Bikram Khanal

PhD student in Quantum Machine Learning and Quantum Computing.

Waco, TX, USA

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About

I am a Quantum Computing and Quantum Machine Learning PhD candidate with an analytical mind and the ability to break down and solve complex problems. I have sound foundational knowledge in Quantum Computing, Machine Learning, Deep Learning, and Quantum Machine Learning algorithms. I have worked on various projects in the field of Adverserial Machine Learning, Program Synthesis, Fairness and Robustness, and Natural Language Processing. I have strong communication skills with a strong mathematical foundation on learning from data. I have an ability to learn new concepts and technologies quickly with a consistent record of meeting project deadlines.

Experience

Baylor University
Graduate Assistant

2021 - Present

Research Assistant

Assisted in the development and management of a tissue bank for alcohol research, specializing in bioinformatics, tissue tracking, and data integration across species and experimental protocols. Technologies: Django, Python, Docker, PostgresSQL

2020 - Present

Teaching Assistant

Assisted courses in C++ and Python Programming, Computer Architecture, Computing and Computer Fundaments, and Algorithms, to enhance student comprehension through lab tutorials and assessment development. My role involved close collaboration with professors in assignments and exam design, and direct support to students, contributing to improved academic outcomes in Computer Science and Data Science courses. Technologies: C++, Python, Latex, Jupyter Notebook, Canvas

Education

Baylor University

2020 - Present
PhD in Computer Science

Baylor University

2020 - 2023
Master's Degree in Computer Science

Troy University

2016 - 2020
Bachelor's Degree in Computer Science

Skills

Python
Latex
Machine Learning
Deep Learning
Natural Language Processing
PyTorch
Transformers
Tensorflow
Quantum Computing
Quantum Machine Learning
Qiskit
Pennylane
Quantum Algorithms
Django
Large Language Models
Docker

Projects and Publications

Noise Evaluation on Variational Circuits

A thorough investigation of noise impact on quantum variational classification in the NISQ context over diverse dataset.

Quantum Computing
Qiskit
Machine Learning
Quantum-Classical optimization

Quantum Machine Learning with Grover's Search

An Approach to reformulate the classification problem as a searching problem via Amplitude amplification technique using universal gates.

Quantum Machine Learning
Grover's Algorithm
Quantum Computing
Oracle Design

Supercomputing levaraging Quantum machine learning

A simulation of rudimentary classical logical gates into quantum circuits considering AND, XOR, and OR gates.

Grover's Algorithm
Oracle Design
Variational Quantum Classifier
NISQ Devices

Kernels and Quantum Machine Learning

A review on parameterized quantum circuit and kernel-based training of QML model.

Quantum Machine Learning
Clasical and Quantum Kernels
Kernel Methods
Reproducing Kernel Hilbert Space
Quantum Computing

Human Activities Classification

A evaluation on the performance of various machine learning algorithms in predicting human behavior.

Machine Learning
Human Activity Recognition
Machine Learning Algorithms

Muzzle Matching for Cattle Identification

A non-invasive muzzle matching to address the challenges in insurance fraud and animal trading markets.

Computer Vision
Image Processing
Convolutional Neural Networks
Fraud Detection

Automatic Grading of SQL Queries

A behavioral analysis of the machine learning model, particularly in terms of how it assigns grades to SQL queries.

Large Language Models
Natural Language Processing
Word Embeddings
Deep Learning

Adverserial example generation using white-box attach on text embedding

A white-box adversarial attack on text embedding vectors through encoder-decoder model to generate adversarial examples.

Large Language Models
Natural Language Processing
Word Embeddings
Adverserial Training
Latent Representation Perturbation