Hossein E
- Research Program Mentor
PhD at Purdue University
Expertise
Data Science, Engineer, Statistics, Math, Design Products, engineering design process, user experience design and research, toy design, CAD/3Dprinting, prototyping and rapid manufacturing
Bio
I have received my PhD in engineering education from Purdue University. With a BSc degree in Mechanical Engineer, and MSc in Biomedical Engineering, my research focuses on investigating how designs impact people's experiences at different fields and settings, including medicine, robotics, educational technology and artificial intelligence technology. I employ quantitative and qualitative research methods to explore user experiences and the science behind data, when interacting with the designed objects like robots/platforms like games and chat bots. For the past two years, I have been working as a data scientist in the higher education, I use advance quantitative analysis to analyze factors effecting student success, using advanced programming. My passion is to help students learn about the field of design, computer science, data science and statistics, and explore how these fields are intertwined. In addition to my academic passion, I also have a strong personal interest in cooking. I have always been fascinated with the art of creating delicious meals and experimenting with new ingredients. Whether it's trying out a new recipe or perfecting an old classic, cooking allows me to express my creativity and bring joy to those around me. I believe that food not only nourishes the body but also brings people together and creates memories that last a lifetime.Project ideas
Design and Code an Arduino Robot for Autonomous Navigation
In this mentorship project, I will guide you as you explore Arduino, an open-source microcontroller platform, and embark on designing, building, and coding your own robot for autonomous navigation. Throughout the project, I will provide you with valuable resources and tools to help you learn about Arduino and how it can be used for robotics projects. You will have the opportunity to brainstorm and create the physical structure of your robot, taking into consideration factors such as size, weight, and mobility. Together, we will explore various sensors that can be integrated into your robot to enable it to perceive its surroundings effectively. I will assist you in accessing resources and learning materials to understand how to code your robot using Arduino's user-friendly programming language and development environment. You will gain knowledge in programming behaviors like obstacle detection, avoidance strategies, and path planning algorithms. As your mentor, I will provide guidance and support throughout the project, helping you troubleshoot any challenges you encounter.
Movie Ratings Analysis
This project can involve the use of data visualization and descriptive statistics. The students can gather data on movie ratings from websites like IMDb or Rotten Tomatoes and use visualization tools, such as histograms, bar plots, and scatter plots, to explore the data. They can also use statistical methods, such as mean, median, and standard deviation, to describe the distribution of ratings. Through this project, students can learn about data visualization and the basics of descriptive statistics. They can also learn about how to explore and summarize data, and how to use data to answer questions about a particular topic, such as movie ratings.
Stock Market Analysis
This project can involve the use of time series analysis and regression analysis. The students can gather data on stock prices for a company of their choice and use time series methods, such as moving averages and exponential smoothing, to analyze trends in the stock market. They can also use regression analysis to explore the relationship between stock prices and other economic factors, such as inflation, interest rates, or gross domestic product. Through this project, students can learn about finance and economics, as well as how to use data to make investment decisions. They can also learn about time series analysis and regression analysis, and how to use these methods to explore trends and relationships in data.
Website Traffic Analysis
This project can involve the use of web analytics and data visualization. The students can gather data on website traffic, such as the number of visitors, the average time spent on the site, and the most popular pages, and use visualization tools, such as bar plots and pie charts, to explore the data. They can also use web analytics tools, such as Google Analytics, to analyze patterns in website usage. Through this project, students can learn about web analytics and how to use data to optimize a website. They can also learn about data visualization and how to use visualizations to explore and communicate data.
Image Recognition
This project can involve the use of computer vision and machine learning. The students can use computer vision techniques, such as edge detection and color filtering, to pre-process images, and then use machine learning algorithms, such as decision trees, to build a model that can recognize objects in the images. They can start with simple techniques and progress to more advanced techniques, such as convolutional neural networks, as they become more comfortable with the material. Through this project, students can learn about image processing, machine learning, and computer vision. They can also learn about the basics of computer science and how to use data and algorithms to solve real-world problems.
Customer Segmentation
This project can be approached using clustering techniques, such as k-means, hierarchical clustering, or Gaussian mixture models. The students can collect customer data, such as purchase history, demographic information, or website usage data, and use this data to segment customers into different groups based on their behavior. Through this project, students can learn about customer segmentation, data visualization, and the basics of clustering algorithms. They can also learn about the importance of understanding customer behavior and how to use this knowledge to make data-driven decisions for marketing and customer engagement.
Analyzing Social Media
This project can be approached using text mining and natural language processing techniques. The students can gather data from social media platforms, such as tweets, posts, or comments, and use tools like word frequency, sentiment analysis, and topic modeling to analyze the data. Through this project, students can learn about text data processing, data visualization, and the basics of text mining and natural language processing. They can also learn about the challenges of working with unstructured data, and how to extract insights from large amounts of text data.