Top 10 Interesting ML Dissertations from Ph.D. Students

This article features the top 10 ML dissertations for Ph.D. students to try in 2022.

Choosing interesting dissertation topics in ML is the first choice of Master's and Doctorate scholars nowadays. Ph.D. candidates are highly motivated to choose research topics that establish new and creative paths toward discovery in their field of study. Selecting and working on a dissertation topic in machine learning is not an easy task as machine learning uses statistical algorithms to make computers work in a certain way without being explicitly programmed. The main aim of machine learning is to create intelligent machines which can think and work like human beings. This article features the top 10 ML dissertations for Ph.D. students to try in 2022.

Text Mining and Text Classification: Text mining is an AI technology that uses NLP to transform the free text in documents and databases into normalized, structured data suitable for analysis or to drive ML algorithms. This is one of the best research and thesis topics for ML projects.

Recognition of Everyday Activities through Wearable Sensors and Machine Learning: The goal of the research detailed in this dissertation is to explore and develop accurate and quantifiable sensing and machine learning techniques for eventual real-time health monitoring by wearable device systems.

Computer Vision: Computer Vision is a field that deals with making systems that can read and interpret images. In computer vision, data is collected from images that are imparted to systems. The system will take action according to the information it interprets from what it sees.

Voice Classification: Voice classification or sound classification can be referred to as the process of analyzing audio recordings. Voice and Speech Recognition, Signal Processing, Message Extraction from Voice Encoded, etc are the best research and thesis topics for ML projects.

Deep in-memory computing: There is much interest in embedding data analytics into sensor-rich platforms. Such platforms often need to implement machine learning (ML) algorithms under stringent energy constraints with battery-powered electronics.

Object Detection with Deep Learning: Object Detection with Deep Learning is one of the interesting machine learning projects to create. When it comes to image classification, Deep Neural Networks (DNNs) should be your go-to choice. In this Machine Learning project, you will solve the problem of object detection by leveraging DNNs.

Algorithms and analysis for non-convex optimization problems in machine learning: This dissertation proposes efficient algorithms and provides theoretical analysis through the angle of spectral methods for some important non-convex optimization problems in machine learning. In this research, a novel algorithm is proposed that can flexibly learn a multi-view model in a non-parametric fashion.

Supervised Machine Learning: It is a good topic for ML dissertation Ph.D. students. It is a type of machine learning algorithm which makes predictions based on known data sets. Supervised Learning is further classified into classification and regression problems.

Collaborative detection of cyberbullying behavior in Twitter data: It is critical to efficiently detect cyberbullying behavior by analyzing tweets, in real-time if possible. This dissertation proposes a new approach called the distributed-collaborative approach for cyberbullying detection.

Bayesian Network: It is a network that represents probabilistic relationships via Directed Acyclic Graph (DAG). There are algorithms in Bayesian Network for inference and learning. Bayesian Network finds its application in bioinformatics, image processing, and computational biology.