor the hard work and ensuing success of students, faculty, staff, and alumni in 2024-2025.

“In this past year, my first as the dean of computing, I have seen exactly how much work it takes from everyone to keep this community going, not to mention excelling,” said Vivek Sarkar, dean and John P. Imlay Jr. Chair of the College of Computing.

“We are strong across the board, and that makes our winners all the more impressive.”

The School of Computational Science and Engineering (CSE) is one unit that reinforces the College’s emphasis on collaboration, problem solving, and excellence. By earning awards this year at the College, Institute, and levels beyond, the School of CSE continues to distinguish itself as a top-tier department for research and learning.

Select award winners from the School of CSE recognized at this year’s banquet were:

Professor Polo Chau- Dean’s Award
Pratham Mehta, M.S. CS student- The Donald V. Jackson Fellowship
Parisa Babolhavaeji- The Marshall D. Williamson Fellowship
Aeree Cho, Ph.D. student- Rising Star Doctoral Student Research Award
Alumnus Zijie (Jay) Wang (Ph.D. ML-CSE 2024)- Outstanding Doctoral Dissertation Award

The College of Computing also recognized awardees with ties to the School of CSE. These included:

Lecturer and alumnus Max Roozbahani (Ph.D. CSE 2019)- William A. "gus" Baird Faculty Teaching Award. Instructor of the online section of CSE6242: Data and Visual Analytics.
Lecturer and alumnus Nimisha Roy (Ph.D. CSE 2021)- William D. "Bill" Leahy Jr. Outstanding Instructor Award
Teaching Assistant Susanta Routray- Outstanding Instructional Associate Teaching Award. Co-head TA of the online section of CSE6242: Data and Visual Analytics.

Chau teaches the CSE6242 course, and advises Babolhavaeji, Cho, Mehta, and Wang. Along with the College of Computing awards, Chau received the Innovator’s Award at the M.S. Analytics Ten Year Anniversary. He has served as the program’s associate director since 2014 and over 1,000 students have taken his data and visual analytics course each semester in recent years.

Along with receiving the College of Computing’s dissertation, Wang received a 2025 Outstanding Dissertation Award from the Association for Computing Machinery Special Interest Group on Computer-Human Interaction (ACM SIGCHI).

SIGCHI is the world’s largest association of human-computer interaction professionals and practitioners. Wang is one of five recipients of the award this year.

Earlier in the year, Forbes recognized Wang by naming him to its 30 Under 30 in Science for 2025.

Wang’s dissertation earned him the 2025 Best Ph.D. Thesis Award from the Georgia Tech Sigma Chi chapter.

At the same ceremony, Sigma Chi presented Regents’ Professor Mark Borodovsky with the Best Faculty Paper Award for his work on GeneMark-ETP. Borodovsky holds joint appointments with the School of CSE and the Wallace H. Coulter Department of Biomedical Engineering.

Trailblazing work in biocomputing earned Regents’ Professor Srinivas Aluru the 2025 Charles Babbage Award. The Institute of Electrical and Electronics Engineers Computer Society (IEEE CS) presented the award for Aluru’s pioneering contributions intersecting parallel computing and computational biology.

News of Aluru’s Babbage Award arrived at the same time the College of Computing announced the appointments of associate deans. The College appointed Aluru as senior associate dean, and Associate Professor Elizabeth Cherry became associate dean for graduate education.

Aluru and Cherry’s appointments marked the first time in the School’s history that faculty represented the School as associate deans.

Aluru ended his role as executive director of Georgia Tech’s Institute for Data Engineering and Science (IDEaS) when he accepted the senior associate dean role. In his place, IDEaS appointed Regents’ Professor C. David Sherrill as interim executive director.

Sherrill holds joint appointments with CSE and the School of Chemistry and Biochemistry. He has served as associate director of IDEaS since its founding in 2016. His appointment as interim executive director comes after his election to the International Academy of Quantum Molecular Science (IAQMS).

Cherry's appointment as associate dean was one of many accolades she received in 2025. In March, the Society for Industrial and Applied Mathematics (SIAM) selected her as a Class of 2025 Fellow, recognizing her contributions to computational cardiology research and extensive service to the SIAM community. Cherry is the fifth faculty member from the School of CSE selected as a SIAM Fellow.

Cherry co-chaired the organizing committee for the SIAM Conference on Computational Science and Engineering (CSE25). She is also serving a second consecutive term as a SIAM council member-at-large.

Members of the SIAM Activity Group on Computational Science and Engineering (SIAG/CSE) elected School of CSE Professor and Associate Chair Edmond Chow as vice chair. Chow’s two-year term began in January after serving as the group’s program director.

Cherry previously served as the School of CSE’s associate chair for academic affairs. When she accepted her new associate dean role, the School appointed B. Aditya Prakash as associate chair.

