Join the Georgia Tech Library in person and virtually Tuesday Oct. 14 through Thursday, Oct. 16 for our Inaugural AI Week, a mix of panel discussions and seminars aimed at celebrating and investigating the myriad ways researchers, students and faculty harness the burgeoning technology. 

“We’re thrilled to bring this slate of events, discussions and learning opportunities to campus focused on the game-changing use of artificial intelligence happening across the Institute,” said Dean Leslie Sharp. “The Library has brought together industry experts, student practitioners and research faculty to offer a varied and intriguing set of learning opportunities for our community.”

AI Week 2025 will include five separate in-person and online events, including: 

• Faculty Panel Discussion: Harnessing AI Tools to Make Teaching More Effective and Engaging
  Oct. 14 | 10:30-11:15 a.m.
  Scholars Event Network, first floor Price Gilbert
   
• Panel Discussion: Enhancing Research with AI Tools 
  Oct. 14 | 1-2 p.m.
  Scholars Event Network, first floor Price Gilbert
   
• Trademark Fundamentals and Searching (ONLINE)
  Oct. 15 | 2-3 p.m.
  Online
   
• Patents in the Age of AI: Navigating the Changing Landscape (ONLINE)
  Oct. 16 | 2-3 p.m.
  Online
   
• Exploring AI Together for Study, Copilot and Firefly
  Oct. 16 | 4:30-5:30 p.m. 
  Crosland Tower Fourth Floor Classroom

The idea of people experiencing their favorite mobile apps as immersive 3D environments took a step closer to reality with a new Google-funded research iniative at Georgia Tech. 

A new approach proposed by Tech researcher Yalong Yang uses generative artificial intelligence (GenAI) technologies to convert almost any mobile or web-based app into a 3D environment. 

That includes application software programs from Microsoft and Adobe as well as any social media (Tiktok), entertainment (Spotify), banking (PayPal), or food service app (Uber Eats) and everything in between.

Yang aims to make the 3D environments compatible with augmented and virtual reality (AR/VR) headsets and smart glasses. He believes his research could be a breakthrough in spatial computing and change how humans interact with their favorite apps and computer systems in general.

“We’ll be able to turn around and see things we want, and we can grab them and put them together,” said Yang, an assistant professor in the School of Interactive Computing. “We’ll no longer use a mouse to scroll or the keyboard to type, but we can do more things like physical navigation.”

Yang’s proposal recently earned him recognition as a 2025 Google Research Scholar. Along with converting popular social apps, his platform will be able to instantly render Photoshop, MS Office, and other workplace applications in 3D for AR/VR devices.

“We have so many applications installed in our machines to complete all the various types of work we do,” he said. “We use Photoshop for photo editing, Premiere Pro for video editing, Word for writing documents. We want to create an AR/VR ecosystem that has all these things available in one interface with all apps working cohesively to support multitasking.”

Filling The Gap With AI

Just as Google’s Veo and Open AI’s Sora use generative-AI to create video clips, Yang believes it can be used to create interactive, immersive environments for any Android or Apple app. 

“A critical gap in AR/VR is that we do not have all those existing applications, and redesigning all those apps will take forever,” he said. “It’s urgent that we have a complete ecosystem in VR to enable us to do the work we need to do. Instead of recreating everything from scratch, we need a way to convert these applications into immersive formats.”

Walk into any room Aleksandra Teng Ma’s been working in this summer, and you’ll probably hear a mix of experimental sounds, snippets of Amy Winehouse vocals, and the occasional Animal Crossing tune playing in the background. That’s just how her brain works—blending tech, artistry, and everyday play into something entirely her own.

Aleksandra is a master’s student in Music Technology at Georgia Tech, but “student” barely scratches the surface. This summer, she’s been everywhere—physically in Massachusetts and intellectually somewhere between a Pride performance and a human-AI jam session at MIT.

