Information engineering

In the 1980s/1990s term information engineering referred to an area of software engineering which has come to be known as data engineering in the 2010s/2020s.{{cite web |last1=Black |first1=Nathan |title=What is Data Engineering and Why Is It So Important? |url=https://quanthub.com/what-is-data-engineering/ |website=QuantHub |access-date=31 July 2022 |date=15 January 2020}}

{{Main article|Machine learning}}

Machine learning is the field that involves the use of statistical and probabilistic methods to let computers "learn" from data without being explicitly programmed.{{Cite book|title=Pattern Recognition and Machine Learning|last=Bishop|first=Christopher|publisher=Springer-Verlag New York Inc.|year=2007|isbn=978-0387310732|location=New York}} Data science involves the application of machine learning to extract knowledge from data.

Subfields of machine learning include deep learning, supervised learning, unsupervised learning, reinforcement learning, semi-supervised learning, and active learning.

Causal inference is another related component of information engineering.

{{Main article|Control theory}}

Control theory refers to the control of (continuous) dynamical systems, with the aim being to avoid delays, overshoots, or instability.{{Cite book|title=Control Systems Engineering|last=Nise|first=Norman|publisher=Wiley|year=2015|isbn=978-1118170519}} Information engineers tend to focus more on control theory rather than the physical design of control systems and circuits (which tends to fall under electrical engineering).

Subfields of control theory include classical control, optimal control, and nonlinear control.

{{Main article|Signal processing}}

Signal processing refers to the generation, analysis and use of signals, which could take many forms such as image, sound, electrical, or biological.{{Cite book|title=Understanding Digital Signal Processing|last=Lyons|first=Richard|publisher=Prentice Hall|year=2010|isbn=978-0137027415}}

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{{Main article|Information theory}}

Information theory studies the analysis, transmission, and storage of information. Major subfields of information theory include coding and data compression.{{Cite book|title=Elements of Information Theory|last=Cover|first=Thomas|publisher=Wiley-Interscience|year=2006|isbn=978-0471241959}}

{{Main article|Computer vision}}

Computer vision is the field that deals with getting computers to understand image and video data at a high level.{{Cite book|title=Computer Vision: Principles, Algorithms, Applications, Learning|last=Davies|first=Emlyn|publisher=Academic Press|year=2017|isbn=978-0128092842}}

{{Main article|Natural language processing}}

Natural language processing deals with getting computers to understand human (natural) languages at a high level. This usually means text, but also often includes speech processing and recognition.{{Cite book|title=Speech and Language Processing|last=Jurafsky|first=Daniel|publisher=Prentice Hall|year=2008|isbn=978-0131873216}}

{{Main article|Bioinformatics}}

Bioinformatics is the field that deals with the analysis, processing, and use of biological data.{{Cite book|title=Introduction to Bioinformatics|last=Lesk|first=Arthur|publisher=Oxford University Press|year=2014|isbn=978-0199651566}} This usually means topics such as genomics and proteomics, and sometimes also includes medical image computing.

{{Main article|Cheminformatics}}

Cheminformatics is the field that deals with the analysis, processing, and use of chemical data.{{Cite book|title=An Introduction to Chemoinformatics|last=Leach|first=Andrew|publisher=Springer|year=2007|isbn=978-1402062902}}

{{Main article|Robotics}}

Robotics in information engineering focuses mainly on the algorithms and computer programs used to control robots. As such, information engineering tends to focus more on autonomous, mobile, or probabilistic robots.{{Cite book|title=Introduction to Autonomous Mobile Robots|last=Siegwart|first=Roland|publisher=MIT Press|year=2011|isbn=978-0262015356}}{{Cite book|title=Mobile Robotics|last=Kelly|first=Alonzo|publisher=Cambridge University Press|year=2013|isbn=978-1107031159}}{{Cite book|title=Probabilistic Robotics|last=Thrun|first=Sebastian|publisher=MIT Press|year=2005|isbn=978-0262201629}} Major subfields studied by information engineers include control, perception, SLAM, and motion planning.

In the past some areas in information engineering such as signal processing used analog electronics, but nowadays most information engineering is done with digital computers. Many tasks in information engineering can be parallelized, and so nowadays information engineering is carried out using CPUs, GPUs, and AI accelerators.{{Cite news|url=https://www.zdnet.com/article/how-the-gpu-became-the-heart-of-ai-and-machine-learning/|title=How the GPU became the heart of AI and machine learning|last=Barker|first=Colin|work=ZDNet|access-date=3 October 2018|language=en}}{{Cite news|url=https://www.infoworld.com/article/3290104/artificial-intelligence/powering-ai-the-explosion-of-new-ai-hardware-accelerators.html|title=Powering artificial intelligence: The explosion of new AI hardware accelerators|last=Kobielus|first=James|work=InfoWorld|access-date=3 October 2018|language=en}} There has also been interest in using quantum computers for some subfields of information engineering such as machine learning and robotics.{{Cite book|title=Quantum Machine Learning|last=Wittek|first=Peter|publisher=Academic Press|year=2014|isbn=978-0128100400}}{{Cite book|title=Supervised Learning with Quantum Computers|last=Schuld|first=Maria|publisher=Springer|year=2018|isbn=978-3319964232}}{{Cite book|title=Quantum Robotics|last=Tandon|first=Prateek|publisher=Morgan & Claypool Publishers|year=2017|isbn=978-1627059138}}

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Category:Engineering disciplines

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