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Tal Schuster

PhD Student

CSAIL, MIT

Biography

I'm a Ph.D. student at MIT CSAIL and a member of the NLP and Learn To Cure groups. I'm fortunate to be advised by Prof. Regina Barzilay.

Currently, I focus on developing ML and NLP methods to improve the robustness of models, prevent undesired outcomes, and increase their performance in challenging and realistic scenarios.
I have also worked on developing deep learning screening-based methods to improve cancer detection and risk assessment.

Before coming to MIT, I was an MSc student in the Computer Science Dep. at Tel-Aviv University, advised by Prof. Lior Wolf.

Interests

  • Machine Learning
  • Natural Language Processing
  • Computer Vision

Education

  • PhD in Computer Science, in progress

    Massachusetts Institute of Technology

  • MSc in Computer Science, 2017

    Tel Aviv University

  • BSc in Mathematics and Computer Science

    Ben-Gurion University

Projects

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Conformal Prediction

Predicting with confidence estimates

Word Embeddings

Dense representations of words

Fake News

Misinformation detection

Medical

Deep learning for cancer risk prediction

Metric Learning

Deep metric learning

More Publications

Few-shot Conformal Prediction with Auxiliary Tasks

2021.

PDF Project

Exploiting Rules to Enhance Machine Learning in Extracting Information From Multi-Institutional Prostate Pathology Reports

In American Society of Clinical Oncology Journal (JCO), 2020.

PDF Project

Distilling the Evidence to Augment Fact Verification Models

In Workshop on Fact Extraction and VERification (FEVER workshop at ACL), 2020.

PDF Project

The Limitations of Stylometry for Detecting Machine-Generated Fake News

In Computational Linguistics, 2020.

PDF Dataset Project News article

Humpty Dumpty: Controlling Word Meanings via Corpus Poisoning

In IEEE Symposium on Security and Privacy (IEEE S&P), 2020.

PDF Project Video

Automatic Fact-guided Sentence Modification

In AAAI Conference on Artificial Intelligence (AAAI), 2020.

PDF Code Project News article

Teaching

TA: 6.883 - Modelling with Machine Learning

Syllabus