![Computer Science in science
Examples
• Bioinformatics
• Experimental particle physics
• Quantum computing
• DNA computing
• Political and social science
• Protein folding
• Public health informatics
…
Scholars in information technology, software engineering, and
computer science study the technical and computational attributes of
digital technology
Scholars in behavioral, cognitive, and psychological sciences study
individuals’ exposure, use, appropriation, and general behaviors [within
digital technology domains].
Scholars in organizational science, management, and business study
how corporate environments shape, and are shaped by digital technology.
Economists study the large-scale effects of digital technology diffusion and
innovation on organizations, markets, and societies.
Prof. P. Patra Research in Computer Science and Engineering 7](https://image.slidesharecdn.com/researchincsepart1-240204121238-4fadfdb3/85/Research-in-Computer-Science-and-Engineering-7-320.jpg)
Research in Computer Science and Engineering
- 1. Computer Science and Engineering Research Priyadarsan Patra, Professor Part 1
- 2. Foundations of Computer Science & Engineering Prof. P. Patra 2 Research in Computer Science and Engineering Religion, Art, Culture, the Unknown etc. Humanities Social Sciences Natural Sciences Math Math Logic Paradigm shift with omni data
- 3. Scientific Method What is science? ❑ A process that systematically builds and advances knowledge by explaining, predicting, or altering phenomena/operations in the real (or the artificial!) world The Way of ‘Doing Science’ ❑ Something happens in the world around you; Observe and learn about it ❑ Form a hypothesis that explains/predicts/alters it ❑ Gather data through experimentation* ❑ Test hypothesis against the collected “hard cases or benchmarks” ❑ If successful, use it as a model and explain more ◼ Meetings, publish, share Value of skepticism, criticism, peer review, challenge ◼ Become part of the scientific literature – you made a “dent” else ‘Rinse and repeat’ (Until no known counterexample disproves it) ◼ New hypotheses, new experiments to retest ideas Multiple conditions, times, people -> well-supported hypothesis -> model -> theory ➢ The Scientific Method is a way of thinking, not a formula Prof. P. Patra Research in Computer Science and Engineering 3
- 4. CSE is a Young Science There is science in Computer Science (CS) although not all of CS is conventional science ◼ It is the study of computing and computing engines CS combines science, engineering, and math ◼ Hypothesis formulation, Algorithm Design and Performance Testing ◼ Design and implementation of computer systems ◼ Proofs and analysis of algorithms and information transformation ◼ Computer Science, and Computer Engineering are often clubbed together to be called CSE: Designing a computing or communication chip… CS has been combined with nearly every other field ◼ CSE has found itself at the cornerstone of interdisciplinary research ◼ Nearly endless combinations leading to nearly endless interesting questions to explore ◼ Has a foundation and transformative role at the interfaces of disciplines Prof. P. Patra Research in Computer Science and Engineering 4
- 5. The “Science” in Computer Science Some think that computer science is not a science in the same sense as biology or chemistry ◼ Interdisciplinary nature of computer science has made it hard to classify ◼ Discovery vs Invention/innovation • Researchers in Biologists, physicists, chemists, psychology… are discoverers • Computer scientists, researchers in nanotech or in process engineering or in industrial engineering… are inventors Computer science is the study of computation and the machinery ◼ Involves all aspects of problem solving and machine building, including design and analysis of algorithms formalization of algorithms as programs development of computational devices for executing programs and ‘learning’ theoretical study of the power and limitations of computing and computer ◼ In short, computer science represents a rigorous approach to understanding complex phenomena and problem solving! Prof. P. Patra Research in Computer Science and Engineering 5
- 6. Scientific Method (in CSE) The process developed by the scientific community for examining observations and events is known as the scientific method Many activities carried out by computer scientists follow the scientific method ◼ e.g., designing and implementing a large database system requires hypothesizing about its behavior under various conditioning, experimenting to test those hypotheses, analyzing the results, and possibly redesigning ◼ e.g., debugging a complex program requires forming hypotheses about where an error might be occurring, experimenting to test those hypotheses, analyzing the results, and fixing the bugs ◼ Specifying, Architecting, Modeling, Designing, Simulating, Verifying, Manufacturing, then Validating the resultants (with loopbacks at various stages!) Prof. P. Patra Research in Computer Science and Engineering 6
