Experience and Skills

CE959: Deep Generative Models

• This course was instructed by Dr. Beigy in Spring of 2025. I helped design and grade the quiz and assignment on Normalizing Flows.

CE846: Security and Privacy in Machine Learning

• This course was instructed by Dr. Sadeghzadeh in Fall of 2025. I helped design and grade the first assignment on Adversarial Attacks and Universal Adversarial Perturbations. I also edited some of the slides on adversarial attacks and defenses against adversarial examples.
• This course was instructed by Dr. Sadeghzadeh in Fall of 2024. I helped design and grade the third assignment on Defenses against Adversarial Examples and Black-Box Attacks, as well as the fourth assignment on Data Poisoning and Model Extraction.

CE716: Reinforcement Learning

• This course was instructed by Dr. Rohban in Spring of 2026. I helped with the theoretical assignment of Policy-Based methods, as well as the assignment on Bandits.
• This course was instructed by Dr. Rohban in Spring of 2025. I designed and conducted the workshop session on Model-Based Reinforcement Learning covering topics such as Dyna-Q, Monte Carlo Tree Search (MCTS) and the Cross-Entropy Method (CEM). I was also responsible for designing and grading the homework assignments on Model-Based Reinforcement Learning.
• This course was instructed by Dr. Rohban in Spring of 2024. I designed and graded the practical section of the second assignment, which covered Monte Carlo Methods, Temporal Difference Methods, Eligibility Traces, and Deep Q-Networks (DQN). Additionally, I graded theoretical problems from the third assignment on Policy Gradient Methods and the fourth assignment on Model-Based Reinforcement Learning and Multi-Armed Bandits. I was also tasked with grading half of the midterm exam problems.

CE719: Deep Learning

• This course was instructed by Dr. Soleymani in Spring of 2025. I helped design and grade the assignment on Optimization and Regularization.
• This course was instructed by Dr. Beigy in Fall of 2023. I helped design and grade the assignments on Deep Reinforcement Learning and Deep Generative Models.

CE616: Advanced 3D Computer Vision

• This course was instructed by Dr. Kasaei in Fall of 2024. I helped design the fourth assignment on Keypoint Description, and Keypoint Matching.

CS999: Generative Models

• This course was instructed by Dr. Seyyedsalehi in Fall of 2025. I designed and graded the Flow Matching and Stochastic Differential Equations parts of the third assignment.
• This course was instructed by Dr. Seyyedsalehi in Fall of 2024. I was the head of the team responsible for designing the first assignment on Structured Density (Probabilistic Graphical Models) and Causality and Causal Models which had a theoretical and a practical component. I was also part of the team responsible for designing the fourth assignment which was focused on Energy Based Models.

CS828: Machine Learning Theory

• This course was instructed by Dr. Seyyedsalehi in Spring of 2024. I wrote the lecture notes on Generalization and Decision Trees.

EE120: Deep Generative Models

• This course was instructed by Dr. Amini in Fall of 2025. I helped with designing the projects on the applications of generative models in Adversarial Robustness and Privacy.
• This course was instructed by Dr. Amini in Fall of 2024. I designed and graded the second practical assignment on Variational Autoencoders (VAE).

CE477: Machine Learning

• This course was instructed by Dr. Sharifi-Zarchi in Fall of 2024. I created educational content on Neural Networks from Scratch, Neural Networks with PyTorch, Convolutional Neural Networks from Scratch, Residual Networks and Transfer Learning, AutoEncoders, and Vision Transformers.
• This course was instructed by Dr. Motahari and Mr. Malekzadeh in Spring of 2024. I was the head of the team responsible for designing and grading the first theoretical assignment which focused on Linear Regression, Lasso & Ridge, Bias-Variance Tradeoff, and KNN.
• This course was instructed by Dr. Jafari-Siavoshani in Fall of 2023. I helped design and grade the first theoretical assignment.

CE417: Artificial Intelligence

• This course was instructed by Dr. Rohban in Fall of 2024. I helped design and grade the first theoretical assignment on Search Algorithms.

CE282: Linear Algebra

• This course was instructed by Dr. Sharifi-Zarchi in Fall of 2023. I was responsible for creating jupyter notebooks containing course materials.

CE181: Engineering Probability and Statistics

• This course was instructed by Dr. Najafi in Fall of 2024. I was part of the team responsible for designing and grading the first practical assignment which focused on Random Variables, Probability Distributions and Statistical Measures, Joint and Conditional Distributions of Random Variable.
• This course was instructed by Dr. Najafi in Spring of 2024. I was the head of the team responsible for designing and grading the fifth theoretical assignment which focused on Point Estimation, Interval Estimation, Maximum Likelihood Estimation, Mean Squared Error, Confidence Interval, Bias & Variance.
• This course was instructed by Dr. Najafi in Fall of 2023. I was responsible for designing one of the theoretical assignments as well as validating two of the other assignments. I was also responsible for designing and grading parts of the practical assignment.

EE737: Introduction to Machine Learning

• This course was instructed by Dr. Amini in Fall of 2025. I helped design and grade the assignment on Statistics, Linear Algebra, and Optimization.

DS16: Principles and Techniques in Data Science

• This course was instructed by Dr. Fazli in Winter of 2024. I designed and graded the fifth assignment which focused on Modeling, Regularization, Bias/Variance, and Feature Engineering. Additionally, I designed problems for the final exam from the aforementioned topics.

AI14: Machine Learning

• This course was instructed by Dr. Motahari in Winter of 2024. I designed the third assignment which focused on Decision Trees, Random Forests, Ensemble Learning, and Bagging.

AI12: Mathematics for Artificial Intelligence and Data Science

• This course was instructed by Dr. Najafi in Fall of 2023. I designed and graded some of the theoretical assignments, for the Linear Algebra, Multivariable Calculus, and Optimization sections of the course.

Algorithmic Creativity and Programming in Python

• This course was instructed by Dr. Sharifi-Zarchi in Summer of 2023. I was responsible for conducting two problem sessions every week for the duration of this course covering topics such as python programming, combinatorics, sorting algorithms, induction and greedy algorithms, game theory and combinatorial games, graph theory and graph algorithms, recursion and recursive programming, and dynamic programming.