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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.

CSE Faculty and Student Research Awards

We congratulate our faculty members that have received research awards. They are:

  • Dr. Christian O'Reilly for receiving funds from NIH-NIMH on the project titled "The Role of Autonomic Regulation of Attention in the Emergence of ASD"
  • Dr. Jason Bakos for receiving funds from NSF on the project titled "Collaborative Research: SHF: Small: Sub-millisecond Topological Feature Extractor for High-Rate Machine Learning"
  • Dr. Homayoun Valafar for receiving funds from Prisma Health-Upstate on the project titled "Analysis of Patient Glycomic Profiles in Search for Breast Cancer Signatures Using Machine Learning Approach"
  • Dr. Jianjun Hu for receiving funds from EPSCoR/IDeA/SC Commission on the project titled "GEAR CRP: Deep learning reinforced high-resolution semiconductor radiation detector for real- time medical imaging"
  • Dr. Micheal Huhns for receiving funds from University of Maryland/ARLIS/DOD on the project titled "Information Competition Simulator"
  • Mr. Lexington Wahlen for receiving a NASA South Carolina Space Grant Consortium STEM Outreach Award for the project titled "Wordification: A New Way of Teaching English Spelling Patterns"
  • Mr. Musa Azeem for receiving a NASA South Carolina Space Grant Consortium STEM Outreach Award for the project titled "Unobtrusive and User-Friendly Acquisition of Multi-sensor Data from Wearable Smartwatch Technology"

Capstone Projects Showcase 2023

This year the students in the Senior Capstone course developed 45 apps. There are:

  • 17 web applications using technologies such as Django, node, express, Angular, react, Vue, firebase, AWS.
  • 23 Android or iOS mobile apps using technologies such as Android Studio, Flutter, React Native Android, XCode, Firebase.
  • 5 desktop apps using technologies such as Unreal Engine, Unity, C#, Pygame.

You can view video demos of all of them. 

Summer Classes in .NET, Mobile, Azure Cloud

This Summer we are offering some 500-level classes that we do not usually offer in the Summer, these include Windows Programming (.NET), Mobile Application Development, Visualization Tools, and a class on Cloud Computing (Azure) which has not been added to the schedule yet. Check the Summer schedule at my.sc.edu. Some of these classes will bet taught by people from Capgemini. CS majors can use them as part of a Cloud-Native Application Development career, along with some MGMT classes for the Application Area.

Using Machine Learning Algorithms for Challenging Image Analyses

As artificial intelligence (AI) and machine learning continue to transform patient care, Computer Science and Engineering Assistant Professor Forest Agostinelli is currently pursuing research on predicting outcomes for PAD patients.

PAD is a growing concern among aging populations and usually caused by a blockage where arteries in the legs are calcified, which is the build-up of calcium-containing plaque in the artery. The risk of developing PAD is increased by smoking, an unhealthy diet, diabetes and high blood pressure. 

Read full article here.