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.
I am interested in language-based computational models and tools that enable equitable access to knowledge and technology. My research is driven by a fundamental question: how do humans learn, communicate, and build knowledge through interaction? Learning emerges through iterative cycles of inquiry, feedback, and the integration of new information with prior knowledge. Understanding these processes is key to designing AI systems that effectively support human learning and collaboration. Despite remarkable advances in large language models (LLMs), they still struggle to support learning, generalize beyond high-resource settings, and align reliably with human goals and values. My research seeks to understand the computational principles underlying learning, communication, and human-AI interaction, drawing on insights from learning and cognitive sciences to augment human capabilities.
I received my PhD from the Department of CSE at IIT Hyderabad, where I was advised by Dr. Maunendra Sankar Desarkar. I was subsequently a Postdoctoral Research Fellow in the Natural Language Processing Department at MBZUAI, working with Dr. Ekaterina Kochmar, and a Research Scientist in the RiTUAL Lab with Prof. Thamar Solorio. I collaborate with researchers at Microsoft India (R&D), NVIDIA, Shizuoka University, University of Tokyo, MBZUAI, and IIT Hyderabad. My work has been recognized with the Best SAC Paper Award at NAACL 2025, the Google Academic Research Award 2024 (Co-PI), and the Exceptional Doctoral Research Scholar Award from IIT Hyderabad.
Current Research Interests
AI for Education
Education is a fundamental pillar of societal development, yet access to expert educators and quality education remains limited, particularly in economically marginalized regions. Language models offer a promising opportunity to bridge this gap, but it remains unclear whether they can serve as effective AI tutors or support human tutors in long-term learning. Since tutoring is inherently conversational, can these models emulate the complex interactions of a human tutor?
Selected Papers:
AITutor-EvalKit: Exploring the Capabilities of AI Tutors (EACL 2026 - Demo Track)
Unifying AI Tutor Evaluation: An Evaluation Taxonomy for Pedagogical Ability Assessment of LLM-Powered AI Tutors (NAACL 2025)
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
- Jun 2026: Joined IIT Delhi Abu Dhabi (IITDAD) as an Assistant Professor in CSE & AI.
- May 2026: Two papers accepted: one at the CBT Workshop at ICML 2026 and one at the BEA Workshop at ACL 2026.
- Apr 2026: Serving as Graduate Forum Co-chair for IndoML 2026.
- Mar 2026: Serving as Diversity and Inclusion (D&I) Co-chair for EACL 2027.
- Mar 2026: AITutor-EvalKit was presented at EACL 2026, Morocco. Check out the demo platform.