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CSE Faculty Research Awards

We report that six of our faculty members have received research awards. They are:

  • Yan Tong from Office of Naval Research (ONR)/DOD for "Reliable Perception for Unmanned Maritime Systems"
  • Jason Bakos from Savannah River National Lab/DOE for "A Unified Machine Learning Framework for Corrosion Surveillance"
  • Amit Sheth 
    • from BMW for "Proactive and Automated Material Control -- BMW" Co-PI Forest Agostinelli
    • from SC Department of Commerce for "Proactive and Automated Material Control -- SC Dept of Commerce" Co-PI Forest Agostinelli
    • from College of Charleston/NASA EPSCoR for "Augmenting Physics-Based Design and Multi-Physics Based Manufacturing with Data Driven Models to Manufacture Advanced Composites Structures with Automated Fiber Placement"
  • Srihari Nelakuditi from NSF for "REU Supplement for MRI: Acquisition of Omnipercipient Chamber for Gathering Ground Truth and Enabling Research on Smart and Connected Things"
  • Homay Valafar from Pennington Biomedical Research Center/Louisiana State University for "The Smartwatch Pilot Project"

Dr Sheth Ranked in Top Computer Scientists in the World

We would like to congratulate Dr. Amit Sheth. He was recently ranked by as one of the Top Computer Scientists in the world. More specifically, he was ranked:

  • #80 in World
  • #50 in the U.S.

with a 111 H-Index, 47,049 citations, and 581 publications.

For context, Amit was ranked close to notable Computer Scientists such as Turing Award winner Yan Lecun (#76, #46) and Co-Director of Stanford’s Human AI Institute Li Fei-Fei (#74, #45)

Congratulations to Amit for this well-deserved recognition. We are proud to have one of the world’s Top Computer Scientists in the CSE Department and leading the UofSC AI Institute.

Dr. Sur Receives NSF Career Award

We are proud to announce that Dr. Sanjib Sur has received an NSF Career Award for his project titled "Vision and Learning Augmented D-Band Networking and Imaging".

This project aims to enable the practical adoption of D-band mmWave networks and applications by solving the fundamental challenges in deployment, link adaptation, coordination, and unified networking-imaging. Specifically, the project explores an optical vision and deep learning augmented paradigm by thoroughly understanding the physical properties of the D-band channel, building measurement-driven empirical and learning models, and designing practical, real-time systems. Successful execution of this project would enable the following. (1) A framework for optimal deployment and a “what-if” analysis tool to help optimize the cost and benefits of D-band deployment in both indoor and outdoor environments. (2) Link adaptation and coordination protocols that significantly minimize latency and maximize throughput and efficiency for scalable D-band networking. (3) A unified networking-imaging protocol that reduces disruptions to the throughput and latency and overcomes challenges with the channel specularity to enable high-resolution D-band images. The project will design, build, and empirically validate the proposed systems in a D-band testbed, and th


Dr. Zeng Receives NSF Career Award

We are proud to announce that Dr. Qiang Zeng has received an NSF Career Award for his project titled "Towards Secure and Usable IoT Authentication Under Constraints".

The project seeks to improve IoT authentication and deliver novel approaches, algorithms, techniques, and systems through the following thrusts. Thrust 1: Authentication for UI-Constrained Devices. A protocol that supports mutual authentication, over an insecure wireless channel, to establish trust between a UI-constrained device and the user to support authentication for heterogeneous IoT devices. Thrust 2: Authentication for Distance-Constrained Devices. A highly usable approach enables secure authentication between an IoT device and the user even when they are multiple meters apart, which has applications ranging from drone delivery to ride sharing. Thrust 3: Authentication for Operation-Constrained Devices. For traditional objects retrofitted with zero-UI sensor nodes, AI-assisted implicit authentication enables recognizing a user without requiring any explicit authentication operations. In sum, the research seeks to substantially advance IoT authentication and foster a variety of IoT applications.


Magellan Scholars: Spring 2022

We congratulate the following Computer Science/Engineering undergraduate students for receiving a Magellan Scholar Award for Spring 2022.

