Hi there, I'm PINAKI 👋
I'm an Engineering Undergrad...an Embedded System, Machine Learning and Quantum Computing Enthusiast!!
- 💽 Firmware Engineer Intern at Western Digital
- 👨💻 Former research Intern at Indian Statistical Institute, Kolkata
- 🌱 Learning about Machine Learning and Quantum Computing
- 🕺 Former mentee at Quantum Open Source Foundation, worked on Research Project related to Implementation of Tensor Network on Quantum Machine Learning under the guidance of Dr. Amandeep Singh Bhatia
- Variational Quantum Classifiers Through the Lens of the Hessian
- Efficient Decoding of Surface Code Syndromes for Error Correction in Quantum Computing
- Towards the Realization of Regular Clocking Based QCA Circuits Using Genetic Algorithm
- Regular Clocking-based Automated Cell Placement Technique in QCA Targeting Sequential Circuit
- Systematic Cell Placement in Quantum-dot Cellular Automata Embedding Underlying Regular Clocking Circuit
1. Analysis, Prediction and Evaluation of Covid-19 Dataset using Quanvolutional Neural Network [Github Repo]
- Implemented concept of CNN using Quantum Circuit, also known as Quanvolutional Neural Net
- Created a classifier model to predict Covid19 or Viral Pneumonia from chest x-ray image
2. Generalizing MAXCUT problem for weighted graphs [Github Repo]
- Implemented QAOA algorithm to solve MAXCUT problem for Weighted Graphs
- Analyzed the impact on the result by increasing number of layers in Variational Ansatz
3. Loss landscape analysis of Quantum Neural Network [Preprint]
- Studying the character of loss landscape of QNN implemented on various datasets, including the analysis of Barren plateau and saddle point
- Analyzing effectiveness of gradient based optimization for Quantum Neural Net using Hessian matrix and Eigen vectors.
4. Cost Optimization Study in VQC [Github Repo] [Blog]
- Studying the effect of no. of layer repetitions in Variational Quantum Circuit on the Optimized Cost of the output StateVector.
- Implementing Gradient-free optimization technique using Pennylane
5. Deep learning model for Covid-19 and Viral Pneumonia Prediction using Chest X-Ray [Github Repo]
- This is a multi class classification RESNET9 model trained on a dataset containing chest x-ray of covid19, Pneumonia patient and normal person.
- Available dataset being not enough large, various data augmentation techniques has been implemented. Final model gives a validation accuracy of 87%
- Optimizing a Variational Quantum Circuit, studying the character of the optimized cost as a function of layers in the circuit
- Why only the train and test set is not enough for generalizing a ML model? Significance of Validation set
- PRAW — a python package to scrape Reddit Post data
- Hierarchical Extreme Quantum Machine Learning with Tensor and Neural Networks, NISQ Era - Pinaki Sen {Channel - Full-Stack Quantum Computation}
- HackerEarth | Qiskit India Challenge Experience by Pinaki & Shubham {Channel - QuantumComputing India}
- Quantum Machine Learning, Quantum Chemistry, Quantum Algorithm, Basics of Quantum Hardwares
- Frameworks - Qiskit, Pennylane, Cirq
- Supervised Learning, Unsupervised Learning, Deep Learing, CNN, GAN
- Frameworks - Pytorch, Tensorflow, Keras, scikit-learn, OpenCV, Matplotlib, Plotly
- Python, C/C++, MATLAB/OCTAVE
- Data Structures, Object Oriented Programming