Prakash was one of three School of CSE faculty members who received promotions that take effect in July. He was promoted to full professor. Assistant Professors Chao Zhang and Xiuwei Zhang earned tenure and promotions. Each has been promoted to associate professor.

Prakash advised Alexander Rodríguez (Ph.D. CS 2023), now an assistant professor at the University of Michigan. Rodríguez won an outstanding dissertation award runner-up at the International Conference on Knowledge Discovery and Data Mining (KDD 2024).

Rodríguez’s dissertation on Artificial Intelligence for Data-centric Surveillance and Forecasting of Epidemics earned him the College of Computing's Outstanding Dissertation Award in 2024.

Assistant Professor Florian Schäfer co-authored a paper selected for one of five best technical paper awards at the annual conference for ACM’s Special Interest Group on Computer Graphics and Interactive Techniques (SIGGRAPH 24).

Schäfer’s work in numerical computation and statistical inference led to his appointment as an initiative lead within Georgia Tech’s Institute for Matter and Systems (IMS). IMS selected Schäfer to lead the initiative on Matter and Information, looking to him to facilitate innovative approaches and impact in alignment with IMS’ mission.

Assistant Professor Spencer Bryngelson and his group received an ACCESS-CI Maximize allocation from the National Science Foundation. The award amounts to 225,000 GPU hours annually to run their multiphase fluid flow simulation algorithms on powerful supercomputers.

One of Bryngelson’s Ph.D. students, Ben Wilfong, received the 2024-2025 CRNCH Fellowship. Wilfong will use the fellowship to optimize superchip architectures, such as NVIDIA Grace Hopper and AMD MI300A.

Early in the year, Suzan Manasreh and Elizabeth Hong won President’s Undergraduate Research Awards (PURA) for Fall 2024. Manasreh studies in Bryngelson’s group, and Professor Rich Vuduc advises Hong.

M.S. CSE student Grace Driskill attained achievement in the classroom, on the track, and cross country courses. The first-ever School of CSE student-athlete earned a third selection to an All-ACC academic team.

Driskill made history by recording the fourth fastest 3000-meter time in history of the Georgia Tech Women’s Indoor Track program. She clocked a 9:22.21 on Feb. 15 at Boston University’s David Hemery Valentine Invitational.

Students praised Assistant Professor Raphaël Pestourie, who was selected for the Fall 2024 CIOS Honor Roll. The honor roll recognized Pestourie for outstanding teaching and educational impact through his CSE 8803: Scientific Machine Learning course.

In the waning weeks of the semester, CSE-AE Ph.D. student Atticus Rex received the NSF Graduate Research Fellowship Program (GRFP) award for computational and data-enabled science research. Rex is advised by Assistant Professor Elizabeth Qian, who holds joint appointments with the School of CSE and the Daniel Guggenheim School of Aerospace Engineering.

In March, the American Institute of Mining, Metallurgical and Petroleum Engineers (AIME) awarded honorary membership to Regents’ Professor Surya Kalidindi. Kalidindi is affiliated with the School of CSE, the George W. Woodruff School of Mechanical Engineering, and the School of Materials Science and Engineering.

Summary sentence

By earning awards this year at the College, Institute, and levels beyond, the School of Computational Science and Engineering (CSE) continues to distinguish itself as a top-tier department for research and learning.

Summary

“We are strong across the board, and that makes our winners all the more impressive.”

Dateline

Fri, 04/25/2025 - 12:00

Contact

Bryant Wine, Communications Officer
bryant.wine@cc.gatech.edu

Keywords

College of Computing

School of Computational Science and Engineering

Categories

Student and Faculty

Student Competition WInners (academic, innovation, and research)

Student Honors and Achievements

Mercury ID

682027

Source updated

Fri, 04/25/2025 - 10:11

Thesis on Human-Centered AI Earns Honors from International Computing Organization

dgivens8 — Tue, 22 Apr 2025 14:30:41 +0000

Thesis on Human-Centered AI Earns Honors from International Computing Organization dgivens8 Tue, 04/22/2025 - 10:30

A Georgia Tech alum’s dissertation introduced ways to make artificial intelligence (AI) more accessible, interpretable, and accountable. Although it’s been a year since his doctoral defense, Zijie (Jay) Wang’s (Ph.D. ML-CSE 2024) work continues to resonate with researchers.

Wang is a recipient of the 2025 Outstanding Dissertation Award from the Association for Computing Machinery Special Interest Group on Computer-Human Interaction (ACM SIGCHI). The award recognizes Wang for his lifelong work on democratizing human-centered AI.

“Throughout my Ph.D. and industry internships, I observed a gap in existing research: there is a strong need for practical tools for applying human-centered approaches when designing AI systems,” said Wang, now a safety researcher at OpenAI.

