About

Hi, I am Samyadeep Basu, a 1st year CS PhD student at UMD, College Park (2022 - Present). I work with Soheil Feizi in the Center for Machine Learning. My research focus is to learn from data with limited supervision (few-shot learning) and model interpretability (how to understand decision making process of deep networks). Previously I received my MS from UMD in 2020 and then spent close to two years at Microsoft AI in the ML rotation program. During my stint at Microsoft AI, I worked with the Language Science Team at Azure AI and MSAI where I researched, developed and deployed large-scale language models for various scenarios.

News

(September 2022): Finished an amazing research internship at Microsoft Research working with Daniela Massiceti on few-shot learning!

(Feb 2022): Started my PhD to work on few-shot learning and model interpretability!

Publications

  1. Hard Meta-Dataset++: Towards Understanding Few-shot Performance on Difficult Tasks (Under Review)
  2. Strategies to Improve Few-Shot Learning for Intent Classification and Slot Filling (NAACL 2022 (Suki Workshop))
  3. Influence Functions in Deep Learning are Fragile (ICLR 2021)
  4. On Second-Order Group Influence Functions for Black-Box Predictions (ICML 2020)
  5. Membership Model Inversion Attacks for Deep Networks (NeurIPS 2020 - Workshop)

Other

  1. Topic Segmentation in the Wild: Towards Segmentation of Structured and Unstructured Data (NeurIPS 2022 - ENLSP)