RWTH Aachen University
I work on running speech recognition models on synaptic memristor hardware, studying how the hardware’s analog behavior and noise affect the models.
I work on speech and machine learning, with a background in software engineering. I’m currently a research assistant at RWTH Aachen and an M.Sc. Data Science student.
My work spans speech recognition on analog hardware, speaker diarization, and training speaker recognition models. Before moving to Aachen, I worked on applied ML and software at ZS.
I work on running speech recognition models on synaptic memristor hardware, studying how the hardware’s analog behavior and noise affect the models.
I worked on speaker recognition and diarization: identifying speakers and determining who spoke when in a recording. This involved training models, experimenting with training data and clustering methods, and evaluating the results. I also worked on the software and experiment pipelines around these models.
I worked on machine learning applications for document processing, question answering, and healthcare analytics. My work included using language models to organize and retrieve information from documents, and building predictive models from healthcare and sales data.
I developed municipal web tools and a social network frontend, and maintained deployment pipelines.
I built web applications and a career recommendation system, working across frontend and backend development.
M.Sc. Data Science, RWTH Aachen
B.Tech Computer Science, Jamia Millia Islamia
I also helped found mSpace, a community connecting students and professionals from marginalized communities in India with education and employment opportunities.