“My work not only helps people understand AI and guide its behavior but also provides user-friendly tools that fit into existing workflows.”

Wang’s dissertation presented techniques in visual explanation and interactive guidance to align AI models with user knowledge and values. The work culminated from years of research, fellowship support, and internships.

Wang’s most influential projects formed the core of his dissertation. These included:

CNN Explainer: an open-source tool developed for deep-learning beginners. Since its release in July 2020, more than 436,000 global visitors have used the tool.
DiffusionDB: a first-of-its-kind large-scale dataset that lays a foundation to help people better understand generative AI. This work could lead to new research in detecting deepfakes and designing human-AI interaction tools to help people more easily use these models.
GAM Changer: an interface that empowers users in healthcare, finance, or other domains to edit ML models to include knowledge and values specific to their domain, which improves reliability.
GAM Coach: an interactive ML tool that could help people who have been rejected for a loan by automatically letting an applicant know what is needed for them to receive loan approval.
Farsight: a tool that alerts developers when they write prompts in large language models that could be harmful and misused.

“I feel extremely honored and lucky to receive this award, and I am deeply grateful to many who have supported me along the way, including Polo, mentors, collaborators, and friends,” said Wang, who was advised by School of Computational Science and Engineering (CSE) Professor Polo Chau.

“This recognition also inspired me to continue striving to design and develop easy-to-use tools that help everyone to easily interact with AI systems.”

Like Wang, Chau advised Georgia Tech alumnus Fred Hohman (Ph.D. CSE 2020). Hohman won the ACM SIGCHI Outstanding Dissertation Award in 2022.

Chau’s group synthesizes machine learning (ML) and visualization techniques into scalable, interactive, and trustworthy tools. These tools increase understanding and interaction with large-scale data and ML models.

Chau is the associate director of corporate relations for the Machine Learning Center at Georgia Tech. Wang called the School of CSE his home unit while a student in the ML program under Chau.

Wang is one of five recipients of this year’s award to be presented at the 2025 Conference on Human Factors in Computing Systems (CHI 2025). The conference occurs April 25-May 1 in Yokohama, Japan.

SIGCHI is the world’s largest association of human-computer interaction professionals and practitioners. The group sponsors or co-sponsors 26 conferences, including CHI.

Wang’s outstanding dissertation award is the latest recognition of a career decorated with achievement.

Months after graduating from Georgia Tech, Forbes named Wang to its 30 Under 30 in Science for 2025 for his dissertation. Wang was one of 15 Yellow Jackets included in nine different 30 Under 30 lists and the only Georgia Tech-affiliated individual on the 30 Under 30 in Science list.

While a Georgia Tech student, Wang earned recognition from big names in business and technology. He received the Apple Scholars in AI/ML Ph.D. Fellowship in 2023 and was in the 2022 cohort of the J.P. Morgan AI Ph.D. Fellowships Program.

Along with the CHI award, Wang’s dissertation earned him awards this year at banquets across campus. The Georgia Tech chapter of Sigma Xi presented Wang with the Best Ph.D. Thesis Award. He also received the College of Computing’s Outstanding Dissertation Award.

“Georgia Tech attracts many great minds, and I’m glad that some, like Jay, chose to join our group,” Chau said. “It has been a joy to work alongside them and witness the many wonderful things they have accomplished, and with many more to come in their careers.”

Summary sentence

Zijie (Jay) Wang (Ph.D. ML-CSE 2024) is a recipient of the 2025 Outstanding Dissertation Award from the Association for Computing Machinery Special Interest Group on Computer-Human Interaction (ACM SIGCHI).

Summary

Dateline

Thu, 04/17/2025 - 12:00

Contact

Bryant Wine, Communications Officer
bryant.wine@cc.gatech.edu

Keywords

College of Computing

School of Computational Science and Engineering

artificial intelligence (AI)

Georgia Tech News Center

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Source updated

Tue, 04/22/2025 - 10:29

Meet CSE Profile: Grace Driskill

dgivens8 — Mon, 31 Mar 2025 13:29:41 +0000

Meet CSE Profile: Grace Driskill dgivens8 Mon, 03/31/2025 - 09:29

Grace Driskill made Georgia Tech history when she arrived on campus in 2023. She is the first student-athlete to study computational science and engineering (CSE). While this is a notable benchmark, Driskill’s achievements on the track and in the classroom defined her career at Georgia Tech.

As a competitive runner, Driskill holds the fourth-fastest 3000-meter time in the history of Georgia Tech’s women's indoor track program. Off the track, Driskill is a three-time All-ACC Academic team honoree on the women’s cross-country and track teams, and in 2024, she received the College of Computing’s Donald V. Jackson Fellowship.