“I’m always with my microphone and MIDI keyboard,” she says, like it’s just second nature. “I love singing and coming up with tunes.”

Live from MIT — It’s Human + AI Jamming
Forget dusty textbooks and silent labs—Aleksandra’s research life is about real-time musical interactions between humans and AI. As a visiting researcher at MIT this summer, she’s digging into what it looks like when musicians "jam" with intelligent systems. Think futuristic band practice, but with algorithms joining in.

“It’s giving me a lot of exposure to co-design methodologies,” she explains, “and letting me observe how musicians respond to each other—and to AI.”

It’s not just code and theory, either. The insights come alive when she brings them to the stage. This summer, Aleksandra’s band performed at The Music Porch in Reading, MA for Pride Month. Their cover of Pink Pony Club turned into a moment she won’t forget.

“It was so fun seeing people—especially teenagers—singing and dancing together,” she says. “That’s one of those moments where I just thought, yep, this is why I picked music tech.”

From Winehouse Covers to Ableton Experiments
Despite her research chops, Aleksandra hasn’t lost touch with the joy of just making music. She sings and plays keyboard in a band, covers Amy Winehouse songs, and occasionally writes music just for fun. (Her dream studio partner? You guessed it: Amy herself.)

She’s also been expanding her technical toolkit this summer, diving deeper into sound design with Ableton and Serum.

“Still learning,” she says, “but I’m using them for sound design in songs—and loving it.”

And then there are the unexpected “whoa” moments. Like when she built a vocal patch for the Pixies’ Where Is My Mind? to use live during a performance.

“It was haunting,” she says. “And it worked so well live.”

Dream Tech and Georgia Tech
Ask Aleksandra what she’d invent if she could mash up two instruments, and she already has an idea:

“Automatic vocal effects through a microphone with a built-in amplifier,” she says, laughing. “Honestly, someone probably already made this, but I want it anyway.”

That kind of thinking is exactly what her time at Georgia Tech has sparked. Before the program, she saw music mostly through the lens of conventional instruments. Now? She’s all about how software and hardware can expand what music even is.

Her Summer, in Sound
If Aleksandra’s summer had a vibe, it’d be:

• A creek bubbling in the background
• A long, ghostly reverb trail on a siren vocal
• And the ever-cozy tones of Animal Crossing

Not exactly your typical lab soundtrack—but that’s the beauty of it.

This fall, she’s heading back to Georgia Tech after a gap year at Bose, ready to jump into research on multimodal music source separation (AKA teaching machines to pick apart and understand layers in music the way humans do).

And yes, she’ll still be singing.

Hits with Aleksandra

• Current summer jams: Rosebud by Oklou & the new Lorde album
• What people don’t “get” about her work: “How music signals work on a granular level”

Aleksandra Ma doesn’t just study music tech—she lives it. Whether she’s tweaking reverb patches, performing under porch lights, or teaching AI how to groove, she’s showing what it really means to be a 21st-century musician.

Computer vision enables AI to see the world. It’s already being used for self-driving vehicles, medical imaging, face recognition, and more. 

Georgia Tech faculty and student experts advancing this field were in action in June at the globally renowned CVPR conference from IEEE and the Computer Vision Foundation. Georgia Tech was in the top 10% of all organizations for lead authors and the top 4% for number of papers. More than 2000 organizations had research accepted into CVPR's main program.

Watch the video and hear from Tech experts about what’s new and what’s coming next. Featured students include College of Computing experts Fiona Ryan, Chengyue Huang, Brisa Maneechotesuwan, and Lex Whalen.

These researchers in computer vision are showing how they are extending AI capabilities with image and video data.

HIGHLIGHTS:

- College of Computing faculty, from the Schools of Interactive Computing (IC) and Computer Science (CS), represented the majority of Tech's faculty in the CVPR papers program (8 of 10 faculty).

