Speaker: Géza Vekov, Babeș-Bolyai University, Cluj-Napoca, Romania
Date: February 26, 2025. 12:00 – 13:30
Location: JNU GAMF 4/315 Google Maps
Summary
In the smart world of Big Data and IoT sensor networks, data processing plays a crucial role. When sufficient time and computational capacity are available, data processing becomes effortless, relying on basic knowledge, Excel spreadsheets, or brute-force algorithms.
But what happens when computational resources are limited, time is constrained, and a solution must be provided? The challenge could involve making rapid stock market decisions, interrupting a critical process in real-time, continuously processing sensor data and making decisions based on the results, or detecting an unexpected object on the road. The primary goal of algorithm optimization is to minimize execution time and memory usage while processing the maximum possible amount of data.
This lecture aims to introduce certain linear-time algorithms that enable fast processing of large data sets. These algorithms classify data, identify majority elements, or perform sorting operations. We will explore the fundamentals of classifying algorithms based on execution time and analyze potential solutions to the problems mentioned above.
Their primary applications include efficient large-scale data processing, online algorithms (handling continuously incoming data), all while keeping in mind the limitations of computational resources and available time.
Speaker
Géza Vekov is a lecturer at the Faculty of Mathematics and Computer Science at Babeș-Bolyai University. He teaches courses on programming, algorithms, and data structures. His interests also include alternative methods for developing algorithmic thinking.
All interested are welcome! Participation in the lecture is free of charge.