- 7. Computer Science in science Examples • Bioinformatics • Experimental particle physics • Quantum computing • DNA computing • Political and social science • Protein folding • Public health informatics … Scholars in information technology, software engineering, and computer science study the technical and computational attributes of digital technology Scholars in behavioral, cognitive, and psychological sciences study individuals’ exposure, use, appropriation, and general behaviors [within digital technology domains]. Scholars in organizational science, management, and business study how corporate environments shape, and are shaped by digital technology. Economists study the large-scale effects of digital technology diffusion and innovation on organizations, markets, and societies. Prof. P. Patra Research in Computer Science and Engineering 7
- 8. Computer Science Themes since computation encompasses many different types of activities, computer science research is often difficult to classify ◼ three recurring themes define the discipline David Reed, ISBN 0-13-046709-X Prof. P. Patra Research in Computer Science and Engineering 8
- 9. A Science of the ‘Artificial’ The distinction between computer science and natural sciences like biology, chemistry, and physics is the type of systems being studied ◼ natural sciences study naturally occurring phenomena and attempt to extract underlying laws of nature ◼ computer science studies human-made constructs: programs, computers, and computational modes Herbert Simon coined the phrase "artificial science" to distinguish computer science from the natural sciences In Europe, computer science is commonly called "Informatics" ◼ emphasizes the role of information processing as opposed to machinery ◼ Denning: Science of information processes and their interactions with the world The term "Algorithmics" has also been proposed ◼ emphasizes the role of algorithms and problem solving Other related fields study computation from different perspectives ◼ computer engineering focuses on the design and construction of computers ◼ information systems management focuses on business applications Ack: David Reed, Creighton University Prof. P. Patra Research in Computer Science and Engineering 9
- 10. Basic vs. Applied in the World of CSE Search Engines and Information Retrieval: Applied: Code employing algorithms, data structures, and distributed computing Basic: PageRank algorithms, natural language processing, and information retrieval theory. Machine Learning and Deep Learning: Applied: image and speech recognition, recommendation systems, and autonomous vehicles are among numerous applications. Basic: neural networks, reinforcement learning, and transfer learning, pushing the boundaries of AI understanding. Cybersecurity – information and systems: Applied: security protocols and tools to protect computer systems from cyber threats Basic: spawned cryptography, network security, and cybersecurity theory Blockchain and Cryptocurrency: Applied: like Bitcoin involve Applied in distributed ledger technology. Basic: cryptography, consensus algorithms, and decentralized systems. Human-Computer Interaction (HCI): Applied: user interface & experience in/with software and hardware products Basic: cognitive psychology, usability testing, and user-centered design principles. Natural Language Processing (NLP): Applied: Building chatbots, language translation tools, and sentiment analysis Basic: fundamental research in syntax, semantics, and linguistic models. Quantum Computing: Applied: applications such as cryptography and search optimization problems Basic: quantum algorithms, and quantum information theory Prof. P. Patra Research in Computer Science and Engineering 10
- 11. The Art and Science of CSE Research The "Art": Creativity: The ability to think outside the box, propose new solutions, and design innovative algorithms or systems. Design: The artistry involved in designing user interfaces, algorithms, architectures, and other components of systems & devices. Problem Solving: The creative approach to identifying and solving complex problems, which often requires unconventional thinking. Visualization: Creating visual representations of data or systems, making complex concepts more understandable. User Experience (UX) Design: Crafting interfaces and interactions that are not only functional but also aesthetically pleasing and user-friendly. Innovation: Pushing the boundaries of what's possible -- through novel concepts, ideas, and approaches. The ‘Science’: Scientific Method: involves formulating hypotheses, conducting experiments, collecting data, and drawing conclusions based on evidence. Empirical Analysis: Gathering and analyzing data to validate hypotheses, makeinformed decisions, and quantify the effectiveness of solutions. Algorithms: Thedevelopment and analysis of algorithms based on mathematical principles and formalproofs. Applying Engineering Principles: such as systemdesign, optimization, and reliability, to create practicaland efficient solutions. Experimental Validation: Conducting experiments, simulations, or testing to validate theories and models in a controlled and systematic manner. Quantitative Analysis: Using quantitativemethods, statistics, and metrics to measurethe performance, efficiency, and effectiveness of systems and solutions. Computer Science Theory: Investigating thetheoretical foundations such as automata theory, complexity theory, and formallanguages. DataScience: Applying scientific methods and specialized devices to extract meaningful insights fromdata and make data-driven decisions Software Engineering: systematic approaches to design, develop, test and maintain softwaresystems. Prof. P. Patra Research in Computer Science and Engineering 11