Computer Science and Computer Engineering students are hard at work to become the next generation of engineers who make an impact on Arkansas and the world!
Computer Science and Computer Engineering students are hard at work to become the next generation of engineers who make an impact on Arkansas and the world!
CSCE Undergraduate Electives for Fall 2021
Descriptions for electives can be found on the CSCE Undergraduate Courses page.
CSCE 4123 – Programming Challenges – Dr. Wing Ning Li
CSCE 4143 – Data Mining – Dr. Xintao Wu
CSCE 4273 - Big Data Analytics and Management - Dr. Justin Zhan - Introduction to the tools and techniques for distributed data computing and management, big data analytics, scalable machine learning, and real-time streaming data analysis. Students cannot receive credit for both CSCE 4273 and CSCE 5273. Prerequisites: CSCE 3193 - Programming Paradigms or DASC 2103 - Data Structures & Algorithms.
CSCE 4333/5223 – Introduction to Integrated Circuit Design – Dr. Zhong Chen. Cross-listed with CSCE 5223.
CSCE 4553 – Information Retrieval – Dr. Susan Gauch
CSCE 4613 – Artificial Intelligence – Dr. Khoa Luu
CSCE 4623 – Mobile Programming – Dr. Alexander Nelson
CSCE 4783 – Cloud Computing and Security – Dr. Miaoqing Huang
CSCE Graduate Special Topics Classes and Electives for Fall 2021
CSCE 5013-003 - Advanced Special Topics: Post Moore's Law Comp. Arch. - Dr. David Andrews
The end of Dennard scaling and slowdown of Moore’s law has ushered in a new era called Post Moore’s Law Computing. This course will look at the trends, applications, and emerging architectures that are defining this new era. The course will look at how big data analytics and machine learning applications are driving innovation in large scale near memory architectures, domain specific accelerators, and neuromorphic computing. The course will also survey new proposed technologies that are emerging to augment and replace CMOS as our computing base. Course materials will be drawn from the literature. Students will be required to make presentations during the semester and submit a final project.
CSCE 5013-005 - Advanced Special Topics: Deep Learning - Dr. Thi Hoang Ngan Le
The course aims at understanding the fundamental of deep learning and its application in computer vision, natural language understanding and game theory. The course starts with basic multi-layer perceptron and then moves towards other complicated models such as convolutional neural networks, recurrent neural networks, attention, and generative adversarial network models. The course will end with deep reinforcement learning. The course provides required steps for building deep learning models. Prerequisite: CSCE Graduate Standing. Note: Student should have previous exposure to linear algebra (matrix multiplication, inversion, and eigenvectors), vector spaces (principal component analysis, vector distance), programming (Java, or Python, or C++), linux, and probability.
Decriptions for the following electives can be found on the CSCE Graduate Courses page.
CSCE 5063 – Machine Learning – Dr. Xintao Wu
CSCE 4333/5223 – Introduction to Integrated Circuit Design – Dr. Zhong Chen. Cross-listed with CSCE 4333.
CSCE 5323 – Computer Security – Dr. Dong "Kevin" Jin
CSCE 5333 – Computer Forensics – Dr. Brajendra Panda
CSCE 5533 – Advanced Information Retrieval – Dr. Susan Gauch
CSCE 5763 – Privacy Enhancing Technologies – Dr. Qinghua Li
NSF CyberCorps Scholarship Applications Now Being Accepted for Spring 2021
Sponsored by the National Science Foundation and managed by the Arkansas Security Research and Education (ASCENT) Institute, the UofA Scholarship for Service (SFS) program is now accepting applications from eligible undergraduate and graduate students in CSCE, INEG, and ELEG at UofA with the goal as developing a superior cybersecurity workforce. This program provides generous scholarships ($25,000 per year for undergraduate students and $34,000 per year for graduate students, plus the full amount of tuition and other educational allowance per year). Each scholarship recipient will need to agree to work at a government agency post-graduation for a period equal to the duration of the scholarship. For more information and application submission, please visit https://ascent.uark.edu/sfs/ The application is now closed.
What is Computer Science?
Computer scientists specialize in the software side of computing, focusing on writing new programs that allow computer applications to run faster and more efficiently. You might work for a security company, creating technology that reduces the risks of viruses and hackers, or develop flight simulation exercises that allow airline pilots to practice managing flight problems.
What is Computer Engineering?
Computer engineers deal with both software and hardware. As a computer engineer, you could design entire computer systems and networks, making sure that the hardware, or physical equipment, is capable of running the appropriate software. You might build devices such as retinal scanners that identify people by checking their eyes, or you could design computers that are incorporated into prosthetic devices to aide people with disabilities.
