Dubravko Ćulibrk is a Full Professor of Information Systems Engineering at the Department of Industrial Engineering and Management within the Faculty of Technical Sciences at the University of Novi Sad, Serbia. Since March 18th, 2021, he has been dedicating most of his time and effort to developing and heading The Artificial Intelligence Research and Development Institute of Serbia.

Since July 2019, he transitioned into the role of Ambassador for Tandemlaunch, a unique startup foundry based in Montreal, Canada. Since April 3rd, 2019, he has also held the position of NVIDIA Deep Learning Institute University Ambassador.

Between 2013 and 2015, he spent two years as a postdoc researcher at the University of Trento, Italy, working with the Multimedia and Human Understanding Group. During his more recent sabbatical from 2018 to 2019, he held the post of Senior Research Scientist at Tandemlaunch.

While pursuing his Ph.D. degree from 2003 to 2006 at Florida Atlantic University, USA, his were affiliated with the Center for Coastline Security and the Center for Cryptology and Information Security. His current research interests include Neural Networks and Deep Learning, Computer Vision, Machine Learning and Data Science, Multimedia, Visual Attention, and Image/Video Processing.

Topic:  Large Language Models for Code Generation

In this keynote talk, we will explore the use of LLMs (Large Language Models) for code generation.

LLMs have emerged as a powerful tool for automating code writing tasks, allowing developers to generate high-quality code with minimal effort. We will delve into the underlying technology behind LLMs, including their composition, structure, and training data. Additionally, we will examine the benefits and limitations of LLMs for code generation, as well as their applications across various programming languages and domains. Through real-world examples and case studies, we will showcase how LLMs can drastically accelerate the software development process, increase productivity, and foster creativity. Finally, we will discuss the future of LLMs for code generation, exploring potential advancements, challenges, and ethical considerations.

(This abstract has mostly been written by an LLM called gpt-3.5-turbo and edited by the lecturer.)

Do you want to hear him? Get your ticket HERE