Ms. Sania Khalid SCIT - BNU

Ms. Sania Khalid

Lecturer

School of Computer & IT (SCIT)

Sania Khalid is a Lecturer at SCIT, Beaconhouse National University, Lahore, specializing in Data Science, Machine Learning, cloud computing, DevOps, and intelligent systems. She has experience in system administration, production monitoring, and cloud infrastructure, and is engaged in teaching and research in MLOps, Kubernetes, and scalable system design.

Bio

Sania Khalid is a Lecturer at the School of Computer and Information Technology (SCIT), Beaconhouse National University (BNU), Lahore. She is a Data Science and Machine Learning professional with a strong focus on cloud computing, DevOps practices, and intelligent systems engineering.

She has experience in system administration, production monitoring, and cloud-native infrastructure management, along with academic involvement in teaching and research in areas related to MLOps, Kubernetes, and scalable system design.

Academics

  • MS Data Sciences, Punjab University College of Information Technology (PUCIT), Lahore
  • BS Computer Science, COMSATS Institute of Information Technology

Experience

  • L1 Support Engineer, Seamless Distribution Systems, Lahore (May 2024 – Sep 2024)
  • System Administrator, SudoBricks (Sep 2024)
  • Teaching Assistant, PUCIT Lahore (Fall 2024 – Spring 2025)

Research Experience

Researcher – Kubernetes Resource Management
CloudNet Lab, PUCIT Lahore

  • Working on intelligent resource scheduling and autoscaling in Kubernetes environments
  • Exploring OpenTelemetry-based observability and reinforcement learning-based autoscaling
  • Focusing on performance-aware scheduling and cloud optimization

Projects

  • Dockerized ML API Hosting – Deployed regression model with REST API for temperature forecasting using Docker & Python
  • Jenkins CI/CD Pipeline – Built CI/CD pipeline with Jenkins, Docker, and Git-based automation
  • MLFlow Model Management System – End-to-end ML lifecycle tracking, deployment, and API serving using MLFlow

Technical Skills

  • Machine Learning, Deep Learning, Data Analytics
  • Python, C++, JavaScript, HTML, CSS, SQL
  • Docker, Kubernetes, Jenkins, CI/CD
  • Prometheus, Grafana, Kibana, Nagios
  • MySQL, MongoDB, Data Warehousing, ETL
  • TensorFlow, PyTorch, Scikit-learn, Keras
  • OpenCV, Pandas, NumPy, Matplotlib, Seaborn
  • Linux, CLI, Git, GitHub
  • OpenAI API, MLOps Tools

Certifications

  • DevOps Prerequisite Course (Credential ID: QZKCWPNA0FKO)
  • Neural Networks and Deep Learning – DeepLearning.AI (T7KFXNSMGGNJ)
  • AWS Academy Cloud Foundations (H6kTTGUx)

Contact

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