Skills
Quantum Machine Learning and Optimization
Parameterized Quantum Circuits (PQC)
Variational Quantum Eigensolver (VQE)
Quantum Approximate Optimization Algorithm (QAOA)
Quantum Support Vector Machines (QSVM)
Quantum Kernels
Open Quantum Systems with Lindblad Equation
Open Quantum Systems
Quantum Fisher Information (QFI) Estimation
Non-unitary Evolution
Decoherence Modeling
Quantum Classical and Hybrid Architectures
Quantum Error Correction (QEC)
Quantum Error Mitigation (QEM)
Quantum Error Avoidance
Quantum Neural Networks (QNNs)
Quantum Search and Optimization
Linear Algebra-based Quantum Algorithms
Quantum Classification and Regression
Langfuse
Helicone
Comet
PyTorch
Tensorflow
Keras
scikit-learn
H2O AutoML
MLflow
PyCaret
HuggingFace Transformers
sentence-transformers
torchtext
keras-nlp
spaCy
nltk
Gensim
textblob
Feature Engineering
Statistical Techniques
pandas
Polars
NumPy
collections
re
string
matplotlib
seaborn
FastAP
Git
Github
GltLab
mne
mne-bids
About
I recently work on the theme of Quantum Error Correction (QEC) and Quantum Information Systems (QIS) with flow patterns as Ph.D Researcher. As a Software Engineer, I enjoy to observe the consequences of algorithmic differences between various applications.
My Ph.D thesis is on the theme of Quantum Information Systems and Information Flow patterns. Hence, it is highly significant to deal with Quantum Error Correction (QEC), Quantum Error Mitigation (QEM), and Quantum Error Avoidance. Since Information System Patterns in Quantum realm are highly vulnerable to errors, these topics constitute an important place.
I enjoy algorithm development and Quantum-theoretic conversations.