Checkout our website for prospective students.

Dr. Zand Receives NSF CAREER Award

Ramtin Zand

We are proud to announce that Dr. Ramtin Zand has received an NSF CAREER award for his research on "Heterogeneous Neuromorphic and Edge Computing Systems for Realtime Machine Learning Technologies". 

This project aims to harness the combined capabilities of neuromorphic and edge computing to forge a heterogeneous machine learning system. Its primary goal is to enable computer vision and language models on resource- and energy-constrained devices at an unprecedented scale. It focuses on several key aspects: (1) developing hybrid models that merge the energy efficiency, temporal sparsity, and spatiotemporal processing of spiking neural networks with the global processing of transformer models for complex large-scale computer vision tasks, (2) creating a methodology to deploy large language models on edge devices by employing system-level innovations such as computational graph modifications, custom kernels, and mathematical refactoring, (3) designing a flexible edge artificial intelligence (AI) accelerator to overcome hardware limitations hindering real-time implementation of large transformer models at the edge, (4) seamlessly integrating a heterogeneous system of mobile processors, edge AI accelerators, and neuromorphic hardware for a comprehensive end-to-end solution. Throughout the project, rigorous investigation delves into critical trade-offs between bandwidth, accuracy, performance, and energy consumption.

AAAI Best Demo Award

PosterThe paper titled  "Expressive and Flexible Simulation of Information Spread Strategies in Social Networks Using Planning," by Bharath Muppasani, Vignesh Narayanan, Biplav Srivastava, Michael N. Huhns, has been selected for the Best Demo Award at AAAI-24. AAAI is a top AI conference and was held over the past week.

The work enables detailed simulations of opinion evolution and strategic interventions using planning. Designed to enhance human-AI collaboration, the framework supports the creation of strategies that facilitate a deeper understanding and informed engagement with the opinion evolution in networks. It was selected from 30 demos, which themselves were selected from a pool of 97 submissions. You can read the poster and watch the video presentation.

Students Win Data Science Competition

We congratulate our three graduate students who took first place in a national data science competition held on January 26-28th this year: Sankalp Jajee, Gaurav Kumar, and Supriya Nayanala.

This competition has been organized by Big Data Health Science Center annually for the past five years. This year, the competition featured 30 teams from 17 universities in the US: University of South Carolina, Arkansas State University, Boston University, Central Washington University, College of Charleston, Dartmouth College, Duke University, Louisiana State University, Middle Tennessee State University, Minnesota University-Duluth, Oklahoma State University, University of Louisville, University of Memphis, University of North Carolina at Chapel Hill, University of West Florida, Vanderbilt University, and Yale University. Read more about this event and our students' accomplishments.

Outstanding Senior Awards

Each year the Faculty of the Department of Computer Science and Engineering (CSE) award four Outstanding Senior Awards. This process is never easy given the many excellent and accomplished students in our program. This year, we have decided that the 2024 Computer Science and Engineering Outstanding Senior Awards go to:

  • Anna Michelitch: Computer Science Outstanding Senior Award
  • Musa Azeem: Computer Engineering Outstanding Senior Award
  • Valerie Duffey: Computer Engineering SCSPE Award
  • Terry Hancock: Computer Information Systems Outstanding Senior Award

awardees will be honored at the University Awards Day ceremony.

USC Part of U.S. Artificial Intelligence Safety Institute (USAISI)

University of South Carolina is collaborating with the National Institute of Standards and Technology (NIST) in the Artificial Intelligence Safety Institute Consortium to develop science-based and empirically backed guidelines and standards for AI measurement and policy, laying the foundation for AI safety across the world. This will help ready the U.S. to address the capabilities of the next generation of AI models or systems, from frontier models to new applications and approaches, with appropriate risk management strategies. Please see the announcement, the members list which is the who's who in the nation, quotes from participants, and the scope of the consortium.

