Bikram Khanal
PhD student in Quantum Machine Learning and Quantum Computing.
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
Amazon.com IncApplied Scientist Intern
Applied Scientist Intern
Baylor UniversityGraduate Assistant
Research Assistant
Education
Baylor University
Baylor University
Troy University
Skills
Projects and Publications
Learning Robust Observable to Address Noise in Quantum Machine Learning
A framework for learning observables that are robust against noisy channels in quantum systems
Generalization Error Bound for Quantum Machine Learning in NISQ Era--A Survey
A Systematic Mapping Study (SMS) to explore the state-of-the-art generalization bound for supervised QML in NISQ-era and analyze the latest practices in the field
A Modified Depolarization Approach for Efficient Quantum Machine Learning
A modified representation for a single-qubit depolarization channel using two Kraus operators based only on X and Z Pauli matrices.
Quantum-Enhanced Representation Learning: A Quanvolutional Autoencoder Approach against DDoS Threats
A quantum-circuit based DDoS attacks analysis on time-series data.
Noise Evaluation on Variational Circuits
A thorough investigation of noise impact on quantum variational classification in the NISQ context over diverse dataset.
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.
Supercomputing leveraging Quantum machine learning
A simulation of rudimentary classical logical gates into quantum circuits considering AND, XOR, and OR gates.
Kernels and Quantum Machine Learning
A review on parameterized quantum circuit and kernel-based training of QML model.
Human Activities Classification
A evaluation on the performance of various machine learning algorithms in predicting human behavior.
Muzzle Matching for Cattle Identification
A non-invasive muzzle matching to address the challenges in insurance fraud and animal trading markets.
Automatic Grading of SQL Queries
A behavioral analysis of the machine learning model, particularly in terms of how it assigns grades to SQL queries.
Adversarial 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.