Application Of Mathematics In Computer Science And Engineering

1. Application Of
Mathematics In
Computer
Science And
Engineering

2. Dr. Bimal Chandra Das (BCD)
Associate Professor
Department of GED
Faculty of SIT

3. Emam Ul Haque
Emon
ID - 222-15-6290
Section - 62_C
Fyshal Ahmed
ID - 222-15-6195
Section - 62_C
Tausif Mahmud
Ruhan
ID - 222-15-6432
Section - 62_C
Masudul Alom
ID - 222-15-6290
Section - 62_C
T.M. Shahid Rumi
ID - 222-15-6485
Section - 62_C
Abdullah Al
Mahmud
ID - 222-15-6115
Section - 62_C
Mufuqur Rahman
ID - 222-15-6290
Section - 62_C

4. Math is one of the most important subject for
computer science which provides a foundation
for more advanced topics in computer
science.
❖ Problem-solving skills,
❖ Logical thinking,
❖ Structure and analyze arguments.
These are all critical skills for a computer
scientist.
Why Math is important?

5. Algorithms and Data Structures
Mathematics is crucial for designing and analyzing algorithms and data structures.
Mathematical concepts such as graph theory, probability theory, and combinatorics provide
the foundation for developing efficient algorithms for tasks like sorting, searching,
optimization, and machine learning.

6. Number Theory
Cryptography
Encryption &
Decryption
Network Security
Digital
Signature

7. Artificial Intelligence and Machine Learning
Mathematics, particularly statistics, linear algebra, and calculus, forms the backbone of
artificial intelligence (AI) and machine learning (ML). These fields rely on mathematical
models and algorithms to train models, make predictions, and perform data analysis.
Techniques like regression, neural networks, support vector machines, and clustering
heavily depend on mathematical foundations

8. Computational Geometry
Computational geometry deals with the efficient manipulation and analysis of geometric
objects, such as points, lines, and polygons, using computers. Concepts from linear algebra,
calculus, and discrete mathematics are applied to solve problems like geometric algorithms,
computer graphics, and spatial data analysis.

9. Computer Vision
Computer vision aims to enable computers to understand and interpret visual information
from images or videos. Mathematics plays a vital role in tasks such as image recognition,
object detection, image segmentation, and 3D reconstruction. Concepts like linear algebra,
calculus, statistics, and probability theory are essential for image processing and computer
vision algorithms.

10. Computer Networks and Optimization
Mathematical optimization techniques are employed to optimize network routing, resource
allocation, scheduling, and capacity planning. Linear programming, integer programming,
and network flow algorithms are used to solve optimization problems in computer networks
and system design.

11. Simulation and Modeling
Mathematics is used to model and simulate complex systems in various domains, such as
physics, economics, and social sciences. Numerical methods, differential equations, and
probability theory are employed to create mathematical models and simulate real-world
phenomena in computer-based simulations.