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Nirav Shenoy

Relational ML Lab - CISPA

Master Thesis

  • Worked on building deep learning algorithms in the field of sparse neural networks.
  • My thesis was on the topic of Efficient Pruning: Combining Continuous Sparsification with Dynamic Sparse Training.
  • The focus of my research was on stabilizing training to increase the likelihood of producing lottery tickets in the ultra-sparse regime (above 99% sparsity) .

German Research Center for Artificial Intelligence (DFKI)

Researcher

  • QUASIM was a project based on applying graph-based quantum machine learning models for prediction and optimization tasks in industrial laser cutting simulations.
  • The results of our experiments are being submitted to the Quantum Machine Intelligence 2025.
  • Worked on ESCADE which focuses on energy efficient AI in the context of data centers
  • Presented to stakeholders at Hannover Messe ‘25
  • Our research was submitted to CAiSE 2025 under the Research Projects Exhibition track

KollegeAI

Lead Engineer

  • Startup where I was responsible for building a Generative AI chatbot that assists MBA candidates in India with their B-school applications
  • Implemented an RAG system that could help provide candidates with up to date and detailed information about the colleges that they were interested in applying to
  • Vector database includes up-to-date information of the top 200 B-schools in India

SAP Labs

Software Developer

  • Designed and implemented scalable cloud solutions for over 3600 customers using Java, Springboot, and HANA.
  • Led the Job Agency team in building a pilot end-to-end microservice using Docker and Kubernetes.
  • Modularized cloud application handling 25+ million requests per day into smaller services.
  • Reduced customer defects and security vulnerabilities for the Agency module by 50% over 6 months.