  • Ian McDowell and Rahul Bulusu with the project "Drone-based Multimodal Surveying for Outdoor 5G Millimeter-Wave Picocell Placement"
  • Cassidy Carter for "Detection and discovery of structural motifs in crystal materials using quotient graphs"
  • James Seekings for "Attention Tracking for Intuitive Robot Tutors using Neuromorphic Computing"
  • Edward Sitar for "5G Millimeter-Wave Enabled At-Home Human Silhouette Estimation"
  • Corinne Smith for "A network of UAV deployable sensor packages for monitoring hydraulic parameters during severe weather events"
  • Lexington Whalen for "The Wordification Project"

Dr. Tong, Dr. Huang and Dr. Cole Receive Research Awards

We are to announce the following research awards received by CSE department faculty:

Dr. Yan Tong received an award from Clemson University/SCRA for the project "Modernizing South Carolina Manufacturing Assets to Enable Industry 4.0"

Dr. Chin-Tser Huang received an award from Clemson/USDOT for the project "A Machine Learning-Assisted Framework for Determination of Performance Degradation Causes and Selection of Channel Switching Strategy in Vehicular Networks"

Dr. Casey Cole received an award from the US Department of Education (USDE) for the project "University of South Carolina – Transition to Teaching Residency"

Dr Homay Valafar Receives Bioinformatics Research Awards

Dr. Homay Valafar has received the following research awards:

  • “South Carolina IDeA Networks of Biomedical Research Excellence (SC INBRE) - Bioinformatics Core (BIPP) - Year 2 of 5”  from the National Institute of General Medical Sciences (NIGMS)/NIH
  • “Targeting important behaviors for weight loss through the use of social gaming and points: The Social Pounds Off Digitally (Social POD) study” from the National Institute of Diabetes & Digestive & Kidney Diseases (NIDDK)/NIH.

Dr Amit Sheth Receives Research Awards

Dr. Amit Sheth has received the following research awards:

  • "RII Track 2 FEC: Enabling Factory to Factory (F2F) Networking for Future Manufacturing" from the National Science Foundation (NSF)
  • "Actionable Sensemaking Tools for Curating and Authenticating Information in the Presence of Misinformation during Crises" from Ohio State University (OSU)/NSF
  • "Improving mosquito control methodologies through development of technology-driven traps and artificial intelligence guided detection of mosquito breeding habitats" from the National Institute of Allergy & Infectious Diseases.

New Faculty: Vignesh Narayanan

We would like to welcome Dr. Vignesh Narayanan as a new Assistant Professor to our Computer Science and Engineering department. He received his Ph.D. in Electrical Engineering from Missouri University of Science and Technology (2017), a Control Systems from the National Institute of Technology, Kurukshetra, India (2014) and a B.Tech. Electrical and Electronics Engineering, SASTRA University, India, (2012).

His research is in the areas of dynamical systems and networks, data science and learning theory, and computational neuroscience. Visit his homepage to learn more.

New Faculty: Christian O’Reilly

We welcome Dr. Christian O’Reilly as a new Assistant Professor to our Computer Science and Engineering department. Dr. O'Reilly received his B.Ing (electrical eng.; 2007), his M.Sc.A. (biomedical eng.; 2011), and his Ph.D. (biomedical eng.; 2012) from the École Polytechnique de Montréal.

His main interests are related to better understanding the brain across spatial and temporal scales in order to address complex neurodevelopmental issues such as autism and other neurodevelopmental disorders. The methods he uses include analytical techniques (e.g., EEG source reconstruction, functional connectivity) and modeling (e.g., point neurons, morphologically-detailed neurons, neural masses), as well as the combination of these two approaches through Bayesian model-driven analyses. He is further interested in novel ways to empower the study of neuroscience through AI and to empower AI through biologically inspired neural networks

MaterialsAtlas: A Toolbox for Materials Discovery from UofSC

The availability and easy access of large scale experimental and computational materials data have enabled the emergence of accelerated development of algorithms and models for materials property prediction, structure prediction, and generative design of materials. However, lack of user-friendly materials informatics web servers has severely constrained the wide adoption of such tools in the daily practice of materials screening, tinkering, and design space exploration by materials scientists. Herein Dr. Jianjun Hu's team developed, a web based materials informatics toolbox for materials discovery, which includes a variety of routinely needed tools for exploratory materials discovery, including materials composition and structure check (e.g. for neutrality, electronegativity balance, dynamic stability, Pauling rules), materials property prediction (e.g. band gap, elastic moduli, hardness, thermal conductivity), and search for hypothetical materials, and fool-proof machine learning of user-specified datasets.  These user-friendly tools can be freely accessed at This materials informatics apps will greatly ease the pains in exploratory materials discovery.