I am Anand Kumar Rai, a 4th Year Part-time PhD in the Department of Computer Science and Engineering at the Indian Institute of Technology Kharagpur, advised by Prof. Animesh Mukherjee. My primary research interests lie in Fairness in Speech Technologies, particularly Automatic Speech Recognition (ASR), with an emphasis on measuring, understanding, and mitigating demographic disparities in real-world systems.

My research is motivated by the growing deployment of algorithmic systems in high-impact societal settings. I focus on developing fairness-aware, explainable, and evaluation-driven approaches for speech recognition, ensuring that such systems do not reinforce or amplify biases against underrepresented groups. My work has resulted in publications at leading venues including ICWSM, ICKG, and Interspeech.

I received my Master’s degree (M.Tech.) in Data Science from IIT Hyderabad, where I was advised by Dr. Maunendra D. Desarkar. During this period, my M.Tech project was focused on Text-to-SQL generation, where I developed an attention-based Seq2Seq model trained on template-augmented natural language–SQL pairs. I earned my B.Tech. in Computer Science and Engineering from IIITDM Jabalpur in 2012, securing second rank in the graduating class.

I have accumulated over 13 years of professional experience spanning industry and government, having worked at Amada Co. Japan, AmadaSoft India Pvt Ltd, and the Joint Plant Committee, Ministry of Steel, Government of India. My roles involved developing analytical dashboards, APIs, and software tools, as well as applying machine learning and natural language processing to real-world problems. This experience grounds my research in practical deployment constraints and large-scale data challenges. I am also a recipient of the UGC Junior Research Fellowship (JRF) in 2021.

I am actively seeking research scientist and applied research roles in industrial or academic research labs, where I can contribute to advancing Fairness in AI and Speech Technologies. I welcome opportunities for collaboration on research aimed at building inclusive, trustworthy, and responsible AI systems.