We caught up with Driskill to learn more about her and how she balances academic and athletic responsibilities.

Student: Grace Driskill

Current Degree Program: M.S. in Computational Science and Engineering

Research Interests: Computational biology, computing applications toward health

Hometown: Tucson, Arizona

Where are you from, and how did you get to Georgia Tech?

I grew up in Tucson, Arizona. I attended the University of Arizona, earning a bachelor’s degree in computer science while running on the track and field team. When I finished my undergraduate, I still had two seasons of eligibility to run track. I looked into master’s programs so that I could continue my athletic career and expand my horizons academically.

The cards fell into place for me to come here. Georgia Tech has a great reputation as a school for computing and engineering. Additionally, the cross country and women’s track coach, Alan Drosky, is very experienced and knowledgeable in coaching distance runners.

You are the first ever student-athlete in the School of CSE’s history. What does this mean to you? What does it mean for the CSE program?

I didn’t realize I was the first student-athlete in the School of CSE, but I think it’s pretty cool. It is meaningful to me, and hopefully, others, because it goes against the thought that you need to fit into some typical mold to be a student-athlete or to study CSE.

CSE is a challenging degree for any student, let alone a student-athlete. What interested you about the program in the first place?

I think the CSE program at Georgia Tech is unique; not many colleges in the U.S. offer a master’s degree in the topic. I like the interdisciplinary nature of it. I enjoyed studying computer science during my undergraduate, but I thought leaning more into computing applications was an interesting opportunity.

Could you describe an average day for you as a CSE student-athlete?

After eating some breakfast and having a coffee, the first thing I typically do is go for an easy run that might be 3-8 miles. Then, I go to class or do homework for a few hours, making sure to take a break for lunch.

At 3:30 p.m., I have practice with the team. This typically includes a higher-intensity run and exercises to practice form or help with strength and mobility. After practice, I usually stretch and take an ice bath for recovery. I typically get home around 6-6:30. Then, I’ll eat dinner and maybe do some more work, but I try to get to bed at a decent hour.

What CSE research areas interest you most and why?

Computational biology and applications in healthcare. Health affects everyone throughout their lives, so it is an important topic. Additionally, there are many applications and different angles to use computing in the field.

What do you do to relax or for fun?

Currently, I have been watching the TV show Severance. A new episode comes out weekly, so getting together with friends is something relaxing to look forward to. I also like to cook. When I have some free time, I enjoy taking a bit more time while cooking dinner to make something exciting or different.

What is your proudest achievement at Georgia Tech?

Last year, I qualified for the preliminary round of the track national championship. I love representing Georgia Tech at every competition throughout the season, but the opportunity to do it at a higher level and in a more prominent competition was extra special.

What are your plans after completing your M.S.?

After graduation, I will work at Sandia National Labs in their Technical Internships to Advance National Security (TITANS) program.

Summary sentence

Meet Grace Driskill, the first-ever student-athlete in the School of Computational Science and Engineering who holds records in the history books of Georgia Tech's Cross Country and Track and Field teams and the College of Computing.

Summary

We caught up with Driskill to learn more about her and how she balances academic and athletic responsibilities.

Dateline

Mon, 03/31/2025 - 12:00

Contact

Bryant Wine, Communications Officer
bryant.wine@cc.gatech.edu

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Keywords

College of Computing

School of Computational Science and Engineering

GT athletics

cross country

track and field

women's athletics

Daily Digest

Georgia Tech News Center

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Community

Student and Faculty

Student Honors and Achievements

Mercury ID

681454

Source updated

Mon, 03/31/2025 - 09:28

Computing Student Runs into History Books for Athletic and Academic Achievement

dgivens8 — Wed, 26 Mar 2025 13:59:41 +0000

Computing Student Runs into History Books for Athletic and Academic Achievement dgivens8 Wed, 03/26/2025 - 09:59

Grace Driskill has spent the last three years defining excellence at Georgia Tech. Between coding algorithms to setting running records, achievement has followed Driskill everywhere she has gone throughout her collegiate career.

Driskill came to Georgia Tech in 2023 as a graduate transfer to run long-distance for the women’s cross country and track teams. In doing so, she became the first-ever student-athlete in the School of Computational Science and Engineering (CSE).

While a pioneer in her own right, the trails that Driskill blazed will be her legacy at Georgia Tech and the School of CSE.

“We are so proud of Grace and so happy she came our way for graduate school,” said Alan Drosky, head coach of Georgia Tech’s cross country and track and field teams.

“She is obviously very talented academically and athletically, and she has contributed in a major way to our teams in competition.”

This year, Driskill recorded the fourth fastest time in history of the Georgia Tech Women's Indoor Track program. She clocked a 9:22.21 in the 3000-meter race at the David Hemery Valentine Invitational, held on Feb. 15 at Boston University.

