Why are we doing this?

• We want to encourage our Undergraduate Students to participate in research as early as possible. So, we are looking for Sophomore and Junior students.
• To you, this may be your first exposure to research! You can learn interesting techniques and get to know another career/education path!

Words from previous students:

• Alexander Palmer (Spring 2023): Over the Spring '23 I worked with Dr Saule and did Research on Enabling Adoption of High-Performance Centrality Tools. This research has helped me with my career and graduate school expectations. More recently this research has also helped me with my summer internship and to get a full-time job offer upon graduation. During intern, I worked on a team creating a new metadata search engine. We used research papers to implement new functions in our product. The research and one on one mentoring by Dr Saule helped me to take the lead on my internship project and really outline goals and objectives for myself. I was able to confidently complete the product within 10 weeks and earn a Full-time offer. I will also be applying to the early entry program for next semester.
• Sumi Verma (Spring 2023): Joining the URI program at UNCC gave me a fantastic opportunity to dive into research. Before URI, I had a strong curiosity about research and even tried reaching out to professors, but was unable to find the right fit. The URI program changed that by connecting me with a dedicated mentor and introducing me to a community of other UNCC students equally passionate about research. Through the program, I got involved in a project called “Machine Learning-Based Parameter Ranking in HPC I/O Stack”, which I presented at UNCC’s undergraduate research conference. Joining URI was invaluable- it gave me a firsthand exposure of research, helped me learn more about exciting technologies, and grew my coding skills. Thanks to this experience, I’m continuing my research activities and am planning on pursuing a master’s degree.
• ...

Previous achievements:

In 2023 Spring, we received over 60 applicants and accepted 14 students. After a semester's work, we have achieved a lot:

• 5 of our students are selected into OUR Summer Research Scholar Program during 2023 Summer.
• One student is selected as SC23 student volunteer.
• One student is accepted into SC23 immersion program.
• One student accepted to SC’23 Student Research Competition (SRC) and a SC'23 workshop paper (PMBS’23).
• Four students were hired as Research Assistant (RA) during 2023 Summer.
• Three students returned as Research Assistant (RA) in 2023 Fall.
• Two students continue their research via ITCS4990 independent study or capstone course.

How to get involve for Spring 2024?

• Spend 5-mins to fill this Google Form to apply, (Deadline Oct. 31st).
• Attend one of the in-person info sessions at Woodward Hall 237 on Nov 1st 12:00pm - 1:00pm or Nov 3rd from 12:00pm-1:00pm. (Must Attend)
• We will contact you within 1-2 weeks to learn more about your background and interests.
• We will register you in Course ITCS 3050 in Spring 2024 for the program.

Important: Due to the limited resources, we will have to select attendees from the applicants. We will do this as soon as possible. But, please be aware of this and make sure you register enough courses for Spring 2024. Once you are selected, you can swap one to ITCS3050.

Who are the mentors? (check their research interests!)

	Dr. Tyler Allen is an Assistant Professor of Computer Science in the UNC Charlotte College of Computing and Informatics. His research focuses on enabling new capabilities for High Performance Computing (HPC) systems using architecture-focused applications, as well as making HPC systems more accessible through development and optimization of systems technology.
	Dr. Dong Dai is an Assistant Professor in the Department of Computer Science at UNC Charlotte. He works in optimizing and designing intelligent infrastructure for high-performance data-intensive systems, such as parallel file systems, metadata management, graph storage, and resource management.
	Dr. Siddharth Krishnan an Assistant Professor in the Department of Computer Science at the University of North Carolina at Charlotte. He is broadly interested in web-mining, data analytics, computational social science, and applied machine learning with a primary emphasis on analyzing, characterizing, and forecasting information (news, rumors, memes, advertisements, etc.) dynamics on online social networks & social media.
	Dr. Aidong Lu is a Professor in the Department of Computer Science. Her research interests are visualization, mixed reality, intelligent systems, and applied machine learning. Her recent work funded by NSF focuses on new augmentation technology with interdisciplinary research to improve users performance in diverse environments, such as better sensemaking for visual analytics and effective operations for first responders.
	Dr. Harini Ramaprasad is a Teaching Full Professor in the Department of Computer Science and the Director of Undergraduate Programs in the College of Computing and Informatics of the University of North Carolina at Charlotte. Her research interests are in the areas of real-time/embedded systems, cyber-physical systems, operating systems and Computer Science education.
	Dr. Erik Saule is Associate Professor at the University of North Carolina at Charlotte in the department of Computer Science. He is particular interested in student willing to work in graph algorithms, cluster computing, accelerators and middleware for HPC.
	Dr. Meera Sridhar is an Associate Professor in the Department of Software and Information Systems at UNC Charlotte. Her research interests span language-based and systems security, formal methods, and their application to web, mobile and Internet-of-Things security.
	Dr. Hongfei Xue is an Assistant Professor of Department of Computer Science at the University of North Carolina at Charlotte. His research interests lie in the intersection of Internet of Things and Artificial Intelligence, with an emphasis on building intelligent wireless sensing systems. Here is a real-time video demon related to his current research projects.
	Dr. Yonghong Yan is an Associate Professor at the University of North Carolina at Charlotte, Department of Computer Science. His research interest are broad in the system area of computer science, with focus on parallel and high performance computing, parallel programming model and compiler techniques, computer architecture and systems.

How will the class go?

• First 1-2 Weeks: Faculty members and Ph.D. students introduce the projects. Students match with projects.
• You will talk with TA biweekly to sync and complain.
• There will be occasional sessions to talk about specific topics, such as How to use terminal; How to read a paper; How to prepare a poster.
• Flexible class location, but Fixed Time.
• Outcome of these projects include software artifacts and potential publications, which can be listed in your CV.
• Last 1-2 Weeks: There will be a poster/presentation session at the end of the semester for CS Research Day (Fall) or the Undergraduate Research Conference (URC, Spring).

Other Q&A

• What is the weekly workload for this course? The workload is self-paced and similar to a typical 3 credit hour course. This means that you should be prepared to meet with your mentor at least once a week for 30 minutes. Afterwards, you should expect to spend between 9 and 15 hours a week working on your course project. Research progress is hard to predict, so it is important to have sufficient time to dedicate towards your project to get your expected outcome.
• What is the final exam for this course? There will be a poster/presentation session at the end of the semester that serves as your final exam. However, this is intended to be a fun opportunity to share your progress with others, and not an intense examination session.
• Will the students get the chance to learn about relevant concepts before starting the project? Yes, doing the project itself includes learning phase at beginning.

What are the Research Projects?

The projects change every semester. Here are some examples:

• Project 1: Transforming Large-Scale Data Processing!
• Project 2: Scheduling Highly-Parallel Data Accesses!
• Project 3: Analysis and Visualization of Execution Tracing of Parallel Program!
• Project 4: Parallel Programming Models and Compiler based on OpenMP!
• Project 5: Medical image processing using ML/DL!
• Project 6: Visualization Site for Job Trace Analysis!