Olga Vechtomova, PhD

Dr. Olga Vechtomova is a Professor in the Department of Management Science and Engineering, Faculty of Engineering, cross-appointed in the Cheriton School of Computer Science at the University of Waterloo. Professor Vechtomova leads the Natural Language Processing (NLP) Lab, affiliated with the Waterloo AI Institute. Her research has been supported by a number of industry and government grants, including Amazon Research Award, Natural Sciences and Engineering Research

Council (NSERC) and Social Sciences and Humanities Research Council (SSHRC). Her current and recent research projects include aesthetic preferences modelling, controlled text generation, text style transfer, supporting human artistic creativity with AI, and designing generative AI models for creative applications. She has over 50 publications in top conferences and journals, including ACL, ACM SIGIR, and ACM CIKM, COLING, EMNLP, EACL, and NAACL-HLT. Professor Vechtomova and her colleagues received the ACM SIGIR 2019 Test of Time Award.

• natural language generation

• artificial intelligence

• machine learning

• natural language processing

• computational linguistics

• computational creativity

• AI and creativity

• AI and music

• AI and poetry

• AI and art

The Natural Language Processing (NLP) Lab, led by Professor Olga Vechtomova, explores how AI can inspire and collaborate with artists through real-time generative systems and computational models of artistic inspiration. The lab's research investigates fundamental questions about generating output that is coherent yet surprising enough to inspire human creativity, with applications spanning music, dance, and poetry. Through collaborations with multimedia artists, dancers, and musicians, recent projects include systems for real-time co-creation between dancers and AI, and computational modeling of aesthetic preferences in poetic lines (recipient of the Best Paper Award at ICCC 2025). Creative systems developed in the lab include LyricJam—which generates lyrics during live instrumental performances—and LyricJam Sonic, an AI assistant that creates evolving soundscapes in response to live music. Both systems are publicly available at lyricjam.ai for artists and musicians to use. By developing novel machine learning techniques for live performance systems deployed in real artistic contexts, the NLP Lab is pioneering new forms of human-AI creative collaboration.

• 2001, Doctorate Information Science, City University, London, UK

• 2025 Best Paper Award, International Conference on Computational Creativity (ICCC 2025)

• 2019 ACM SIGIR Test of Time Award

• 2011 Best Paper Award, ACM SIGIR Workshop on Entity Oriented Search

• 2010 Life member of Clare Hall College, University of Cambridge, UK

• 2009 Outstanding Performance Award, UW

• MSCI 245 - Databases and Software Design
  • Taught in 2022, 2023, 2024
• MSCI 342 - Principles of Software Engineering
  • Taught in 2023, 2024
• MSCI 598 - Special Topics in Management Engineering
  • Taught in 2022
• MSCI 641 - Text Analytics
  • Taught in 2022, 2023, 2024
• MSE 245 - Databases and Software Design
  • Taught in 2025
• MSE 342 - Principles of Software Engineering
  • Taught in 2025, 2026
• MSE 641 - Text Analytics
  • Taught in 2025

* Only courses taught in the past 5 years are displayed.

• Vechtomova, Olga and Sahu, Gaurav and Kumar, Dhruv, LyricJam: A system for generating lyrics for live instrumental music, Proc. of the 12th Conference on Computational Creativity, , 2021

• Bahuleyan, Hareesh and Mou, Lili and Vechtomova, Olga and Poupart, Pascal, Variational Attention for Sequence-to-Sequence Models, COLING, , 2018