Driskill’s record-setting performance at the Valentine Invitational came days after news of her latest academic achievement. She was among 19 Yellow Jackets selected to the 2024 All-ACC Cross Country Academic Team.

This listing was Driskill’s third after previous selections in 2024 for indoor track and 2023 for cross country. She is on pace for a 2025 indoor track selection, putting her on four All-ACC academic teams during her Georgia Tech career.

To earn an All-ACC academic team selection, student-athletes must attain a 3.0 grade point average in the previous semester and maintain an overall 3.0 cumulative average. Student-athletes must also compete in the ACC and/or NCAA championships during the most recent season.

In 2024, Driskill’s academic achievement earned her the Donald V. Jackson Fellowship. Georgia Tech’s College of Computing presents the award annually to well-rounded, first-year master’s students. The College selects fellows who best embody Jackson’s academic excellence and leadership values.

Driskill was instrumental in helping the women’s cross country team earn high rankings at the NCAA South Regionals both years she competed.

Driskill was the second-fastest Yellow Jacket and finished 34th overall at the 2023 regional, earning Georgia Tech 6th place among a field of 29 teams. At last year’s regional, she helped Georgia Tech place 7th out of 31 teams by finishing 41st overall and fourth from Georgia Tech.

“Last year, I qualified for the preliminary round of the track national championship,” Driskill said, remembering her proudest accomplishment at Georgia Tech.

“I love representing Georgia Tech at every competition throughout the season, but the opportunity to do it at a higher level and more prominent competition was extra special.”

A native of Tucson, Arizona, Driskill intends to return to the Southwest after graduating from Georgia Tech this summer. She will work with the Technical Internships to Advance National Security program (TITANS) at Sandia National Laboratories in Albuquerque, New Mexico.

Driskill started her collegiate career in 2020, competing on the cross country and track teams at the University of Arizona. She graduated in 2023 with a B.S. in computer science and a minor in mathematics.

In high school, Driskill was a four-year cross country letter winner and a two-year letter winner in track and field and softball. She earned first-team all-state honors her senior year in 2019 after state champion finishes in the 1600 and 3200-meter events.

“Grace’s contributions go way beyond what she does while running. She has a fantastic attitude, an easy-going demeanor, and a great sense of humor,” Drosky said. “She has become an integral figure on our teams and will be missed.”

Summary sentence

M.S. CSE student Grace Driskill achieved many athletic and academic accolades during her career at Georgia Tech, including being the first-ever student-athlete in the School of Computational Science and Engineering.

Summary

While a pioneer in her own right, the trails that Driskill blazed will be her legacy at Georgia Tech and the School of CSE.

Dateline

Wed, 03/26/2025 - 12:00

Contact

Bryant Wine, Communications Officer
bryant.wine@cc.gatech.edu

Keywords

College of Computing

School of Computational Science and Engineering

GT athletics

cross country

track and field

women's athletics

women's history month

Daily Digest

Georgia Tech News Center

News room topics

Campus and Community

Categories

Community

Student and Faculty

Student Honors and Achievements

Mercury ID

681370

Source updated

Wed, 03/26/2025 - 09:58

Machine Learning Encoder Improves Weather Forecasting and Tsunami Prediction

admin — Wed, 26 Mar 2025 01:20:41 +0000

Machine Learning Encoder Improves Weather Forecasting and Tsunami Prediction admin Tue, 03/25/2025 - 21:20

Successful test results of a new machine learning (ML) technique developed at Georgia Tech could help communities prepare for extreme weather and coastal flooding. The approach could also be applied to other models that predict how natural systems impact society.

Ph.D. student Phillip Si and Assistant Professor Peng Chen developed Latent-EnSF, a technique that improves how ML models assimilate data to make predictions.

In experiments predicting medium-range weather forecasting and shallow water wave propagation, Latent-EnSF demonstrated higher accuracy, faster convergence, and greater efficiency than existing methods for sparse data assimilation.

“We are currently involved in an NSF-funded project aimed at providing real-time information on extreme flooding events in Pinellas County, Florida,” said Si, who studies computational science and engineering (CSE).

“We're actively working on integrating Latent-EnSF into the system, which will facilitate accurate and synchronized modeling of natural disasters. This initiative aims to enhance community preparedness and safety measures in response to flooding risks.”

Latent-EnSF outperformed three comparable models in assimilation speed, accuracy, and efficiency in shallow water wave propagation experiments. These tests show models can make better and faster predictions of coastal flood waves, tides, and tsunamis.

In experiments on medium-range weather forecasting, Latent-EnSF surpassed the same three control models in accuracy, convergence, and time. Additionally, this test demonstrated Latent-EnSF's scalability compared to other methods.

These promising results support using ML models to simulate climate, weather, and other complex systems.

