Anas Zafar

Anas Zafar

Data Associate

Followers of Anas Zafar9000 followers
location of Anas ZafarKarachi Division, Sindh, Pakistan

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  • Timeline

  • About me

    Computer Vision & Deep Learning Enthusiast | Research Engineer at Retrocausal | Expertise in Computer Vision, NLP, and Reinforcement Learning

  • Education

    • National University of Computer and Emerging Sciences

      -
      Bachelor's degree Computer Science
    • University of Oxford

      2023 - 2023
      Oxford Machine Learning Summer School 2023

      Activities and Societies: Machine Learning Fundamentals, Machine Learning in Healthcare, Machine Learning in Finance - Statistical / probabilistic ML (e.g., Bayesian ML, causal inference, approximate inference, modeling uncertainty) - Advanced topics in representation learning (e.g., learning with little or no supervision, self-supervised learning, multi-modal representation learning) -Reinforcement learning -Graph neural networks, and deep learning -Computer vision -Knowledge graphs -Knowledge-aware ML

    • Massachusetts Institute of Technology

      2023 - 2024
      MicroMasters, Statistics and Data Science

      - Currently enrolled in the rigorous MIT MicroMasters program in Statistics and Data Science, focusing on mastering the foundations of these crucial fields.- Developing skills in creating and refining machine learning algorithms to handle complex, real-world data science problems.- Learning modern data analysis techniques to effectively leverage big datasets and transform them into actionable insights.- Gaining practical experience in analyzing big data, making data-driven… Show more - Currently enrolled in the rigorous MIT MicroMasters program in Statistics and Data Science, focusing on mastering the foundations of these crucial fields.- Developing skills in creating and refining machine learning algorithms to handle complex, real-world data science problems.- Learning modern data analysis techniques to effectively leverage big datasets and transform them into actionable insights.- Gaining practical experience in analyzing big data, making data-driven predictions through probabilistic modeling and statistical inference.- Acquiring proficiency in various data science tools and technologies, including Python and R, as part of coursework and project work. Show less

    • University of Cambridge

      -
      O levels
    • University of Cambridge

      -
      A Levels
    • University of Oxford

      2024 - 2024
      Oxford Machine Learning Summer School 2024

      Activities and Societies: MLx Representation Learning & Generative AI

  • Experience

    • Sehat Kahani

      Jun 2018 - Jul 2018
      Data Associate
    • Afiniti

      Jul 2020 - Sept 2020
      Intern
    • Engro Corp

      Jul 2020 - Oct 2020
      Data Science/ Machine Learning Intern
    • National University of Computer and Emerging Sciences

      Jan 2021 - Feb 2022
      Deep Learning Researcher

      Video Instance Segmentation, Human Tracking, Object Detection

    • VIDIZMO LLC

      Jul 2021 - Jan 2022
      Machine Learning Engineer
    • EEML

      Jul 2021 - Jul 2021
      Eastern European Machine Learning Summer School '21
    • Amazon Web Services (AWS)

      Jan 2022 - now
      Community Builder (Machine Learning)

      Generative AI, AWS Sage Maker, AWS Code Whisperer

    • Retrocausal

      Feb 2022 - now
      Research Engineer (Deep Learning)

      3D Human Pose Estimation, Human tracking, Ergonomic Analysis, Human Object Interaction

    • EEML

      Jul 2022 - Jul 2022
      Eastern European Machine Learning Summer School '22
    • McKinsey & Company

      Jul 2022 - Dec 2022
      McKinsey Forward Program
    • University of Illinois Urbana-Champaign

      May 2024 - Jul 2024
      Research Intern

      Advisors: Prof. Darko Marinov and Prof. Reyhaneh Jabbarvand- Conducted a large-scale empirical study on the effectiveness of large language models (LLMs) in automating code translation across five programming languages, revealing a success rate of only 2.1% to 47.3%, and identified 15 categories of translation bugs.- Proposed a prompt-crafting approach that improves LLM-based code translation accuracy by 5.5% on average, providing significant insights and a comprehensive bug taxonomy for advancing LLM-based code translation research. Show less

  • Licenses & Certifications

    • Introduction to Deep Learning in Python

      DataCamp
      Apr 2021
    • Deep Learning with PyTorch

      DataCamp
      May 2023
      View certificate certificate
    • Introduction to Natural Language Processing in Python

      DataCamp
      Apr 2021
    • Introduction to Data Visualization in Python

      DataCamp
      Apr 2021
    • Introduction to Data Science

      School of Data Science YDATA
      May 2022
    • Cleaning Data in Python

      DataCamp
      Feb 2021