Coursework

Duke University (Graduate)

• Generative Models (CS 590-01, Prof. Bhuwan Dhingra)
• Natural Language Processing (CS 572, Prof. Monica Agrawal)
• Machine Learning in Adversarial Settings (ECE 663, Prof. Neil Gong)
• Advanced Topics in Deep Learning (ECE 590-07, Prof. Vahid Tarokh)
• Introduction to Deep Learning (ECE 685D, Prof. Vahid Tarokh)
• Engineering Deep Neural Networks (ECE 590-02/ECE 661, Prof. Yiran Chen)
• Probabilistic Machine Learning (ECE 682D, Prof. Eric Laber)
• Vector Space Methods (ECE 586, Prof. Henry Pfister)

UNC Chapel Hill (Undergraduate)

Mathematics

• Numerical Techniques (PHYS 331)
• Physical Modeling (PHYS 358)
• Mathematical Methods I & II (ODEs II, Fourier Analysis, Partial Differential Equations, Complex Analysis) (MATH 529 & 529)
• Real Analysis (MATH 521)
• Linear Algebra (MATH 547)
• Ordinary Differential Equations (ODEs) (MATH 383H)
• Multivariable and Vector Calculus (MATH 233H)
• Probability (MATH 535)

Physics

• Quantum Mechanics I & II
• Quantum Computing
• Electromagnetism I & II
• Thermodynamics and Statistical Mechanics
• Cosmology
• Classical Mechanics
• Astrophysics
• Observational Astronomy/Astronomical Data
• Experimental Techniques