Traditionally, such studies require employment of large, energy-intensive supercomputers. However, advances like Latent-EnSF are making smaller, more efficient ML models feasible for these purposes.

The Georgia Tech team mentioned this comparison in its paper. It takes hours for the European Center for Medium-Range Weather Forecasts computer to run its simulations. Conversely, the ML model FourCastNet calculated the same forecast in seconds.

“Resolution, complexity, and data-diversity will continue to increase into the future,” said Chen, an assistant professor in the School of CSE.

“To keep pace with this trend, we believe that ML models and ML-based data assimilation methods will become indispensable for studying large-scale complex systems.”

Data assimilation is the process by which models continuously ingest new, real-world data to update predictions. This data is often sparse, meaning it is limited, incomplete, or unevenly distributed over time.

Latent-EnSF builds on the Ensemble Filter Scores (EnSF) model developed by Florida State University and Oak Ridge National Laboratory researchers.

EnSF’s strength is that it assimilates data with many features and unpredictable relationships between data points. However, integrating sparse data leads to lost information and knowledge gaps in the model. Also, such large models may stop learning entirely from small amounts of sparse data.

The Georgia Tech researchers employ two variational autoencoders (VAEs) in Latent-EnSF to help ML models integrate and use real-world data. The VAEs encode sparse data and predictive models together in the same space to assimilate data more accurately and efficiently.

Integrating models with new methods, like Latent-EnSF, accelerates data assimilation. Producing accurate predictions more quickly during real-world crises could save lives and property for communities.

To share Latent-EnSF to the broader research community, Chen and Si presented their paper at the SIAM Conference on Computational Science and Engineering (CSE25). The Society of Industrial and Applied Mathematics (SIAM) organized CSE25, held March 3-7 in Fort Worth, Texas.

Chen was one of ten School of CSE faculty members who presented research at CSE25, representing one-third of the School’s faculty body. Latent-EnSF was one of 15 papers by School of CSE authors and one of 23 Georgia Tech papers presented at the conference.

The pair will also present Latent-EnSF at the upcoming International Conference on Learning Representations (ICLR 2025). Occurring April 24-28 in Singapore, ICLR is one of the world’s most prestigious conferences dedicated to artificial intelligence research.

“We hope to bring attention to experts and domain scientists the exciting area of ML-based data assimilation by presenting our paper,” Chen said. “Our work offers a new solution to address some of the key shortcomings in the area for broader applications.”

Summary sentence

Ph.D. student Phillip Si and Assistant Professor Peng Chen developed Latent-EnSF, a technique that improves how ML models assimilate data to make predictions.

Summary

Ph.D. student Phillip Si and Assistant Professor Peng Chen developed Latent-EnSF, a technique that improves how ML models assimilate data to make predictions.

Dateline

Fri, 03/14/2025 - 12:00

Contact

Bryant Wine, Communications Officer
bryant.wine@cc.gatech.edu

Keywords

College of Computing

School of Computational Science and Engineering

go-researchnews

Research Horizons

Daily Digest

Georgia Tech News Center

machine learning

artificial intelligence

News room topics

Earth and Environment

Science and Technology

Categories

City Planning, Transportation, and Urban Growth

Community

Computer Science/Information Technology and Security

Engineering

Environment

Research

Student and Faculty

Student Research

Mercury ID

681164

Source updated

Tue, 03/25/2025 - 21:19

Study Highlights Challenges in Detecting Violent Speech Aimed at Asian Communities

admin — Mon, 12 Aug 2024 14:36:41 +0000

Study Highlights Challenges in Detecting Violent Speech Aimed at Asian Communities admin Mon, 08/12/2024 - 10:36

A research group is calling for internet and social media moderators to strengthen their detection and intervention protocols for violent speech.

Their study of language detection software found that algorithms struggle to differentiate anti-Asian violence-provoking speech from general hate speech. Left unchecked, threats of violence online can go unnoticed and turn into real-world attacks.

Researchers from Georgia Tech and the Anti-Defamation League (ADL) teamed together in the study. They made their discovery while testing natural language processing (NLP) models trained on data they crowdsourced from Asian communities.

“The Covid-19 pandemic brought attention to how dangerous violence-provoking speech can be. There was a clear increase in reports of anti-Asian violence and hate crimes,” said Gaurav Verma, a Georgia Tech Ph.D. candidate who led the study.

“Such speech is often amplified on social platforms, which in turn fuels anti-Asian sentiments and attacks.”

Violence-provoking speech differs from more commonly studied forms of harmful speech, like hate speech. While hate speech denigrates or insults a group, violence-provoking speech implicitly or explicitly encourages violence against targeted communities.

Humans can define and characterize violent speech as a subset of hateful speech. However, computer models struggle to tell the difference due to subtle cues and implications in language.

