New from the Faculty of Engineering: The Data Engineering Program

Over the past several years, data-driven science has become a leading field in the hi-tech industry and in academia.  The Faculty of Engineering at Bar-Ilan University is launching an innovative and up-to-date data engineering program and will be one of the first faculties in Israel to offer such a program for undergraduate students. “It’s a hot and highly sought-after field, both in the industry and academia, and our faculty already offers many courses in the core of the field, including courses in signal processing, machine learning, computer networks, and cryptography,” says Prof. Sharon Gannot, who will be heading the new program. “The program is designed for students who excel in quantitative and analytical thinking, and will provide them with the scientific and technological foundations of data science and engineering, including extensive technical knowledge and the practical skills required to effectively and efficiently analyze and process signals and data.”

The new program emphasizes machine learning and statistical signal processing from both the theoretical and applicative perspectives and provides its graduates with the tools to handle signals and data that represent physical phenomena, along with a comprehensive understanding of the data science cycle (data collection, processing, and analysis, deduction and implications for accumulated knowledge), a broad systems-thinking and engineering perspectives, and practical skills in core data science tools. “Other institutions around the world offer similar programs for advanced degrees. We looked into those, of course, but we really wanted to inject our perspective, figure out how such a program would work in the context of the Faculty of Engineering,” shares Prof. Gannot. “In parallel, I assembled a committee of international experts who specialize in a variety of topics in signal processing and machine learning, and together we created guidelines for such types of programs, targeting engineering students. We wanted to understand what knowledge and skills our students need to acquire in order to work in these fields or to proceed with advanced studies and research. Data science evolved from several disciplines, including statistics, applied mathematics, information systems, industry engineering, computer science, bio-informatics, and, of course, signal processing. A large quantity of data comes from sampled signals. The analytical and statistical tools developed for signals, e.g., images, video, and audio, give experts in signal processing a significant advantage. We presented our findings at the prestigious IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), held in May 2022 in Singapore. We are currently working on a joint publication with the aim of defining and applying the perspectives of experts from the fields of engineering and signal processing in the data science discipline.”

The new program is particularly suitable for students with excellent mathematical grasp and will include expanded mathematics studies—more so than other engineering programs—as well as computer and algorithmic skills, signal processing, machine learning, and statistical inference. In addition, we will emphasize applications, in part via a unique track dedicated to various applications of data engineering in bio-informatics, speech processing, natural language processing, smart cities, econometrics, crypto currency, materials engineering, electro-optics and more. “The application track is mandatory, and includes 11 courses from which students must choose two,” explains Prof. Gannot. “Our aim is to allow students to learn and expand their knowledge in real-world subjects and expose them to real-life applications.

As part of this applied emphasis, students will have to hand in an annual final project starting in their second year, and of course, an extensive graduation project in the fourth year, as required in other programs in the faculty." In addition to the application track, and similar to other degrees offered by the Faculty of Engineering, the students will have five specialization tracks from which they would have to choose two: networks and communication, information processing and analysis and statistical learning, computer vision and computer graphics, optimization and algorithms, information security and reliability. "We will also be raising students' awareness of the ethical aspects of learning systems, via a designated course, as well as an emphasis on these aspects during practical courses," says Prof. Gannot, adding: "The importance of ethics in the development of data-driven methods cannot be overstated."

As in all fields of engineering, the data engineering program takes four years to complete. The program has been carefully crafted to allow its graduates to pursue advanced degrees or to find their place in the hi-tech industry in a variety of development and research roles. Graduates will be able to work in software development for data processing and analysis and statistical inference, develop modern algorithms for machine learning and signal processing from various sources, and delve into a theoretical analysis of problems and performance evaluation, management, storage, and transfer of data in a reliable and secure manner, and more. "These fields are in great demand, and it’s a trend that will only continue to rise," clarifies Prof. Gannot. "Graduates of the program are bound to have a promising future in industry or academia and engage in fascinating topics at the forefront of science and application."

The program is CHE certified and is open for applications. The electrical engineering program with a signal processing track, or the computer engineering program with a data processing and analysis track will be a ‘safety net’ for this program. You can find the complete course list here: https://engineering.biu.ac.il/node/11526.