Those who continue onward to obtain a graduate degree in either computer science or computer engineering learn to advance the frontiers of science. With an MS or PhD, you will invent the new technologies that enable the next generation of software and computing devices.
To learn more about Computer Science check out the links below from ComputerScience.org:
Computer Science Programs in Arkansas
Student News
Student Startup MORE Technologies Closes Acquisition Deal With Sphero
From left, the MORE Technologies team, Rex Hearn, Kaushik Ramini, Canon Reeves and Peyton Smith.
FAYETTEVILLE, Ark. – MORE Technologies, a startup company founded by four University of Arkansas students specializing in the sale of 3-D printable robots, recently sold its technology assets and patent to Sphero, a company based in Boulder, Colorado, that makes programmable robots and educational tools based in science, technology, engineering, arts and mathematics fields — or the STEAM fields.
MORE Technologies — the acronym stands for Modular Open-source Robotics Ecosystem — was the brainchild of Canon Reeves, company CEO and U of A undergraduate in computer science. Read More
Top Stories
CSCE Assistant Professor Yarui Peng Receives the Prestigious NSF CAREER Award to Study
Design Automation Tools for Heterogeneous Multi-Chiplet Systems
Yarui Peng, assistant professor of computer science and computer engineering, has received the NSF Faculty Early Career Development Award in 2021, known as a CAREER award. NSF describes the CAREER Award as its most prestigious award in support of early-career faculty who have the potential to serve as academic role models in research and education and to lead advances in the mission of their department and organization. Read More
Di Appointed to Lead Computer Science and Computer Engineering
Jia Di (left) will become head of the Department of Computer Science and Computer Engineering Jan. 1. Dale Thompson (right) has served as interim department head since July.
Dec. 14, 2020 - Professor Jia Di has been chosen to lead the Department of Computer Science and Computer Engineering.
The department is the largest in the College of Engineering, with more than 600 undergraduate students enrolled.
Di succeeds Xiaoqing "Frank" Liu, who departed in July to become dean of engineering at Southern Illinois University.
Di has been a faculty member in the Department of Computer Science and Computer Engineering since 2004 and holds the Twenty-First Century Research Leadership Chair. He is internationally recognized for his research in asynchronous integrated circuit design and hardware security. Di holds six patents and is a senior member of the Institute of Electrical and Electronics Engineers, an elected member of the National Academy of Inventors, and an eminent member of Tau Beta Pi. Read More
Data Science Professor Receives $1.25 Million from Department of Defense
Oct. 08, 2020
FAYETTEVILLE, Ark. - A $1.25 million grant from the Department of Defense will enable data science researcher Justin Zhan to develop novel algorithms to enhance the speed and efficiency of computational software that uses large amounts of streaming data.
By harnessing big data analytics faster and more efficiently, the algorithms will significantly enhance computational performance of many applications and programs that require massive amounts of streaming data. This so-called machine-learning approach to big data analytics will improve operational robustness, in addition computational speed and efficiency. Read More
facts
The U of A is among universities with the highest level of research activity
Engineering was an early focus of the university
Fayetteville, AR is the fourth best place to live
News
Arkansas Researchers Developing Prediction Models for Coronavirus
Fayetteville, Ark. - Data Science professor Justin Zhan is collaborating with University of Arkansas for Medical Sciences professors David Ussery and Xuming Zhang to develp accurate predictions of genomic variation trends of coronavirus.
Their work will help public health officials monitor the outbreak and adapt to changes. It could also provide valuable information for the deisgn of the vaccine.
"To control and prevent COVID-19, public officials need highly robust models for predicting how and where the virus will spread," Zhan said. "This project will assist that effort and lead to better detection and prevention strategies. We think it could have colassal social and economic impacts."
Zhan's research focuses on big data, blockchain technologies, information assurance, and biomedical informatics. For this project, he will use a novel, blockchain-based artificial intelligence system, which integrates information on the relationships of biological systems to predict trends and changes as the coronavirus spreads. The system will be evaluated and tested through various coronavirus benchmark datasets.
Ussery and Zhang will provide expertise in the areas of bioinformatics, microbiology, and immunology.
A blockchain is a growing list of records, called blocks, that are linked using cryptography. Each block contains a cryptographic of the previous block, and timestamp, and transaction data generally represented as a Merkle tree. By design, a blockchain is resistant to modification of the data. It is "an open, distributed ledger that can record transactions efficiently and in a verifiable and permanent way." As the fundamental component and functional element of blockchains, Merle trees allow for efficient and secure verification of large data structures and potentially boundless data sets.
With a large grant from the Army Research Office, Zhan in building and graphics processing unit at the U of A. The unit is a computer cluster of big data research and eduction.
Justin Zhan and David Ussery are both Arkansas Research Alliance scholars.
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