Riza Velioglu

Riza Velioglu
Bielefeld University · CITEC - Cognitive Interaction Technology

Master of Science
Computer Vision, Vision and Language | Co-founder

About

10
Publications
3,053
Reads
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105
Citations
Introduction
Riza Velioglu earned his B.Sc. in Electrical and Electronics Engineering from Istanbul Bilgi University in 2018, followed by an M.Sc. in Intelligent Systems from Bielefeld University in 2021. In 2019, he co-founded a tech startup that raised 6M+ euros in investment, leading the R&D team. Currently a Ph.D. candidate, his research focuses on Object Detection and Segmentation, Multi-Modal Learning (Vision-Language Models), and Image Generation.
Additional affiliations
April 2020 - August 2020
Bielefeld University
Position
  • Teaching Asisstant
Description
  • ►Tutor of the course "Introduction to Neural Networks" • Held tutorials for a class of 80 students, 1 day a week • Prepared homework & solutions ►Tutor of the course "Introduction to Computer Algorithms" • Held tutorials for a class of 25 students, 1 day a week • Prepared solutions to the homeworks
October 2019 - March 2020
Bielefeld University
Position
  • Research Assistant
Description
  • ►Tutor of the course "Introduction to Machine Learning" • Held tutorials for 2 classes of 50 students, 2 days a week • Prepared material for tutorials • Prepared solutions to homeworks & graded them *** Awarded "The Best Tutor Award"
February 2019 - September 2019
Bielefeld University
Position
  • Research Assistant
Education
October 2018 - April 2021
Bielefeld University
Field of study
  • Intelligent Systems
September 2013 - July 2018
Istanbul Bilgi University
Field of study
  • Electrical & Electronics Engineering

Publications

Publications (10)
Preprint
Full-text available
Project Page: https://rizavelioglu.github.io/fashionfail/ To be published in 2024 International Joint Conference on Neural Networks (IJCNN)
Preprint
Full-text available
In modern business processes, the amount of data collected has increased substantially in recent years. Because this data can potentially yield valuable insights, automated knowledge extraction based on process mining has been proposed, among other techniques, to provide users with intuitive access to the information contained therein. At present,...
Chapter
In modern business processes, the amount of data collected has increased substantially in recent years. Because this data can potentially yield valuable insights, automated knowledge extraction based on process mining has been proposed, among other techniques, to provide users with intuitive access to the information contained therein. At present,...
Preprint
Full-text available
The IARAI Traffic4cast competitions at NeurIPS 2019 and 2020 showed that neural networks can successfully predict future traffic conditions 1 hour into the future on simply aggregated GPS probe data in time and space bins. We thus reinterpreted the challenge of forecasting traffic conditions as a movie completion task. U-Nets proved to be the winni...
Preprint
Full-text available
Accurate traffic prediction is a key ingredient to enable traffic management like rerouting cars to reduce road congestion or regulating traffic via dynamic speed limits to maintain a steady flow. A way to represent traffic data is in the form of temporally changing heatmaps visualizing attributes of traffic, such as speed and volume. In recent wor...
Article
Machine translation (MT) is an important challenge in the fields of Computational Linguistics. In this study, we conducted neural machine translation (NMT) experiments on two different architectures. First, Sequence to Sequence (Seq2Seq) architecture along with a variation that utilizes attention mechanism is performed on translation task. Second,...
Preprint
Full-text available
Memes on the Internet are often harmless and sometimes amusing. However, by using certain types of images, text, or combinations of both, the seemingly harmless meme becomes a multimodal type of hate speech -- a hateful meme. The Hateful Memes Challenge is a first-of-its-kind competition which focuses on detecting hate speech in multimodal memes an...
Conference Paper
Full-text available
Abstract—With the rise of the usage and interest on social media platforms, emojis have become an increasingly important part of the written language and one of the most important signals for micro-blog sentiment analysis. In this paper, we employed and evaluated classification models using two different representations based on bag-of-words and fa...

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