Abdallah Bashir

Abdallah Bashir

Applied Scientist II

Goldman Sachs

Biography

Hi! I am Abdallah. Welcome to my homepage. I am an Applied Scientist at the NLP Modleing team in Goldman Sachs. I have obtained my MSc degree in Computer Science from Saarland University. My thesis focuses on leveraging self-supervised learning in domain specific languge models. My research interests include solving real world NLP problems. I can be classified with high confidence as a coffeeholic Ambievert who loves to talk about comedy, travel (below images are my own), politics, and philosophy.

Download my resumé.

Interests
  • Machine Learning/Deep Learning.
  • Natural language processing (NLP).
  • Medical/ Financial NLP.
  • Large Langauge Models LLMs (pertaining, fine-tuning, synthesizing data).
  • Search (retrieval/ reranking).
Education
  • M.s in Computer Science, 2021

    Saarland University

  • B.S. in Electrical and Electronic Engineering, Software Engineering, 2018

    University of Khartoum

Experience

 
 
 
 
 
Applied Scientist II
Aug 2022 – Present London
  • Spearheaded the development and integration of advanced machine learning and deep learning models, with a focus on Natural Language Processing (NLP) and Large Language Models (LLMs). Trained and fine-tuned different classes of models for NLP usecases.
  • Innovated in areas such as retrieval and reranking, retrieval augmented generation (RAG), fine-tuning LLMs, text classification, named entity recognition, semantic parsing, and synthesizing training data to be used in various model training exercises. Significantly advancing the capabilities of LLMs in interpreting and processing human language for enhanced customer experiences.
  • Proficiently utilize Python, PyTorch, and distributed computing frameworks for efficient model training on GPU clusters. Design and maintain deployment pipelines with continuous integration, version control, and monitoring.
  • Comfortable diving into ambiguous problems by conducting extensive literature reviews to understand the state of the art at the time. Drive and implement solutions that address complex challenges, transforming research findings into production-ready code.
  • Achievements - Co-developed two patent-pending frameworks and implemented ML solutions that realized a cost reduction of 10M USD, demonstrating a direct impact on operational efficiency and innovation.
 
 
 
 
 
Applied Scientist Intern
Apr 2022 – Jul 2022 Seattle, WA
  • Using Transformers-based models, Implemented an end-to-end unsupervised framework to identify sensitive trending topics in Alexa traffic.
  • Achievements - the framework will increase the robustness of online sensitive detection models in Alexa by refining the quality of labeling data.
 
 
 
 
 
Research Intern
Jan 2022 – Mar 2022 Seattle, WA
  • Conduct research in Natural Language Proceeding Data Augmentation using Language models using LSTMs and Transformers
  • Implemented pipelines that leverage models like Albert and BART to extrapolate datasets with structured entities.
 
 
 
 
 
Applied Scientist Intern
Apr 2021 – Aug 2021 Frankfurt, DE
  • Curate, parse, preprocess data related to git projects in the organization.
  • Implementing Deep learning models with Attention to identify high risk changes in Git Software products.
  • Achievements - Implemented a Machine Learning based tool to help code reviewers to detect high risk changes in software product
 
 
 
 
 
Research Assistant
Nov 2019 – Mar 2021 Saarbrucken
  • Conducted groundbreaking research focused on integrating contextual understanding into neural language models through contrastive learning approaches.
  • Implemented models in diverse applications including healthcare, achieving significant reductions in model size and computation time while maintaining competitive accuracies.
  • Developed novel model architectures utilizing Knowledge Graphs to enhance model performance in NER and QA tasks across specialized domains.
 
 
 
 
 
Intern
Aug 2019 – Sep 2019 Düsseldorf
  • Ported Pydial 2.0 to Pydial 3.0 (an open-source statistical dialogue systems tool).
  • Achievements - Wrote and reviewed code for Experiments, unit tests, and evaluation of the porting process. ported the library with 0% errors.
 
 
 
 
 
Research Assistant
May 2019 – Jul 2019 Saarbrucken
  • Built an API to preprocess text data and get it in shape for modeling.
  • Achievements - trained Classifier by fine-tuning BERT to classify post machine translation errors.
 
 
 
 
 
Co-Founder, Software Engineer
Sep 2015 – Oct 2016 Khartoum
  • Gathered and defined customer requirements to develop clear specifications for creating well-organized project plans.
  • Designed, built, and monitored web/mobile applications and sites for continuous improvement.
  • Achievements - building a product in cooperation with Zain Sudan, the top telecommunication company in the country.

Accomplish­ments

Outstanding Paper Award at ACLing 2018
See certificate
Poster Award
won one of the poster awards presented in DLI 2018 for preseinting my bsc thesis research
Scientific Innovation Award for BSc Thesis
Indabax Sudan Organizer
Organized first Indabax Sudan event in Sudan
TEDxYouth@NileStreet organizer
Organized and led the team of TEDxYouth@NileStreet 2016

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