The original members participating from the University are: Engineering - Csilla Farkas, Michael Huhns, Vignesh Narayanan, Amit Sheth, Biplav Srivastava (PI), Dezhi Wu; Journalism - Brett Robertson; Law - Bryant Walker Smith.

Dr. Sur Advanced Wireless Networking and Sensing Technologies Research

Imagine driving at night in heavy fog without having to worry about not seeing the car or a pedestrian in front of you. Or a physician monitoring a patient’s rehabilitation without any visits to the doctor’s office.

Computer Science and Engineering Assistant Professor Sanjib Sur’s research team is working toward designing and implementing innovative systems and technologies with advanced wireless and mobile infrastructure to help improve individuals’ health, safety and convenience.  Read the full story here.

Dr. Huhns Receives TCI Distinguished Service Award

Please join us in celebrating Dr. Huhns' recent recognition by receiving the 2023 Technical Community on the Internet (TCI) Distinguished Service Award. Dr. Huhns has been an influential member of our CSE family as well as an influential member of the broader scientific and engineering community. I have certainly learned a lot from him during my tenure at USC and can personally attest to the accuracy of this award. This is a well-deserved recognition. Well done, and we are proud to have you as a colleague. 

Educating with Empathy

Portia Plante knew she wanted to teach computer science from an early age, but her path to academia was not straightforward.

“My mom was an elementary school teacher, so I grew up sitting in her classroom all the time. When I got older, I would teach the kids how to make websites,” Plante says.

At that time, the demand for teachers in Canada, where Plante spent the first part of her life, was low. So, she chose to pursue a stable career in the software development industry. After earning a bachelor’s degree in software engineering from the University of Waterloo in Ontario, she accepted a role at Microsoft as a program manager, which brought her to the United States.

Read the full story here.

Recent Publications: Natural Language Processiong

The following papers written by our AI Institute members were accepted for presentation at the 2023 Conference on Empirical Methods in Natural Language Processing:

  • Counter Turing Test (CT^2): AI-Generated Text Detection is Not as Easy as You May Think - Introducing AI Detectability Index (ADI). Megha Chakraborty, S.M Towhidul Islam Tonmoy, S M Mehedi Zaman, Shreya Gautam, Tanay Kumar, Krish Sharma, Niyar R Barman, Chandan Gupta, Vinija Jain, Aman Chadha, Amit P. ShethAmitava Das.
  • The Troubling Emergence of Hallucination in Large Language Models - An Extensive Definition, Quantification, and Prescriptive Remediations. Vipula Rawte, Swagata Chakroborty, Agnibh Pathak, Anubhav Sarkar, S.M Towhidul Islam Tonmoy, Aman Chadha, Amit P. Sheth, Amitava Das.
  • FACTIFY3M: A benchmark for multimodal fact verification with explainability through 5W Question-Answering. Megha Chakraborty, Khushbu Pahwa, Anku Rani, Shreyas Chatterjee, Dwip Dalal, Harshit Dave, Ritvik G, Preethi Gurumurthy, Adarsh Ashok Mahor, Samahriti Mukherjee, Aditya Pakala, Ishan Paul, Janvita Reddy, Arghya Sarkar, Kinjal Sensharma, Aman Chadha, Amit P. Sheth, Amitava Das.

The acceptance of these papers at EMNLP, a leading conference in NLP, is a testament to the high quality of research being conducted at the AI Institute. The papers address important and challenging problems in NLP, and their findings have the potential to significantly advance the state of the art in this field.

Why Computer Science? Vansh Nagpal

"I am passionate about computer science because I can use my skills to work on new and beneficial applications for society. In the SyReX lab under Dr. Sanjib Sur, I study the applications of 5G networks and devices for pedestrian/vehicle detection to enhance the functionality of autonomous vehicles. In this case, my research contributions can help implement a system that would reduce the loss of life due to traffic accidents." 

Pictured here: A deep learning-based approach for developing a system to detect pedestrians based on camera (top) and millimeter wave (red circuit board) data. Low visibility is simulated within the plastic cube using a fog machine.

