My Computer Science and Engineering Department

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. 

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.

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. Sheth, Amitava 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.

"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.

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.

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.

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.

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.

The John H. Fain scholarship provides an incentive for upper level Computer Information Systems (CIS) and Computer Science (CS) majors to become entrepreneurs. Fain scholars may receive up to a total of $5,000.  View eligibility requirements and apply here.

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"

We are excited to share that our undergraduate students, Rahul Bulusu and Lareb Khan, won two First Places in the Engineering and Computing division poster presentations at USC Discover 2023 for their works.

Rahul works with Dr. Sanjib Sur, and Lareb works with Dr. Ramtin Zand.

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. 

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.

Dr. Sanjib Sur has been awarded the USC Breakthrough Star award which honors early career research faculty.

Sanjib Sur first became interested in millimeter-wave — a band of radio frequencies that enables high-speed broadband access — because of its potential to bring low-cost wireless connectivity to underserved populations. Since joining USC in 2018, that interest has persisted. Today, Sur is working on designing next-generation wireless network architectures and ubiquitous sensing techniques that make smart objects truly smart. 

Read the full article here.

The iCAS lab, directed by Dr. Ramtin Zand, has received recognition as a recipient of the ZPRIZE competition's Open Division award for "Accelerating Number Theoretic Transform (NTT) Operations on an FPGA." Only two academic labs were amongst the awardees with iCAS being the only one based in the US.

Congratulations to iCAS's graduate students, Mohammed Elbtity and Joseph Lindsay, for their leadership in hardware and algorithm development, and Peyton Chandarana and Mohammadreza Mohammadi, for their supporting contributions to the project.

We are proud to announce that Dr Qi Zhang has been awarded an NSF CAREER Award for his project titled "Identifying and Exploiting Multi-Agent Symmetries". The project's abstract:

It is widely believed by scientists that our universe follows certain symmetry patterns and principles, which lead to profound implications such as conservation laws. Artificial intelligence (AI) can and has already benefited tremendously from exploiting these symmetries. This project seeks to identify and exploit symmetries that are prevalent in cooperative AI tasks, where a group of multiple autonomous sequential decision makers, or agents, plan and learn to maximize their combined benefit. As an example, consider the application of adaptive traffic signal control, where each intersection can be modeled as an agent controlling its traffic signal in a way that adapts to real-time traffic conditions to reduce congestion. There exist certain symmetries when the topology of the road network is regular, e.g., as a 4-connected grid, and the road condition is uniform. When done properly, such multi-agent symmetries can be identified and exploited to greatly improve the efficiency and effectiveness of the current solutions to cooperative AI. This project also integrates the proposed research into an array of education initiatives, playing key roles in the curriculum development and undergraduate research experiences at the PI's university, as well as outreach activities that bridge academia with industry practitioners and community stakeholders.