Kaushal Kumar Maurya

Portrait of Kaushal Kumar Maurya

Hey! I am Kaushal Kumar Maurya, an Assistant Professor in the Computer Science and Artificial Intelligence at IIT Delhi Abu Dhabi (IITDAD), Abu Dhabi, UAE.

My research focuses on Machine Learning and Natural Language Processing, with a particular emphasis on Large Language Models (LLMs) for education, multilingual language technologies, and responsible NLP. I am interested in developing language-based computational models and tools that advance social good and enhance equitable access to technology. My work is grounded in insights from cognitive science, linguistics, and learning sciences, with the goal of building AI systems that are effective, reliable, and beneficial in real-world settings.

I completed my PhD in the Department of CSE at IIT Hyderabad under the supervision of Dr. Maunendra Sankar Desarkar. I subsequently worked as a Postdoctoral Research Fellow in the Natural Language Processing Department at Mohamed bin Zayed University of Artificial Intelligence (MBZUAI), Abu Dhabi, with Prof. Thamar Solorio and Dr. Ekaterina Kochmar. I actively collaborate with researchers from Microsoff India (R&D), Nvidia, Shizuoka University, The University of Tokyo, MBZUAI, and IIT Hyderabad. My work has been recognized with the Best SAC Paper Award at NAACL 2025, the Exceptional Doctoral Research Scholar Award from the CSE Department at IIT Hyderabad, and the Google Academic Research Award 2024 as a Co-PI.

Prospective PhD Students: Interested candidates should apply through the official IIT Delhi Abu Dhabi PhD admissions portal and select a PhD project associated with my name. For any queries or clarifications, please email me at kaushal.maurya [at] iitdabudhabi.ac.ae.

Current Research Interests

Educational NLP

Education is a foundational pillar of societal development, yet we still lack high-quality educators and education, especially in economically marginalized regions or countries. Current language models present an opportunity to bridge this gap. However, it remains unexplored whether they can truly serve as effective AI tutors or tutor co-pilots for long-term learning. Tutoring is inherently at the conversational level—can these models imitate complex interactions like a human?

Selected Papers:
Unifying AI Tutor Evaluation: An Evaluation Taxonomy for Pedagogical Ability Assessment of LLM-Powered AI Tutors (NAACL 2025)
Pedagogy-driven Evaluation of Generative AI-powered Intelligent Tutoring Systems (AIED 2025 - Blue Sky Track)

Multilingual NLP

Despite over 7,000 languages spoken globally, NLP research remains largely English-centric, overlooking the needs of millions who are not primary English speakers. Most state-of-the-art language models cover only a few hundred languages, with the vast majority being low-resource languages that lack sufficient digital representation. Can we harness semantic, lexical, and typological similarities between low- and high-resource languages to enable native-language applications? Can linguistically informed, low-resource methods facilitate effective cross-lingual transfer for underrepresented languages?

Selected Papers:
SelectNoise: Unsupervised Noise Injection to Enable Zero-Shot Machine Translation for Extremely Low-Resource Languages (EMNLP 2023 - Findings)
Meta-XNLG: A Meta-Learning Approach Based on Language Clustering for Zero-Shot Cross-Lingual Transfer and Generation (ACL 2022 - Findings)

Responsible NLP

The rapid advancement and widespread deployment of LLMs present challenges around safety, alignment, and social responsibility. These models can hallucinate, reinforce biases, or produce outputs misaligned with human values. How can we detect such socially unacceptable behavior? How can we develop safer and socially aligned models?

Selected Papers:
DAC: Quantized Optimal Transport Reward-based Reinforcement Learning Approach to Detoxify Query AutoCompletion (SIGIR 2024)
DQAC: Detoxifying Query Auto-completion with Adapters (PAKDD 2024)

News and Updates

  • May 2025: Featured in the official MBZUAI Blog on Tutors of Tomorrow. Check out the Blog!
  • May 2025: Serving as Session Chair for the Multilinguality and Language Diversity track at NAACL 2025.
  • May 2025: Won the SAC Award for the Resource and Evaluation Track at NAACL 2025.
  • Apr 2025: Position paper on AI Tutor Evaluation accepted at AIED 2025 (Blue Sky Track).
  • Mar 2025: Co-organizing the BEA Shared Task 2025. Participate here: CodaBench