Read the rest here.

New Faculty: Dr. Frank (Peng) Fu

We would like to welcome Dr. Frank (Peng) Fu as the newest Assistant Professor in the Department. Dr Fu's research interests are in type theories and their applications, quantum programming languages and their categorical semantics. He received his PhD in Computer Science at the University of Iowa and his Bachelor's at the Huazhong University of Science and Technology in China.

USC awarded NSF MRI grant to acquire HPC cluster for AI-for-science research and education in South Carolina

The University of South Carolina was just awarded $1.1M with a National Science Foundation MRI grant to purchase a High-Performance Computing cluster (HPC) for boosting AI enabled science, engineering, and education in South Carolina. This grant will be led by the PI Prof. Ming Hu (Mechanical engineering), two Computer Science Co-PIs (Prof. Jianjun Hu and Prof. Forest Agostinelli) and additional two Co-PIs (Prof. Sophya Garashchuk of chemistry, and Sagona, Paul of Div. IT).

The new HPC instrument (with both new GPU and CPU servers) will be hosted at USC but will be made accessible to students of more than 10 regional universities such as Claflin University, Furman University, Francis Marion University, Costal Carolina University, College of Charleston, Charleston Southern University, Winthrop University, Presbyterian College, Benedict College, USC Beaufort and etc. It will promote research in diverse fields such as materials science, physics, chemistry, engineering, computer science, bioinformatics, health science and humanities, all enhanced by the HPC, big data and AI tools. The project team will also organize training workshops for AI-enabled scientific research and engineering innovation, education programs for undergraduate students, and summer camps for high school students in the coming years. More information will be posted on the project website at http://ai4science.sc.edu.

Student Q&A: James Thurlow

Computer science and engineering senior James Thurlow came to the University of South Carolina from Beaufort, South Carolina. Along with cultivating his interest in computers, the South Carolina Lowcountry also developed Thurlow’s interest in sailing throughout his childhood. At USC, he has been active in student government, Naval ROTC, Theta Tau professional engineering fraternity and president of the Gamecock Sailing Club. Thurlow’s academic journey will culminate in May 2023, and he will enter the U.S. Navy after making impacts throughout the USC campus. 

Read the full Q&A article here.

Dr. Hu Receives NSF Grant for Machine Learning in Materials Discovery

Prof. Jianjun Hu, director of the Machine Learning and Evolution Lab and his collaborators Prof Ming Hu (PI) from USC Mechanical engineering and Prof. Christopher Wolverton (Co-PI) of Northwestern University have just acquired a NSF grant on generating a modern phonon database and developing machine learning prediction, analysis, and visualization tools for data driven materials discovery, which will speed up research and design of novel thermoelectrics, superconductors, photovoltaics, superionic conductors.

Phonon Database Generation, Analysis, and Visualization for Data Driven Materials Discovery

Material databases and their related computing infrastructures have become the major cornerstone of current data driven and artificial intelligence (AI) based materials discovery. However, among the rich material properties of interest to the materials community, few databases have comprehensively included phonon properties, which are at the center of materials science and are related to diverse functionalities such as thermoelectrics, superconductors, photovoltaics, superionic conductors, etc. This project meets these urgent needs to generate a comprehensive phonon database along with analysis, visualization, navigation, and visualization tools, combined with multi-channel infrastructure-community communication and feedback. The phonon database will become an excellent complement to the currently widely used material databases. Developing such an infrastructure will be beneficial for all areas of materials science and engineering, accelerating the prediction, design, and synthesis of novel materials with various emerging applications in modern science and technology. The project will promote the engagement of underrepresented and minority students in research, equip engineering students with interdisciplinary expertise and frontier knowledge crucial to their future careers, and fulfill the mission to prepare a high-quality workforce for science, technology, and engineering. The project will also develop new course materials for undergraduate and graduate computational materials science courses.