Dr. Junaid Farooq

PhD (Artificial Intelligence), National Institute of Technology Srinagar

Hi, I'm Junaid

Welcome to my website.

I am an engineer, researcher, and technology enthusiast. I have bachelors and masters degrees in Engineering from National Institute of Technology (NIT) Srinagar. Recently, I completed a PhD degree in Artificial Intelligence from NIT Srinagar under the supervision of Prof. Mohammad Abid Bazaz.

My research work mainly involves development and integration of various artificial intelligence and deep learning techniques to achieve advances in computational intelligence with applications in NLP, generative modelling, and machine learning.

I strongly believe that the future of technology will be at the intersection of artificial intelligence and human intelligence.

Areas of Interest: Artificial Intelligence, Deep Learning, Machine Learning, Large Language Models, Generative Modeling,

Programming Skills: Python, Matlab & Simulink, C++, SQL

AI/NLP/CV/Data Science related tools: Pytorch Langchain OpenAI Tensorflow Keras Rasa DialogFlow NLTK Numpy Scipy Sckikit-learn Pandas Matplotlib AWS OpenCV Cuda Docker

Current Role:

Senior Machine Learning Engineer & Head of Artificial Intelligence, StartUs Insights, Vienna, Austria

Previous Roles:

Machine Learning Engineer and Head of Research, Genie AI, Toronto, Canada
AI Research Scientist, Quantum AI Global, India
Senior Research Fellow, Electrical Engineering Department, National Institute of Technology Srinagar, India
Automation Engineer, ETA Group of Comapanie, Dubai, UAE

Education:

PhD, Artificial Intelligence
Masters, Electrical Engineering
Bachelors, Electrical Engineering

Snapshots from Public Defense of PhD thesis at NIT Srinagar (24 April, 2024)

🚀 Exciting News! My Book is Now Live on Amazon! 📖💡

I am thrilled to announce the launch of my book, “The Art of Code: Tactics and Principles for Clean Architecture”!

As developers, we often write code that works—but does it stand the test of time? Does it remain scalable, maintainable, and elegant as projects grow? In this book, I explore the principles, patterns, and tactics that elevate software architecture from functional to truly exceptional.

Watch PhD Thesis Defense of Dr. Junaid Farooq

Latest Publications

Farooq, Junaid, Danish Rafiq, Pantelis R. Vlachas, and Mohammad Abid Bazaz. "RefreshNet: Learning Multiscale Dynamics through Hierarchical Refreshing." Nonlinear Dynamics (2024). doi.org/10.1007/s11071-024-09813-3
Junaid Farooq & Mohammad Abid Bazaz, "Deep Learning for Self-tuning of Control systems," 2021 International Conference on Emerging Techniques in Computational Intelligence (ICETCI), 2021, pp. 6-11, doi.org/10.1109/ICETCI51973.2021.9574048. (IEEE Computational Intelligence Society) [Received Best Paper Award] https://ieeexplore.ieee.org/document/9574048
Junaid Farooq & Mohammad Abid Bazaz. (2020). A novel adaptive deep learning model of Covid-19 with focus on mortality reduction strategies. Chaos, Solitons & Fractals, 138, 110148. doi.org/10.1016/j.chaos.2020.110148
Junaid Farooq & Mohammad Abid Bazaz. (2021). A Deep Learning algorithm for modeling and forecasting of COVID-19 in five worst affected states of India. Alexandria Engineering Journal, 60(1), 587-596 doi.org/10.1016/j.aej.2020.09.037
Danish Rafiq, Junaid Farooq, & Mohammad Abid Bazaz .(2022) Synergistic use of Intrusive and Non-intrusive Model Order Reduction Techniques for Dynamical Power Grids. International Journal of Electrical Power & Energy Systems, 138, 107908, doi.org/10.1016/j.ijepes.2021.107908

Latest Updates:

Paper Published: RefreshNet: learning multiscale dynamics through hierarchical refreshing
PhD Thesis Defended: I successfully defended my PhD thesis in Artificial Intelligence on 24th April, 2024, at NIT Srinagar.
Best Presentation Award conferred to Junaid Farooq and Muhamad Abid Bazaz for their paper entitled "Multiscale Autoencoder-RNN Architecture for Mitigating Error Accumulation in Long-Term Forecasting" at the “International Conference on Emerging Techniques in Computational Intelligence (ICETCI 2023)” organized by IEEE Computational Intelligence Society and Mahindra University in collaboration with NVIDIA and Tech Mahindra at Hyderabad from 21-23 September, 2023.
Paper Published: Hybrid Deep Neural Network for Data Driven Missile Guidance with Maneuvering Target
Best Paper Award conferred to Junaid Farooq and Muhamad Abid Bazaz for their paper entitled "Deep Learning for Self- Tuning of Control Systems" at the “International Conference on Emerging Techniques in Computational Intelligence (ICETCI 2021)” organized by IEEE Computational Intelligence Society and Mahindra University in collaboration with NVIDIA and Tech Mahindra at Hyderabad from 25-27 August 2021.
New Blog Post: Resources for learning AI & ML
New Blog Post: How to start a career in AI?

Page updated

Google Sites

Report abuse