# Nitish Kumar - AI/ML Technical Lead | Computer Vision & Signal Processing Specialist
Source: https://hello.cv/kumarnitish
Bengaluru

## Links
- LinkedIn | https://www.linkedin.com/in/nitishkumar07/
- Email
- Phone

## About
AI/ML Technical Lead with over 7 years of experience specializing in computer vision, deep learning, and signal processing for semiconductor and defense applications. Proven track record of designing and deploying production-ready algorithms, achieving 90%+ accuracy in image registration and 100% detection rates in real-time intrusion systems. Eager to leverage deep expertise in Python, TensorFlow, and PyTorch to drive innovation in applied AI for cutting-edge industries.

## Work
### Algorithm Developer (Technical Lead) | Applied Materials
Led the development and deployment of advanced AI/ML algorithms to optimize semiconductor inspection and manufacturing processes, driving innovation in materials engineering solutions.
- Developed Deep Reinforcement Learning (DRL) algorithms with PyTorch, automating CAD-to-SEM image registration and eliminating manual calibration in semiconductor inspection, significantly increasing throughput.
- Automated simulation parameter tuning using Optuna, resulting in a 40% reduction in manual calibration time and substantial improvements in on-site operational efficiency.
- Engineered an automated ROI detection algorithm for 3D NAND metrology, utilizing signal and image processing to identify nitride band centers with 3 µm precision, reducing manual effort and error.
- Implemented an ML-based classifier with Scikit-Learn and Python, achieving over 80% accuracy in automatically selecting optimal registration scores and differentiating successful from poor cases.
- Enhanced coarse edge extraction accuracy by over 90% using Elastix and ITK-based registration algorithms in Python, critical for high-precision manufacturing metrology.
- Prototyped a GAN-based image inpainting solution using PyTorch, significantly improving defect-repair performance and accelerating R&D project timelines.
- Collaborated with international cross-functional teams across Israel, USA, and India to successfully deploy advanced AI/ML solutions in global facilities.
- Integrated complex algorithms into production environments via CI/CD pipelines, adhering to Low-Level System Design principles for scalable and robust software delivery.
### Scientific Officer | Bhabha Atomic Research Centre (BARC)
Served as a Scientific Officer, leading research and development in signal processing and machine learning for defense-grade security and atomic energy applications.
- Engineered DSP-FPGA-based algorithms using Wavelet and C++ for triboelectric sensor intrusion detection, achieving 100% detection and over 90% classification accuracy.
- Developed phase demodulation algorithms for fiber-optic PIDS using advanced Signal Processing in MATLAB, improving intrusion localization accuracy to within ±50 meters.
- Applied Teager-Kaiser Energy Operator (TKEO) and Discrete Wavelet Transform (DWT) for robust feature extraction, integrating with ML models in Python for real-time signal analysis under strict computational constraints.
- Built and validated Simulink models in MATLAB for high-voltage energizer systems, streamlining prototyping cycles and accelerating development by 30%.
- Optimized embedded signal-processing code in C++ for low-memory, real-time execution, enhancing performance in critical defense-grade security applications.

## Education
### Homi Bhabha National Institute | Electrical Engineering (Nuclear Engineering)
### Jabalpur Engineering College | Electrical Engineering

## Awards
### Best Paper Award
5th IEEE International Conference on Computing, Communication and Security (ICCCS 2020, IIT Patna) | 2020-01-01
Awarded for the paper 'Event Detection and Classification Algorithm using Wavelet and Machine Learning Technique for Vibration Fence PIDS', published in IEEE ICCCS 2020 (DOI: 10.1109/ICCCS49678.2020.927745).

## Skills
### Programming
- Python
- C++
- MATLAB
- Data Structures & Algorithms
- OOP
- Low-Level System Design
### ML/AI
- TensorFlow
- PyTorch
- Scikit-Learn
- Deep Learning
- Machine Learning
- Transfer Learning
- CNNs
- GANs
- Regression
- Predictive Modelling
### Tools/Frameworks
- OpenCV
- Optuna
- Elastix
- ITK
- Simulink
- Git
- MLOps
- AWS
- GCP
- Azure
### Signal & Image Processing
- Wavelets
- TKEO
- DWT
- DSP
- Image Registration
- Feature Extraction
- Object Detection
- Image Segmentation

## Projects
### Solid-State Electron Gun Modulator Simulation
Simulated a solid-state electron gun modulator.
### Hybrid Energy Management System Development
Developed an optimal hybrid energy management solution during B.E.
### Electrical Maintenance Internship (NTPC Vindhayachal)
Completed a 45-day internship in the Electrical Maintenance Department.

## Source
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