Sarvesh Kumar Yadav
Phd Scholar Applied Machine Learning for Astronomical Imaging @Aryabhatta Research Institute Of Observational Sciences
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WORK HISTORY
Phd Scholar Applied Machine Learning for Astronomical Imaging @Aryabhatta Research Institute Of Observational Sciences
Nainital, IN
Conducting research on deep learning applications in astronomy, focusing on transient detection and space-debris streak segmentation in wide-field telescope images.• Designing and implementing CNN-based models with attention mechanisms to automate image decontamination and preserve faint astrophysical signals.• Collaborating with astronomers, data scientists, and engineers to integrate ML models into real-time data-processing workflows for next-generation survey missions.• Exploring model interpretability, transfer learning, and MLOps practices to deploy reproducible, production-ready research pipelines.
EDUCATION
Aryabhatta Research Institute of Observational Sciences
Doctor of Philosophy - PhD, Astronomical Instrumentation
UPES
BTech - Bachelor of Technology, Aeronautics/Aviation/Aerospace Science and Technology, General
Bosscoder Academy
Master's degree, Data Science and Machine Learning
Univ.Ai
Master's degree, Data Science
ABOUT SARVESH KUMAR YADAV
Hello! I\'m Sarvesh Kumar Yadav, a PhD scholar at Aryabhatta Research Institute of Observational Sciences (ARIES), specializing in the application of Machine Learning and Deep Learning to solve data-intensive problems in Astronomy and Astrophysics.My research focuses on designing CNN- and transformer-based architectures for astronomical image analysis — including transient detection, streak segmentation, and data decontamination — enabling efficient and scalable pipelines for next-generation sky surveys.Beyond research, I’m deeply passionate about building end-to-end ML systems that bridge science and technology. I have hands-on experience with MLOps (MLflow, DVC, Jenkins, Kubernetes) and have deployed models on cloud platforms like GCP, working across domains from astronomical imaging to recommender systems and NLP-based generative models.With a foundation in Aerospace Engineering and a strong grasp of statistics and probability, I aim to pursue opportunities as a Machine Learning Engineer or Research Scientist, leveraging my expertise to build intelligent, data-driven solutions with real-world impact.I’m always open to collaborations and conversations in the areas of AI, ML, MLOps, and data-driven astronomy — let’s connect and explore ideas!
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