- IC faculty Zsolt Kira and Bo Zhu each coauthored an oral paper, the top 3% of accepted papers. IC faculty member Judy Hoffman coauthored two highlight papers, the top 20% of acceptances.

- Georgia Tech is in the top 10% of all organizations for number of first authors and the top 4% for number of papers. More than 2,000 organizations had research in the main program.

- Tech experts were on 30 research paper teams across 16 research areas. Topics with more than one Tech expert included:

• Image/video synthesis & generation
• Efficient and scalable vision
• Multi-modal learning
• Datasets and evaluation
• Humans: Face, body, gesture, etc.
• Vision, language, and reasoning 
• Autonomous driving
• Computational imaging

 

A groundbreaking new medical dataset is poised to revolutionize healthcare in Africa by improving chatbots’ understanding of the continent’s most pressing medical issues and increasing their awareness of accessible treatment options.

AfriMed-QA, developed by researchers from Georgia Tech and Google, could reduce the burden on African healthcare systems. 

The researchers said people in need of medical care file into overcrowded clinics and hospitals and face excruciatingly long waits with no guarantee of admission or quality treatment. There aren’t enough trained healthcare professionals available to meet the demand.

Some healthcare question-answer chatbots have been introduced to treat those in need. However, the researchers said there’s no transparent or standardized way to test or verify their effectiveness and safety.

The dataset will enable technologists and researchers to develop more robust and accessible healthcare chatbots tailored to the unique experiences and challenges of Africa. 

One such new tool is Google’s MedGemma, a large-language model (LLM) designed to process medical text and images. AfriMed-QA was used for training and evaluation purposes.

AfriMed-QA stands as the most extensive dataset that evaluates LLM capabilities across various facets of African healthcare. It contains 15,000 question-answer pairs culled from over 60 medical schools across 16 countries and covering numerous medical specialties, disease conditions, and geographical challenges. 

Tobi Olatunji and Charles Nimo co-developed AfriMed-QA and co-authored a paper about the dataset that will be presented at the Association for Computational Linguistics (ACL) conference next week in Vienna.

Olatunji is a graduate of Georgia Tech’s Online Master of Science in Computer Science (OMSCS) program and holds a Doctor of Medicine from the College of Medicine at the University of Ibadan in Nigeria. Nimo is a Ph.D. student in Tech’s School of Interactive Computing, where he is advised by School of IC professors Michael Best and Irfan Essa.

Focus on Africa

Nimo, Olatunji, and their collaborators created AfriMed-QA as a response to MedQA, a large-scale question-answer dataset that tests the medical proficiency of all major LLMs. That includes Google’s Gemini, OpenAI’s ChatGPT, and Anthropic’s Claude, among others.

However, because MedQA is trained solely on the U.S. Medical License Exams, Nimo said it is not adequate to serve patients in underdeveloped African countries nor the Global South at-large.

“AfriMed-QA has the contextualized and localized understanding of African medical institutions that you don’t get from Med-QA,” Nimo said. “There are specific diseases and local challenges in our dataset that you wouldn't find in any U.S.-based dataset.”

Olatunji said one problem African users may encounter using LLMs trained on MedQA is that they may advise unfeasible treatments or unaffordable prescription drugs.

“You consider the types of drugs, diagnostics, procedures, or therapies that exist in the U.S. that are quite advanced. These treatments are much more accessible, for example in the US, and Europe,” Olatunji said. “But in Africa, they’re too expensive and many times unavailable. They may cost over $100,000, and many people have no health insurance. Why recommend such treatments to someone who can’t obtain them?”

Another problem may be that the LLM doesn’t take a medical condition seriously if it isn’t predominant in the U.S.

“We tested many of these models, for example, on how they would manage sickle-cell disease signs and symptoms, and they focused on other “more likely” causes and did not rank or consider sickle cell high enough as a possible cause,” he said. “They, for example, don’t consider sickle-cell as important as anemia and cancer because sickle-cell is less prevalent in the U.S.”

