The Ubiquitous Computer…
And We Can’t Live Without It!
The computer has always been at the forefront of science. From its earliest iterations that required huge rooms to store and operate to the minis we wear on our wrists, it’s all about science. At LTU, the science of computers involves the study of their theoretical and algorithmic foundations, and their application to processing information, data structures, computer and network design, modeling data and information processes, and artificial intelligence. Dr. Patrick Nelson, chair of the Mathematics and Computer Science Department, explained that “the field of computer science is changing so fast that what used to be defined simply as ‘computer science’ has evolved into numerous, next generation, disciplines. For example, artificial intelligence (AI) and data science are now focused, stand-alone concentrations of study.” AI is now the tool everybody can use in their disciplines. Data science, a combination of math, statistics, and computer science, is a bridge between many of the applied sciences.
“In today’s world, there’s an infinite amount of data that needs to be analyzed correctly. People have heard of ‘big data’ and that’s exactly what it is: the human genome project, real-time medical information allowing doctors to make modifications during surgery, drug efficacy, you name it. It all has to be analyzed accurately to be of benefit to society.”
Housed in the College of Arts and Sciences at LTU, which is focused on teaching both foundations and applications, computer science targets the behind-the-scenes of how computers work. He added, “Our program is heavily math-based, a basic discipline. But we give our students unique opportunities to learn how to collaborate with one another and with faculty from day one. Ours is a small department but our faculty are top-notch, very dedicated to every student’s success, so students don’t get lost at LTU.”
In teaching this core discipline, CRE is embedded in computer science courses (See CRE story in this edition). Research is taught while professors teach the various applications. Computer science doesn’t pigeonhole a student into one kind of job. All industries, all institutions need computer science to run. It’s one of the top five careers forecasted over the next ten years. Nelson projected that “we’ll need tens of thousands of students to learn this work.”
As a matter of fact, LTU is continuously adapting its curriculum to be at the forefront of change. “We’re entering a new generation where computer science will be driving future innovation so we’re modernizing our curriculum to meet the needs of our students and employers,” Nelson said.
LTU offers an exciting and fascinating array of computer science concentrations. For their Bachelor of Science degree in Computer Science, students can select from Artificial Intelligence, Business Software Development, Cybersecurity, Game Software Development, Scientific Software Development, and Software Engineering. Master’s level degrees are available in Artificial Intelligence and Computer Science with concentrations available in Intelligent Systems, Distributed System, Data Science & Big Data, Cybersecurity, Database Systems, and Web Software Engineering.
Dr. Ghassan Azar is former College Professor and Associate Chair of Math and Computer Science. He described the many uses of Artificial Intelligence (AI), which is a joint program of LTU’s College of Arts and Sciences and College of Engineering. AI is applied to every facet of our lives. He shared an example of its potential impact on better and more correct diagnoses of mental health disorders. Azar and Master of Science in Computer Science graduate student Sonali Dilip Runwal worked on a study titled “Intelligent Mental Health Diagnosis Architecture using Data Mining and Machine Learning.” Runwal explained that therapists only used five of the 200 possible disorders listed in the Diagnostic Statistical Manual IV to describe the mental health condition of their client or patient. “Misdiagnosis can be fatal to the patient,” she said. We wrote algorithms and “mined” the data collected from real-life cases to identify additional usable diagnoses that therapists can use to more accurately describe their patients’ condition.”
TABLE OF CONTENTS
HUMANITIES, SOCIAL SCIENCES, + COMMUNICATION
Arts + Sciences
Math and Computer Science
Among the exciting subsets of Artificial Intelligence is robotics. Dr. Chan-Jin (CJ) Chung, professor of Computer Science, Director of CS Robotics Labs, and founder of Robofest, explained that he uses robotics to teach many subjects related to STEAM (Science, Technology, Engineering, Arts, Mathematics), including basic programming skills.
Because they’re really computers, we think of robots as 20th century phenomena. “Although the science of robotics only came about in the 20th century,” says thomasnet.com, “the history of robots and human-invented automation has a much lengthier past. In fact, the ancient Greek engineer Hero of Alexandria produced two texts, Pneumatica and Automata, that testify to the existence of hundreds of different kinds of “wonder” machines capable of automated movement. Of course, the evolution of robots in the 20th and 21st centuries has advanced radically to include machines capable of assembling other machines and even robots that can be mistaken for human beings.”
The word “Robotics” came from a 1941 science fiction short story by author Isaac Asimov in the publication Astounding Science Fiction. But it’s not at all fiction to Chung and his students! Chung teaches courses in Intelligent Robotics and Deep Learning, which use the human brain as a model to solve problems. His students write computer programs for the robot to download and test their work. “In that way,” said Chung, “students can see the results immediately and can learn how to correct errors in the coding faster and better.”
An autonomous vehicle is a good example of a robot. All around the vehicle are sensors that collect data and act according to the data it collects. Chung and his students compete in the Intelligent Ground Vehicle International Competition. Preparing for this competition annually gives students a real learning opportunity. Chung says, “Robots motivate students. Robots are moving, are interactive, and students can learn more through robots because it’s hands-on, mind-on, and body-on learning!” Students also learn how to work as a team to produce their robotic vehicle. It’s also an avenue to develop leadership skills. Chung was awarded an NSF grant in February 2022 for undergraduate research projects in self-drive algorithms. His teaching of Robotics and engagement extends also to elementary and high school students, for whom he created Robofest in 1999 and which is hosted by LTU.
