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PLOS ONE is holding a Call For Papers on the topic of New Supply Chain Technologies to highlight the latest research in this field. We interviewed PLOS ONE Academic Editor Sanaa Kaddoura to learn about her research in this field and her perspectives on computer science education and the impact of this topic in wider society.
Dr. Sanaa Kaddoura holds a Ph.D. in computer science from Beirut Arab University, Lebanon. She is currently employed as an assistant professor of information security at the Department of Computing and Applied Technology, College of Technological Innovation, Zayed University, United Arab Emirates. She is also an assistant professor of business analytics for Master’s degree students in the UAE. She is a fellow of Higher Education Academy, Advance HE (FHEA) since 2019, which demonstrates a personal and institutional commitment to professionalism in learning and teaching in higher education. Furthermore, she has been a certified associate from Blackboard Academy since April 2021. In addition to her research interest in cybersecurity and Arabic NLP, she is actively doing research in higher education teaching and learning related to enhancing the quality of instructional delivery to facilitate students’ acquirement of skills and smooth transition to the workplace.
PLOS: Can you tell us a little about your career in science so far? How closely related is your research field to where you started out with your first degree?
SK: Currently, I am working in the education section as an assistant professor of computer science at Zayed University, UAE. Since I started my study of computer science, my career has gone through different stages. I worked as a programmer, technical support manager, and educator. After finishing my Ph.D., I decided to be an educator and researcher. Many other Ph.D. holders may decide to go into industry rather than educational institutions.
The computer science major is changing every day. Daily, new technologies, inventions, and algorithms bring new problems to solve and new research to investigate. Some research topics considered hot topics a few years ago are now considered mature and have less opportunity for research. This might be due to having the problem solved, or the problem has been made irrelevant due to technological changes. The computer science domain is exponentially changing. In previous research works we were required to create our own solution to problems; however, now, there is commercial software that can help us. This is taking the research in this domain to deeper and more advanced places.
From the jobs perspective, computer science is one of the fastest-growing professions in the global economy. One should keep learning new skills to compete in the job market and maintain position. Thus, computer scientists can’t keep doing the same activities they started with when they graduated. Unlike many other jobs in the market, computer science keeps moving people to a newer level with every new technology.
PLOS: What are you working on at the moment? What inspires you about your research and the things you get to do every day?
SK: The research project I started in September 2022, funded by Zayed University, is about Arabic Natural Language understanding (NLU). NLU is a subtopic of natural language processing. It deals with a computer’s ability to comprehend and understand human language. NLU is considered an AI-hard problem due to the vast data required as training input to the algorithm. The solution to this problem has reached an advanced level in some languages, such as the English language. However, for the Arabic language, this problem still needs a lot of work to enable computers to comprehend Arabic text and voice accurately. The complexity of Arabic NLU is due to its complex syntactic structure, such as having a lot of irregular plural verbs. In addition to the problems in the formal Arabic language, the Arab world has a lot of dialects (spoken language). This makes NLU for the Arabic language more challenging, especially for speech recognition and chatbot applications. Moreover, the Arabic language still lacks the corpus data needed for such algorithms. Working on this problem requires computer scientists and Arabic language professionals to be involved to ensure accurate results.
As an Arabic native speaker, I am enthusiastic about participating in the research efforts towards empowering the Arabic language in the new smart devices. It is essential to carry the Arabic language as an essential pillar in the 4th industrial revolution. We can improve machine translation systems, Arab robots, Arabic digital assistants, and others.
PLOS: A lot of your research has focused on the interface between computer science and education. Why is this topic so important, and how can computer science help us understand how to be better educators?
SK: No one can deny that computer science has become part of all other fields, especially education. Computer science contributes in many aspects to the teaching-learning process. Now, no educator can set up a class session without using interactive tools, especially after the COVID-19 pandemic. All educators had to go online for their teaching/learning process to continue. To engage students in the classroom, educators are using online gaming platforms, for example. All these tools need computer scientists to create them. Computer science has become a major in demand.
Also, everyone must learn computer science, especially programming. It should be an essential subject in schools, just like math. There is a famous saying from Steve Jobs: “Everyone in this country should learn how to program because it teaches you how to think.” Programming teaches students logical thinking and provides them with problem-solving skills, such as learning how to break a problem into smaller chunks, solve each chunk, and then integrate them all into one complete solution.
Most occupations will soon require some familiarity with computer programming, and as technology develops, so will the skills needed for software engineering positions. In the coming years, computer science is expected to grow significantly. To sum up, a computer science major has become a core part of our life. No one can live without being part of it, either as a developer or a user.
PLOS: PLOS ONE currently has an open Call For Papers on New Supply Chain Technologies (https://collections.plos.org/call-for-papers/new-supply-chain-technologies/). How does machine learning and cybersecurity work in this field, and what open research questions do you foresee when it comes to the future of supply chains?
SK: Currently, machine learning is contributing as a tool for the prediction and classification of data for other domains. One of these domains is the supply chain. Machine learning can be used as a forecasting tool in the supply chain. A robust forecasting system in the supply chain allows a business to respond quickly, be prepared for any issues, and react quickly without disrupting the business. Another example of the power of machine learning in the supply chain is improving customer experience. A critical example of this area is the Amazon e-commerce website. Amazon employs machine learning to find the correlation between the customer and products for a better shopping experience for the customer.
The supply chain is similar to all other digitized domains in the 4th industrial revolution. It has cybersecurity issues that can disrupt its operations in the case of an attack, affecting the business’s revenue. The supply chain can be affected by ransomware, data breach, malware, and other attacks.
There is still a lot of research to be done in this area. The question is always: “what actions should be taken to secure a supply chain?” Although much research has been done in this area, this question will always be open because attackers are changing these attacking techniques and making the attacks more sophisticated. We are always in a race with attackers who want to disrupt business, gain money, and spread malware.
Disclaimer: Views expressed by contributors are solely those of individual contributors, and not necessarily those of PLOS.