Mohammad-Mosaffa - My name is Mohammad!

My name is Mohammad Mosaffa, and currently I am a PhD student at the Johnson School of Business at Cornell University, specializing in Quantitative Marketing. Also, I hold a Master of Science of Mathematics at University of British Columbia (UBC) majoring in Statistical Machine Learning. I was advised by Dr. Ardestani and Prof. Tavakoli. Before that, I was a B.Sc. student in Industrial Engineering at the Amirkabir University of Technology majoring in Data Analysis, under the supervision of Dr. Ahmadi-Javid, and I worked on a novel fair task allocation in service systems. Also, before starting my career in university, I was honored to be a student of the National Organization for Development of Exceptional Talents (NODET) as for both middle and high school.

In my opinion, business analytics and all its relevant topics are formed according to the necessity of being optimal based on analyzing the systems and data. I have always been passionate about Applied Machine Learning and Text Mining, especially combining these approaches for solving real-world problems. To be more specific, I have a burning passion for researching practically that can unravel difficulties in the world, by focusing on Service Systems, Healthcare Systems, and Marketing!

Also,
I have an INFJ-A personality, which I believe can describe me almost.
And, you can see my top soft skills through test results from Plum.

Bachelor Thesis

Data Analysis and Fair Job Allocation in a Company Offering Electronic Equipment Repair Services

Research 1 (Working)

A Novel Online Fair Task Allocation Using Intelligence Randomized Assignment: Machine Learning Approach

Research 2 (Revision)

The Value of Text for Waiting Time Prediction Using Deep Learning: A Repair Shop Case Study (Service Science - Under Review)

Research 3 (Accepted)

Integration of Text-Mining and Telemedicine Appointment Optimization (Annals of Operations Research - Accepted)

A graduate course final project

A novel Convolutional Neural Network Architecture for distinguishing Pneumonia: X-ray Images processing approach

Reinforcement Learning Specialization

25/01/2022

(1- Fundamentals of Reinforcement Learning) (2- Sample-based Learning Methods) (3- Prediction and Control with Function Approximation) (4- A Complete Reinforcement Learning System (Capstone))

DeepLearning.AI TensorFlow Developer

21/04/2021

(1- Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning) (2- Convolutional Neural Networks in TensorFlow) (3- Natural Language Processing in TensorFlow) (4- Sequences, Time Series and Prediction)

Deep Learning Specialization

04/03/2021

(1- Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization) (2- Neural Networks and Deep Learning) (3- Convolutional Neural Networks) (4- Structuring Machine Learning Projects) (5- Sequence Models)

Comprehensive Data Science course with practical case studies and a final real project

11/04/2020

(1- Introduction to R & Python programming and Regression and multi regression in R) (2- Advance regressions, deep learning and times series with Python) (3- Classifiers, Associations rules and multi variable models with Python) (4- Natural language processing) (5- Advance visualization with Seaborn and Matplotlib in Python) (6- Database management systems with SQL server)