In recent years, cyber attacks have rocked the world of banking and credit cards, a state’s water system, and even the cyber world itself. LTU added Cybersecurity along with AI to the computer science curriculum in 2020. Dr. Tao Liu focuses on this “hot” field in a way that helps students learn the concept of cybersecurity as well as the mechanisms, the hardware and software. “We must learn the hardware and the coding to help us understand how to create defense systems,” Liu said. That’s the unique research that has captured Liu’s attention lately. He calls it “Full-Stack Machine Learning System Security Research.” He digs into the computer’s different layers to identify its potential weaknesses to build an effective defense accordingly.
Liu combines research with his teaching. In his CRE cybersecurity course, undergraduate students “use a real attack environment and then create ways to mitigate damage and build a defense against future attacks,” Liu described.
Assistant Professor Dr. Oriehi (Destiny) Anyaiwe’s approach to teaching might surprise some people but it honors the LTU motto of “Theory and Practice.“ “Teaching comes naturally to me,” he said. “And CRE is a type of teaching philosophy that works very well with my students, because as they’re learning the theory, they’re practicing. I like ‘practical.’”
He like to see students “fail!” “Of course, I don’t mean ‘fail’ the course, but ‘fail’ in the sense that if the program or a proposed solution doesn’t work, I like to see them sweat it out in finding the reason for the failure and how a working solution can be developed,” he explained.
"This is how we break new ground. When we break new ground, we can break old parameters and find new solutions. Students get a deeper examination of their area of study this way. They can sit down tomorrow and solve a problem because they know how to do the research to find out what happened and how to fix it."
Anyaiwe’s research interests include data science, machine learning and in general topics that improve the quality of life and health. He believes that “mathematics is fundamental” and computer scientists need to be able to express themselves mathematically. “Without math, it is difficult to write algorithms. My methodology,” he explained, “helps to learn how to code and get better and better at it.”
“[Students] can sit down tomorrow and solve a problem because they know how to do the research to find out what happened and how to fix it."
– Dr. Oriehi (Destiny) Anyaiwe
He believes that computer science helps to improve our world. There are pressing human problems that needs to be addressed. “Alzheimer’s Disease has no politics. There is no diagnostic methodology or ‘tool kit’ to diagnose this terrible disease. He and his co-researchers are “using saliva to identify and understand neurological activities and degradation in the brain. Does a person of 20, 40, 60 years old have a different saliva composition and is this a determinant?” he’s asking, “and can computer science and machine learning be used to figure that out?”
Sydney Ross and Kim Lam are two of Anyaiwe’s students, both enrolled in LTU’s 4 + 1 computer science program. In four and a half years, 4 + 1 students obtain both a BS and an MS in Computer Science.
Both students were enrolled in Anyaiwe’s Machine Learning and Pattern Recognition class for which they researched the accuracy of a set of “big data” concerning perfusion. Ross said, “I enjoyed learning different languages and seeing how each handled the data.” Lam agreed and added, “In research, it’s important to think out of the box. We broke the data into two groups, one to ‘train’ the model and the other to test the accuracy of the model.” Both students, who have entered the last semester of their 4 + 1 program, believe that these project-based projects indeed put theory to practice.
by Renée Ahee
Meet the Computer Science Professors
PhD in Applied Mathematics, University of Washington. Research interests: developing computer algorithms and web-based interfaces for Type 1 diabetes in the clinic, mathematical modeling of infectious diseases.
PhD in Electrical and Computer Engineering, MS in Computer Engineering, Florida International University, BS in Computer Science, Southeast University. Research interests: intersection of the algorithm, architecture, and security aspects of deep learning, neuromorphic computing, machine learning system design, and their applications in embedded, IoT, and autonomous systems.
Assistant Professor of Practice
PhD in Design Data Management, MS in Industrial & Management Systems Engineering, MS in Architectural Engineering, The Pennsylvania State University, University Park; BArch, Baghdad University. Teaching and research interests: application of machine learning and data mining techniques in various engineering disciplines, Web Technologies, Data Taxonomies and Ontologies, and Software Engineering.
PhD in Computer Science and Informatics, MSc in Computer Science, Oakland University; MSc in Mathematics, Nnamdi Azikiwe University; BSc in Mathematics, Delta State University; ABD in Applied Mathematics. Research interests: data science, machine learning, topics that improve the quality of life and health.
Professor, Director of CS Robotics Lab
PhD in Computer Science, Wayne State University, BS in Computer Science, Honglk University. Research interests: evolutionary computation, cultural algorithms, evolutionary-neuro-fuzzy algorithms, deep neural network learning, evolutionary robotics, robotics in education, and CS education.
BS in Computer Science and Game Software Development and MS in Computer Science and Intelligent Systems, Lawrence Technological University. Research interests: game software development; the overlap of game software development with other fields such as psychology and management.
PhD in Computer Science, Oakland University. Research interests: data mining, information extraction, natural language processing, and computer science education. Taxonomies and Ontologies, and Software Engineering.
For more information about LTU’s Computer Science programs, click here.