In addition to sickle-cell disease, Olatunji said some of the healthcare issues facing Africa that can be improved through AfriMed-QA include:

• HIV treatment and prevention
• Poor maternal healthcare
• Widespread malaria cases
• Physician shortage
• Clinician productivity and operational efficiency

Google Partnership

Mercy Asiedu, senior author of the AfriMed-QA paper and research scientist at Google Research, has dedicated her career to improving healthcare in Africa. Her work began as a Ph.D. student at Duke University, where she invented the Callascope, a groundbreaking non-invasive tool for gynecological examinations

With her current focus on democratizing healthcare through artificial intelligence (AI), Asiedu, who is from Ghana, helped create a research consortium to develop the dataset. The consortium consists of Georgia Tech, Google, Intron, Bio-RAMP Research Labs, the University of Cape Coast, the Federation of African Medical Students Association, and Sisonkebiotik.

Sisonkebiotik is an organization of researchers that drives healthcare initiatives to advance data science, machine learning, and AI in Africa.

Olatunji leads the Bio-RAMP Research Lab, a community of healthcare and AI researchers, and he is the founder and CEO of Intron, which develops natural-language processing technologies for African communities.

In May, Google released MedGemma, which uses both the MedQA and Afri-MedQA datasets to form a more globally accessible healthcare chatbot. MedGemma has several versions, including 4-billion and 27-billion parameter models, which support multimodal inputs that combine images and text.

“We are proud the latest medical-focused LLM from Google, MedGemma, leverages AfriMed-QA and improves performance in African contexts,” Asiedu said. 

“We started by asking how we could reduce the burden on Africa’s healthcare systems. If we can get these large-language models to be as good as experts and make them more localized with geo-contextualization, then there’s the potential to task-shift to that.”

The project is supported by the Gates Foundation and PATH, a nonprofit that improves healthcare in developing countries.

A study from Georgia Tech’s School of Chemical and Biomolecular Engineering introduces LEONARDO, a deep generative AI model that reveals the hidden dynamics of nanoparticle motion in liquid environments. By analyzing over 38,000 experimental trajectories captured through liquid-phase transmission electron microscopy (LPTEM), LEONARDO not only interprets but also generates realistic simulations of nanoscale movement. This innovation marks a major leap in understanding the physical forces at play in nanotechnology, with promising implications for medicine, materials science, and sensor development.

Read the full story.

 

Giga, a global initiative focused on expanding internet connectivity to schools, launched its new tech and innovation event series “Giga Talks” on June 19 with a keynote address from Pascal Van Hentenryck, a leading artificial intelligence expert from the Georgia Institute of Technology.

Van Hentenryck serves as the A. Russell Chandler III Chair and Professor in Georgia Tech’s H. Milton Stewart School of Industrial and Systems Engineering. He is also the director of Tech AI, Georgia Tech’s new strategic hub for artificial intelligence, and the U.S. National Science Foundation AI Institute for Advances in Optimization (AI4OPT), which operates under Tech AI’s umbrella.

In his talk, “AI for Social Good,” Van Hentenryck showcased how AI technologies can drive impact across key sectors—including mobility, education, healthcare, disaster response, and e-commerce. Drawing from ongoing research and real-world deployments, he emphasized the critical role of human-centered design and interdisciplinary collaboration in developing AI that benefits society at large.

“AI has tremendous potential to serve the public good when guided by ethics, equity, and purpose-driven innovation,” said Van Hentenryck. “At Georgia Tech, our work aims to harness this potential to create meaningful change in people’s lives.”

The event marked the debut of Giga Talks, a new speaker series designed to convene global thought leaders, engineers, and policymakers around timely issues in technology and innovation. The initiative supports Giga’s broader mission to connect every school in the world to the internet and unlock digital opportunities for children everywhere.

A video recording of Van Hentenryck’s talk is available on here.