Igor Labutov

Chief AI Officer @ Epiq

Igor Labutov is Chief AI Officer and leads Epiq AI Labs. As a computer scientist and entrepreneur, Igor has spent more than a decade advancing Artificial Intelligence and Machine Learning, with a particular focus on systems that learn from natural human supervision.

He earned his Ph.D. from Cornell, working with Christoph Studer and Hod Lipson, and completed postdoctoral research at Carnegie Mellon with Tom Mitchell, where his work focused on human-centered AI and machine learning.

Prior to joining Epiq, he co-founded LAER AI with Bishan Yang, pioneering AI technologies for legal and investigative workflows.

As Chief AI Officer, Legal Solutions, Igor leads AI strategy and execution across Epiq's Legal Solutions business, driving the development and integration of AI-powered products and services that help clients navigate increasingly complex legal, regulatory, and business challenges.

Publications

Learning to Learn Semantic Parsers from Natural Language Supervision

I Labutov, Bishan Yang and Tom Mitchell
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing

Multi-Relational Question Answering from Narratives: Machine Reading and Reasoning in Simulated Worlds

I Labutov and Bishan Yang
Proceedings of the Association for Computational Linguistics Vo. 1. 2018

Joint concept learning and semantic parsing from natural language explanations

S Srivastava, I Labutov, Tom Mitchell
Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing

Zero-shot learning of classifiers from natural language quantification

S Srivastava, I Labutov, Tom Mitchell
Proceedings of the Association for Computational Linguistics Vo. 1. 2018

LIA: A Natural Language Programmable Personal Assistant

I Labutov, Shashank Srivastava and Tom Mitchell
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing (Demo Paper)

APPINITE: A Multi-Modal Interface for Specifying Data Descriptions in Programming by Demonstration Using Natural Language Instructions

Toby Jia-Jun Li, I Labutov, Xiaohan Nancy Li, Xiaoyi Zhang, Wenze Shi, Wanling Ding, Tom Mitchell and Brad A. Myers
2018 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC). IEEE, 2018

Designing a conversational interface for a multimodal smartphone programming-by-demonstration agent

Toby Jia-Jun Li, I Labutov, Brad A. Myers, Amos Azaria, Alexander I. Rudnicky and Tom Mitchell
Conversational UX Design CHI 2017 Workshop, Denver CO

An End User Development Approach for Failure Handling in Goal-oriented Conversational Agents

Toby Jia-Jun Li, I Labutov, Brad A. Myers, Amos Azaria, Alexander I. Rudnicky and Tom Mitchell
Book Chapter. Studies in Conversational UX Design, Springer (2018)

Evaluation methods for unsupervised word embeddings

T Schnabel, I Labutov, David Mimno, Thorsten Joachims
Proceedings of the 2015 Conference on Empirical Methods in Natural Language Prrocessing

Semi-supervised Techniques for Mining Learning Outcomes and Prerequisites

I Labutov, Yun Huang, Peter Brusilovsky, Daqing He
Proceedings of the 23rd ACM SIGKDD international conference on Knowledge Discovery and Data Mining

Unbounded human learning: Optimal scheduling for spaced repetition

S Reddy, I Labutov, S Banerjee, Thorsten Joachims
Proceedings of the 22nd ACM SIGKDD international conference on Knowledge Discovery and Data Mining

Learning student and content embeddings for personalized lesson sequence recommendation

S Reddy, I Labutov, Thorsten Joachims
Proceedings of the Third (2016) ACM Conference on Learning@ Scale, 93-96

Re-embedding words

I Labutov, H Lipson
Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics

Deep questions without deep understanding

I Labutov, Sumit Basu, Lucy Vanderwende
Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics

Humor as circuits in semantic networks

I Labutov, H Lipson
Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics

Calibrated Self-Assessment

I Labutov, C Studer
Proceedings for Educational Data Mining (EDM) Conference 2016

Generating code-switched text for lexical learning

I Labutov, H Lipson
Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics