Faculty Cover
Dr. Oshin Sharma
10 Yrs
Teaching Experience
10 Yrs
Total Experience
Ph.D.
Highest Qualification
23+
Published Works

About & Biography

I am Dr. Oshin Sharma, an Associate Professor in Department of Computer Science and Engineering, SRMIST Delhi-NCR Campus with around 10 years of teaching and academic experience. My research experience primarily lies in Cloud, Fog and Edge Computing, with a focus on resource optimization, task scheduling, VM consolidation, VM and container placement, energy efficiency, latency and SLA-aware computing. With around 10 years of teaching experience, I follow a student-centric and application-oriented approach. I simplify complex concepts through real-life examples, problem-solving, demonstrations, coding exercises and hands-on laboratory activities. I also encourage students to ask questions, think critically and develop solutions independently rather than relying only on memorization

Education & Qualifications

Doctorate2018
Ph.D.
CSE/ Cloud Computing
Jaypee University of Information & Technology, Waknaghat, Solan, HP, India
Masters2013
M.E.
CSE
Chitkara University , Solan ,HP
Bachelors2012
B.E.
CSE
CHITKARA UNIVERSITY, HP

Research Specialization & Focus Areas

  • Artificial Intelligence
  • Cloud Computing
  • Machine Learning
  • My recent research focuses on AI/ML-driven optimization in edge/fog environments
  • including dynamic container placement and migration
  • with objectives such as energy consumption

Scholarly Publications

23 publications
2026
01

AI driven workflow scheduling in dynamic edge environments using jacobi identity based deep neural network and multi criteria optimization

Discover Computingpeer-reviewed, Scopus/SCI

02

Fuzzified efficient UNet model with conditional random field for semantic segmentation of Alzheimer’s from brain MRI

Discover Computingpeer-reviewed, Scopus/SCI

2025
03

A stacked ensemble deep learning framework for Alzheimer’s severity ranking and classification using MRI scans

Neural Computing and Applicationspeer-reviewed, Scopus/SCI

04

A patch- intuited dense deep network for classification of breast cancer using microscopic imaging

Neural Computing and Applicationspeer-reviewed, Scopus/SCI

05

Taylor-based smart flower optimisation algorithm with the deep residual network to predict mechanical materials properties

Optimal Control Applications and Methodspeer-reviewed, Scopus/SCI

2024
06

Adam Ladybug Beetle Optimisation enabled multi- objective service placement strategy in fog computing

Concurrency and computation: Practice and Experiencepeer-reviewed, Scopus/SCI

Honors, Awards & Recognitions

  • ACADEMIC EXCELLENCE AWARD

    2026

    SRMIST

  • WOMEN WORTH AWARD

    2024

    SRMIST

  • BEST TEACHER AWARD

    2023