Mohammad Nadeem

About

Dr Mohammad Nadeem is an Assistant Professor in the Department of Computer Science at Aligarh Muslim University (AMU), India where he has been serving since 2016. He received his PhD in Computer Science from IIT (ISM) Dhanbad, India and his academic and research work broadly focus on trustworthy AI, AI safety, fairness in foundation models and socio-technical aspects of advanced AI systems.

His recent research particularly explores representational biases and societal implications of large language and multimodal AI systems with emphasis on Global South contexts and region-aware AI evaluation. His works have appeared in venues such as Nature Machine Intelligence, IEEE Intelligent Systems, IEEE Transactions on Big Data, Interspeech (CORE A Conference), and IJCNN (CORE B Conference),. He has also contributed to the development of fairness-oriented datasets and evaluation resources, including IndicFairFace, a balanced Indian face dataset designed for studying geographical bias in vision-language models. He has also received research and travel support from organizations including OpenAI, ANRF-India, and SERB-DST India.

Employment

• Aligarh Muslim University Assistant Professor
  2016 - Present

Education

• Indian Institute of Technology (Indian School of Mines), Dhanbad PhD
  2013 - 2017

Projects & Funding

Projects & funding information is unavailable.

Publications (46)

• Ethical Artificial Intelligence in Business
  IEEE Intelligent Systems 2026 0 citations DOI: 10.1109/MIS.2026.3688455
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• South Asian biases in language and vision models
  Nature Machine Intelligence 2025 2 citations DOI: 10.1038/s42256-025-01144-1
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• Owls are Wise and Foxes are Unfaithful: Uncovering Animal Stereotypes in Vision Language Models
  TRENDS AND APPLICATIONS IN KNOWLEDGE DISCOVERY AND DATA MINING, PAKDD 2025 WORKSHOPS 2025 3 citations DOI: 10.1007/978-981-96-8197-6_31
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• Optimal Design of Car Side Impact Using Improved GA
  2025 1 citation DOI: 10.1007/978-981-96-0451-7_29
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• Investigating Gender Bias in Text-to-Audio Generation Models
  Proc. Interspeech 2025 2025
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• Gender Bias in Text-to-Video Generation Models: A case study of Sora
  Arxiv 2025
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• Beyond Specialization: Benchmarking LLMs for Transliteration of Indian Languages
  Arxiv 2025
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• A Systematic Literature Review for Investigating DevOps Metrics to Implement in Software Development Organizations
  Journal of Software: Evolution and Process 2025 5 citations DOI: 10.1002/smr.2733
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• Taxonomy of metrics for effectively estimating quantum software projects: A fuzzy-AHP based analysis
  Applied Soft Computing 2025 9 citations DOI: 10.1016/j.asoc.2025.112816
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• Gender Bias in Text-to-Video Generation Models: A Case Study of Sora
  IEEE Intelligent Systems 2025 9 citations DOI: 10.1109/MIS.2025.3561475
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