REU 2021

I am a senior working on my Bachelors in Computer Science at the University of Central Florida. I had little knowledge about machine learning and 2021 REU has been a significant experience that has increase my understanding and skills in the subject. I am interested in learning about and advancing computer science as a whole and this opportunity has given me the confidence to further pursue my goals. I am working with Alec Kerrigan on zero-shot action recognition. Zero-shot learning is fundamental to human intelligence and creating a computer model with this capability is a challenging goal. For more information on the project view the available presentations. To learn more about my insights on this topic feel to contact me at: brown169@knights.ucf.edu.

I am a second year student at the University of Arizona double majoring in Computer Science and Mathematics. My main computer science interests are Artificial Intelligence and Machine Learning, so I was very excited to participate in this REU. Over the course of the summer, I worked with Dr. Mitchell Hill on using Transformers to build convergent Energy Based Models. I hope to continue working on research projects during my undergraduate and to do a PhD in Machine Learning after I graduate. My progress is documented in my weekly presentations as well as my report and poster. If you have any questions, you can contact me at chuchen@email.arizona.edu.

I am a rising senior at the College of the Holy Cross majoring in computer science and psychology. This REU has given me the opportunity to explore my interests while introducing me to machine learning. This summer I worked with Shiza Ali, Dr. Gianluca Stringhini, and Dr. Pamela Wisniewski. We focused on object and text recognition in images shared over private Instagram conversations with the goal of automatically detecting risky content. My progress is documented in my weekly presentations and report. Please feel free to email me at tpconr22@g.holycross.edu with any questions.

I am a Rising Senior at Illinois Institute of Technology majoring in Artificial Intelligence and double minoring in Applied Mathematics and Statistics. I decided to participate in this REU to learn more about research in Computer Vision and the opportunities it provides in Academia and Industry. My interest in Artificial Intelligence is tailored towards Computer Vision and its applications in areas such as Autonomous Driving and Sports. This summer, I worked alongside Ph.D. student Aakash Kumar on a 3D Multi Object Tracking using Lidar Data project. This project is specific towards Autonomous Driving Applications as it specializes in the KITTI dataset. You can look through my presentations to track my progress and assess my work, if you have any queries, feel free to contact me at zfarhat@hawk.iit.edu.

I am a rising junior at the University of Central Florida majoring in Computer Science and minoring in Intelligent Robotic Systems. The REU has been an incredible introduction to many aspects of the field of computer science. I am learning both the basics and even a few advanced topics in computer vision and machine learning and have worked on many skills necessary to being successful in a computer science career. Over the summer I am working with my mentor James Beetham on a project utilizing adversarial attacks and GANs to change an image's contents without changing the model classification. Our goal is to change the way a human classifies an image without changing how the model classifies the image. If this sounds interesting, feel free to check out my weekly presentations below or email me at leahhowells@knights.ucf.edu with any questions. Thank you!

I am a rising sophomore at the University of Wisconsin-Madison majoring in Computer Science and Music. I had never touched machine learning before this summer, but the REU provided an engaging experience that has immersed me in the field as well as computer science research as a whole. I am working with Swetha Sirnam to develop a model that can classify complex activities in videos using few-shot learning. Few-shot learning is an important development in recent years given that it is aimed towards reducing the amount of data that is necessary to train a model, and its application towards classifying long-term human activity is very interesting, if not promising. For more detailed information, you may refer to the available presentations and report. For further inquiry, please feel free to reach out to me at iskoh2000@gmail.com.

I am a fourth year student from the University of Virginia. In a departure from my previous focus on business, I am now majoring in Computer Science. While I have lots of experience in the fundamentals of computer science, this REU has been a highly immersive dive into a new realm of computing. At the start of the program, I had a very high level understanding of computer vision and quickly learned much more. Over the summer, I have been working with Jyoti Kini to integrate point cloud data with a tracking and detection model. Point cloud data is information gathered from a LiDaR camera that is able to create a 3d map of its surroundings by calculating the time light pulses take to return to the sensor. Our ultimate goal is to create a model that takes in point cloud data and is able track and detect movement as though it is an RGB image. Understanding how to use point cloud data is challenging, however, the models will be essential in many applications such as self driving cars and much more. If you are interested in looking further into the topic, please consult my presentations and final report. If you have any questions, or simply would appreciate my personal insight, don’t hesitate to contact me to rjl4sw@virginia.edu.

I am a senior student from University of Minnesota - Twin Cities, pursuing B.S in Computer Science. My plan is to achieve a Master Degree in AI. This REU program helped me to explore my interest in research related to artificial intellgence and machine learning. This summer, I worked with Praveen Tirupattur and Dr. Shah on "Future Action Prediction". This project is a challenging task, and is important in many applications such as self-driving and robot action planning. The goal of this project is to predict the actions in the future by observing a part of the video. Feel free to contact me at ml.123456789@hotmail.com about anything related to this project or me.

I am a rising senior studying Computer Engineering at the University of Central Florida. Over the course of the summer this REU has provided me with an incredible opportunity to learn in depth about machine learning, a topic which has always fascinated me, and to learn more about the academic research process. During the REU, I worked with Dr. Navid Kardan to investigate ways in which to train a single robust classifier to achieve strong results for 4 different tasks: image synthesis, image inpainting, image-to-image translations, and super-resolution. More details can be found in my weekly progress reports posted below. If you have any additional questions, please feel free to contact me at brianmod115@gmail.com.

I am a rising junior at the University of Central Florida’s Burnett Honors College, majoring in Computer Engineering. While I have worked on hobby-scale projects in the past, this summer has been my first immersive experience in the field of machine learning. This REU has significantly increased my understanding of computer vision and has given me valuable experience in applying these concepts. With the assistance of Dr. Shah and my mentor, Ishan Dave, I have worked to improve the performance of existing action recognition models when trained on repetition counting video datasets. To do this, we developed a new loss function to take advantage of the count information in these sets. For more information, check out my weekly presentations and final report below. Please feel free to contact me at thomase@knights.ucf.edu with any questions.