The researchers tested five different NLP classifiers and analyzed their F1 score, which measures a model's performance. The classifiers reported a 0.89 score for detecting hate speech, while detecting violence-provoking speech was only 0.69. This contrast highlights the notable gap between these tools and their accuracy and reliability.

The study stresses the importance of developing more refined methods for detecting violence-provoking speech. Internet misinformation and inflammatory rhetoric escalate tensions that lead to real-world violence.

The Covid-19 pandemic exemplified how public health crises intensify this behavior, helping inspire the study. The group cited that anti-Asian crime across the U.S. increased by 339% in 2021 due to malicious content blaming Asians for the virus.

The researchers believe their findings show the effectiveness of community-centric approaches to problems dealing with harmful speech. These approaches would enable informed decision-making between policymakers, targeted communities, and developers of online platforms.

Along with stronger models for detecting violence-provoking speech, the group discusses a direct solution: a tiered penalty system on online platforms. Tiered systems align penalties with severity of offenses, acting as both deterrent and intervention to different levels of harmful speech.

“We believe that we cannot tackle a problem that affects a community without involving people who are directly impacted,” said Jiawei Zhou, a Ph.D. student who studies human-centered computing at Georgia Tech.

“By collaborating with experts and community members, we ensure our research builds on front-line efforts to combat violence-provoking speech while remaining rooted in real experiences and needs of the targeted community.”

The researchers trained their tested NLP classifiers on a dataset crowdsourced from a survey of 120 participants who self-identified as Asian community members. In the survey, the participants labeled 1,000 posts from X (formerly Twitter) as containing either violence-provoking speech, hateful speech, or neither.

Since characterizing violence-provoking speech is not universal, the researchers created a specialized codebook for survey participants. The participants studied the codebook before their survey and used an abridged version while labeling.

To create the codebook, the group used an initial set of anti-Asian keywords to scan posts on X from January 2020 to February 2023. This tactic yielded 420,000 posts containing harmful, anti-Asian language.

The researchers then filtered the batch through new keywords and phrases. This refined the sample to 4,000 posts that potentially contained violence-provoking content. Keywords and phrases were added to the codebook while the filtered posts were used in the labeling survey.

The team used discussion and pilot testing to validate its codebook. During trial testing, pilots labeled 100 Twitter posts to ensure the sound design of the Asian community survey. The group also sent the codebook to the ADL for review and incorporated the organization’s feedback.

“One of the major challenges in studying violence-provoking content online is effective data collection and funneling down because most platforms actively moderate and remove overtly hateful and violent material,” said Tech alumnus Rynaa Grover (M.S. CS 2024).

“To address the complexities of this data, we developed an innovative pipeline that deals with the scale of this data in a community-aware manner.”

Emphasis on community input extended into collaboration within Georgia Tech’s College of Computing. Faculty members Srijan Kumar and Munmun De Choudhury oversaw the research that their students spearheaded.

Kumar, an assistant professor in the School of Computational Science and Engineering, advises Verma and Grover. His expertise is in artificial intelligence, data mining, and online safety.

De Choudhury is an associate professor in the School of Interactive Computing and advises Zhou. Their research connects societal mental health and social media interactions.

The Georgia Tech researchers partnered with the ADL, a leading non-governmental organization that combats real-world hate and extremism. ADL researchers Binny Mathew and Jordan Kraemer co-authored the paper.

The group will present its paper at the 62nd Annual Meeting of the Association for Computational Linguistics (ACL 2024), which takes place in Bangkok, Thailand, Aug. 11-16

ACL 2024 accepted 40 papers written by Georgia Tech researchers. Of the 12 Georgia Tech faculty who authored papers accepted at the conference, nine are from the College of Computing, including Kumar and De Choudhury.

“It is great to see that the peers and research community recognize the importance of community-centric work that provides grounded insights about the capabilities of leading language models,” Verma said.

“We hope the platform encourages more work that presents community-centered perspectives on important societal problems.”

Visit https://sites.gatech.edu/research/acl-2024/ for news and coverage of Georgia Tech research presented at ACL 2024.

Summary sentence

A study of language detection software found that algorithms struggle to differentiate anti-Asian violence-provoking speech from general hate speech. Left unchecked, threats of violence online can go unnoticed and turn into real-world attacks.

Summary

A research group is calling for internet and social media moderators to strengthen their detection and intervention protocols for violent speech.

