Shashank Singh

Shashank Singh is a professional involved in research and consultancy, currently self-employed. His background encompasses a strong focus on statistical machine learning, with significant experience in applying statistical models to enhance the understanding of machine learning algorithms. He is a postdoctoral researcher at the Max Planck Institute for Intelligent Systems in Tübingen, where he conducts research in the Empirical Inference Department. His academic credentials include a PhD in Machine Learning and Statistics from Carnegie Mellon University, where he was advised by Barnabás Póczos.1

Research Focus

Shashank's research primarily revolves around:

• Statistical Machine Learning: Developing statistical guarantees for various machine learning models, including Generative Adversarial Networks (GANs).
• Applied Machine Learning: He has worked on forecasting the effects of the COVID-19 pandemic and optimizing deep neural networks while at Google and Amazon.
• Computational Biology: Utilizing deep learning to predict gene interactions and modeling bacterial behavior through simulations.
• Psychology and Epidemiology: Engaging in probabilistic modeling to analyze developmental data in children and predicting disease spread.1

Professional Experience

Before his current role, Shashank held positions at notable organizations such as Google and Amazon, where he contributed to significant projects related to machine learning and data analysis. His work has implications across various fields, including biology, psychology, and epidemiology.1

In addition to his research role, Shashank Singh is also noted for his entrepreneurial ventures, leveraging his expertise in statistical analysis and machine learning for consultancy purposes. His LinkedIn profile indicates a commitment to innovative solutions in data science and analytics.23