"The project aims to address the unique challenges of sensing and networking in underground mining environments by employing millimeter-wave (mmWave) wireless, a core technology for 5G and beyond standards. This technology is particularly suited for the harsh conditions of underground mines, such as dust and low light or dark conditions. However, the adoption of mmWave technology in mining is challenging due to reconstructing high-quality 3D maps in complex structures, fusing static and mobile underground real-time maps, and deploying mmWave communication infrastructures. By overcoming these challenges, this project seeks to enhance safety in mining operations, improve operational efficiency through better resource management, navigation, and machinery positioning, and contribute to the national interest by advancing the future of autonomous mining systems."
We are delighted to share with you that Hem Regmi, a PhD student of Sanjib Sur, has won this year's C.C. Royal Fellowship, one of the Trustee Fellowships from the Graduate School. The competition for these fellowships is fierce, and this is an amazing achievement for both Hem and Sanjib.
We are happy to announce that Dr. Jamshidi, A. Ahmad, and C. Pahl were recipients of a Most Influental Paper Award at the 9th International Symposium of Software Engineering for Adaptive and Self-Managing Systems for their paper "Autonomic Resource Provisioning for Cloud-Based Software."
We are proud to announce that Lex Whalen has been awarded the NSF Graduate Research Fellowship (GRFP). The GRFP is a prestigious award that recognizes and supports outstanding graduate students who have demonstrated the potential to be high achieving scientists and engineers, early in their careers.
1st place: Poster #22. Flex-TPU: A Flexible TPU Architecture with Runtime Reconfigurable Dataflow Presenter: Peyton Chandarana
2nd place: Poster #2. Rethinking Robust Contrastive Learning from the Adversarial Perspective Presenter: Fatemeh Ghofrani
3rd place: Poster #4. MilliCar: Accurate 3D Bounding Box Prediction of Vehicles and Pedestrians in All Weather Conditions Presenter: Reza Tavasoli; Hem Regmi
Katelyn Wyandt has been awarded the prestigious Goldwater scholarship. More than 400 higher education institutions nominate up to four students each academic year for the $7,500 awards meant to encourage undergraduate students to pursue research careers in natural sciences, engineering and mathematics. Katelyn is an Honor's College student and a junior computer science major from Summerville, South Carolina. She as been conducting research since she was a freshman at USC. Read the full article here.
Starting this Fall 2024 the CS Application Area Requirement, and the CS and CIS Liberal Arts Requirements are being replaced by a more relaxed "Electives" requirement. Any USC course can be used to satisfy the new Electives requirement, including CSCE courses (check out CSCE 180: "Artificial Intelligence for All" this Fall) Also, the total number of credits required for a degree has been reduced for the majority of students. The set of required CSCE courses remains the same. See the new CS Major Requirements and CIS Major Requirements for details.
It starts Fall 2024, so only applies to those graduating in December 2024 or later. You can switch to the new 2024 requirements if you want. Just ask your Advisor to do it. It will mean you have more freedom with your electives and will need fewer or the same number of credits to graduate.
Yuxin Zi, Kaushik Roy, Vignesh Narayanan, and Amit Sheth presented their paper titled "Exploring Alternative Approaches to Language Modeling for Learning from Data and Knowledge"
Kanak Raj, Kaushik Roy, Vamshi Bonagiri, Priyanshul Govil and Krishnaprasad Thirunarayanan: "K-PERM: Personalized Response Generation Using Dynamic Knowledge Retrieval and Persona-Adaptive Queries".
Kaushik Roy, Alessandro Oltramari, Yuxin Zi, Chathurangi Shyalika, Vignesh Narayanan and Amit Sheth: "Causal Event Graph-Guided Language-based Spatiotemporal Question Answering"
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.
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.
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.
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:
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.
Jessica Bradshaw and Caitlin Hudac in the Department of Psychology are collaborating with Christian O’Reilly, a computer science and engineering faculty member, to search for potential patterns and markers of ASD and more. Read the full article here.