Dateline

Wed, 08/07/2024 - 12:00

Contact

Bryant Wine, Communications Officer
bryant.wine@cc.gatech.edu

Keywords

go-ai

Daily Digest

Research Horizons

go-researchnews

School of Computational Science and Engineering

artificial intelligence (AI)

News room topics

Science and Technology

Categories

Computer Science/Information Technology and Security

Research

Student and Faculty

Student Research

Mercury ID

675889

Source updated

Mon, 08/12/2024 - 10:35

Faculty to use AI for Protein Design and Discovery with Support of $1.8 Million NIH Grant

admin — Mon, 13 May 2024 14:38:41 +0000

Faculty to use AI for Protein Design and Discovery with Support of $1.8 Million NIH Grant admin Mon, 05/13/2024 - 10:38

The National Institute of Health (NIH) has awarded Yunan Luo a grant for more than $1.8 million to use artificial intelligence (AI) to advance protein research.

New AI models produced through the grant will lead to new methods for the design and discovery of functional proteins. This could yield novel drugs and vaccines, personalized treatments against diseases, and other advances in biomedicine.

“This project provides a new paradigm to analyze proteins’ sequence-structure-function relationships using machine learning approaches,” said Luo, an assistant professor in Georgia Tech’s School of Computational Science and Engineering (CSE).

“We will develop new, ready-to-use computational models for domain scientists, like biologists and chemists. They can use our machine learning tools to guide scientific discovery in their research.”

Luo’s proposal improves on datasets spearheaded by AlphaFold and other recent breakthroughs. His AI algorithms would integrate these datasets and craft new models for practical application.

One of Luo’s goals is to develop machine learning methods that learn statistical representations from the data. This reveals relationships between proteins’ sequence, structure, and function. Scientists then could characterize how sequence and structure determine the function of a protein.

Next, Luo wants to make accurate and interpretable predictions about protein functions. His plan is to create biology-informed deep learning frameworks. These frameworks could make predictions about a protein’s function from knowledge of its sequence and structure. It can also account for variables like mutations.

In the end, Luo would have the data and tools to assist in the discovery of functional proteins. He will use these to build a computational platform of AI models, algorithms, and frameworks that ‘invent’ proteins. The platform figures the sequence and structure necessary to achieve a designed proteins desired functions and characteristics.

“My students play a very important part in this research because they are the driving force behind various aspects of this project at the intersection of computational science and protein biology,” Luo said.

“I think this project provides a unique opportunity to train our students in CSE to learn the real-world challenges facing scientific and engineering problems, and how to integrate computational methods to solve those problems.”

The $1.8 million grant is funded through the Maximizing Investigators’ Research Award (MIRA). The National Institute of General Medical Sciences (NIGMS) manages the MIRA program. NIGMS is one of 27 institutes and centers under NIH.

MIRA is oriented toward launching the research endeavors of young career faculty. The grant provides researchers with more stability and flexibility through five years of funding. This enhances scientific productivity and improves the chances for important breakthroughs.

Luo becomes the second School of CSE faculty to receive the MIRA grant. NIH awarded the grant to Xiuwei Zhang in 2021. Zhang is the J.Z. Liang Early-Career Assistant Professor in the School of CSE.

“After NIH, of course, I first thanked my students because they laid the groundwork for what we seek to achieve in our grant proposal,” said Luo.

“I would like to thank my colleague, Xiuwei Zhang, for her mentorship in preparing the proposal. I also thank our school chair, Haesun Park, for her help and support while starting my career.”

Summary sentence

The National Institute of Health (NIH) has awarded Yunan Luo a grant for more than $1.8 million to use artificial intelligence (AI) to advance protein research.

Summary

The National Institute of Health (NIH) has awarded Yunan Luo a grant for more than $1.8 million to use artificial intelligence (AI) to advance protein research.

Dateline

Wed, 11/29/2023 - 12:00

Contact

Bryant Wine, Communications Officer
bryant.wine@cc.gatech.edu

Keywords

go-researchnews

Daily Digest

College of Computing

School of Computational Science and Engineering

Computational Science and Engineering

artificial intelligence

machine learning

go-ai

Research Horizons

News room topics

Science and Technology

Categories

Biotechnology, Health, Bioengineering, Genetics

Computer Science/Information Technology and Security

Life Sciences and Biology

Research

Student and Faculty

Mercury ID

671293

Source updated

Mon, 05/13/2024 - 10:37

School of Computational Science and Engineering

Campus Connection Inspires Mother and Son to Find Purpose and Passion

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Faculty Earn Fellowships for Heart Modeling and Data Optimization Research

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School Award Winners Impress on World, National, and Institute Stages

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Thesis on Human-Centered AI Earns Honors from International Computing Organization

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Meet CSE Profile: Grace Driskill

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Computing Student Runs into History Books for Athletic and Academic Achievement

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Machine Learning Encoder Improves Weather Forecasting and Tsunami Prediction

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Study Highlights Challenges in Detecting Violent Speech Aimed at Asian Communities

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Faculty to use AI for Protein Design and Discovery with Support of $1.8 Million NIH Grant

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