cv

Basics

Name Zoher Kachwala
Label PhD Candidate & Student Researcher in AI/ML
Url https://zoher15.github.io/
Summary PhD candidate and Student Researcher advancing the capabilities of frontier Large Language Models to solve large-scale, real-world challenges. My collaborative research drives scientific advancement in foundational AI systems through breakthrough technologies for semantic search and safe content generation, designing scalable decoding strategies, developing comprehensive evaluation frameworks for next-generation multimodal systems, and building production-ready moderation systems at scale.

Education

Publications

Work

  • 2022.08 - 2024.12
    Teaching Assistant
    Introduction to Network Science
    Led collaborative Python-based tutorials on large-scale network analysis; guided students through graph neural network concepts and dynamic analytics for real-world applications.
  • 2020.08 - 2020.12
    Teaching Assistant
    Applied Machine Learning
    Collaborated on PyTorch-based model development curriculum; emphasized reproducible research practices, scalable inference validation, and deployment-ready system design.
  • 2019.08 - 2021.12
    Teaching Assistant
    Elements of Artificial Intelligence
    Designed scalable autograding systems and provided collaborative support on foundational AI concepts including search, logic, and reasoning for 300+ students annually.
  • 2018.05 - 2018.08
    Technology Consultant Intern
    PricewaterhouseCoopers
    Collaborated on enterprise-scale data integration projects, focusing on automation of validation pipelines and scalable audit-ready logic modeling for large-scale systems.

Skills

Research Areas
Large Language Models
Generative AI
Multimodal Systems
AI Safety
Scalable ML
Foundational AI Systems
Next-Generation Intelligent Systems
ML Frameworks
PyTorch
Hugging Face
TensorFlow
Scikit-learn
Distributed Training
Programming
Python (expert)
C++
SQL
Bash
CUDA
Systems & Infrastructure
Git
Docker
Linux
Google Cloud Platform
Large-scale Computing
Research Methods
Collaborative Research
Model Evaluation
Benchmark Development
Reproducible Science
Large-scale Experimentation