Sriranjani Ramakrishnan

Research Engineer

Sriranjani Ramakrishnan is a Research Engineer working in the text and graph analytics area within the Data Analytics Lab at Conduent Labs India. Her research interests lie in the domain of machine learning, deep learning, transfer learning and other applied areas related to these domains like speech and text. At Conduent Labs India, Sriranjani has worked on cross-domain sentiment classification using transfer learning and deep learning techniques. She is currently working on failure prediction using vehicle maintenance data and in healthcare projects involving data analytics. Her broader vision is to apply machine learning techniques for real-world problems involving speech and text. Sriranjani believes in learning from everyone, which helps to develop her research skills and working on challenging projects both within and outside Conduent labs, including academia.

Prior to joining Conduent in 2015, Sriranjani completed her Master’s at IIT Madras. Her thesis work was on improving the performance of automatic speech recognition systems for disordered speech. She has also worked on the DIT consortium project on building speech recognition system for Indian languages, aimed at fetching price information for agricultural commodities. She started her career as a software engineer at Tata consultancy services. Apart from research, Sriranjani is interested in reading books, playing badminton, participating in CSR activities. She has 3 publications and one filed patent application to her credit.


• Email: Sriranjani [dot] Ramakrishnan [at] conduent [dot] com

  • • Sriranjani R, Umesh S, Reddy MR “Automatic Severity Assessment of Dysarthria using State-Specific Vectors", Biomedical sciences instrumentation. 2015 Apr;51:99-106.

  • • Sriranjani R, S Umesh and M Ramasubba Reddy. “Pronunciation Adaptation For Disordered Speech Recognition Using State-Specific Vectors of Phone-Cluster Adaptive Training", Speech and Language Processing for Assistive Technologies (SLPAT) 2015

  • • “Learning Transferable Feature representation using neural networks” Patent Application Filed, 2016.