Services

Professional services and community involvement.

Undergraduate Teaching — Data Science

2024

Course Instructor

Taught core data science concepts including data preprocessing, exploratory data analysis, feature engineering, model evaluation, and project-driven problem solving using Python and industry-relevant tools.

UndergraduateData Science

Undergraduate Teaching — Machine Learning

2024

Course Instructor

Guided students through supervised and unsupervised learning techniques, covering regression, classification, clustering, and model optimization with practical implementation in real-world datasets.

UndergraduateMachine Learning

Undergraduate Teaching — Deep Learning

2024

Course Instructor

Introduced neural networks, CNNs, RNNs, and modern deep learning workflows, enabling students to build and train models using frameworks such as TensorFlow and PyTorch.

UndergraduateDeep Learning

Undergraduate Teaching — Quantum Computing

2024

Course Instructor

Taught foundational principles of quantum computation including qubits, superposition, entanglement, and basic quantum algorithms with hands-on programming using Qiskit.

UndergraduateQuantum Computing

Undergraduate Teaching — Diffusion & Generative Models

2024

Course Instructor

Introduced students to generative AI concepts including diffusion models, representation learning, latent space modeling, and practical experimentation with image and text generation tasks.

UndergraduateGenerative AIDiffusion Models

Undergraduate Teaching — Large Language Models

2024

Course Instructor

Taught concepts related to transformers, embeddings, attention mechanisms, prompt design, and applied workflows for building and evaluating large language model applications.

UndergraduateLLMArtificial Intelligence

Undergraduate Teaching — Statistics for AI

2024

Course Instructor

Covered core statistical foundations including probability, hypothesis testing, estimation methods, regression analysis, and their applications in data-driven modeling and machine learning.

UndergraduateStatisticsData Science

Undergraduate Teaching — Linear Algebra for Machine Learning

2024

Course Instructor

Introduced matrix algebra, vector spaces, eigenvalues, singular value decomposition, and their role in optimization, representation learning, and deep learning architectures.

UndergraduateLinear AlgebraMachine Learning