This document discusses several artificial intelligence research topics that could be explored for a PhD thesis. It begins by introducing the rapid growth of AI in recent years. It then outlines topics such as machine learning, deep learning, reinforcement learning, robotics, natural language processing, computer vision, recommender systems, and the internet of things. For each topic, it provides a brief overview and lists some recent research papers as potential thesis ideas. In conclusion, the document aims to help PhD students interested in AI research by surveying the current state of the field and highlighting subtopics that could be investigated further.

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Artificial Intelligence Research Topics for
PhD Manuscripts 2021
Dr. Nancy Agnes, Head, Technical Operations Phdassistance, info@phdassistance.co
Keywords: Machine Learning, Artificial
Intelligence, Deep learning, Reinforcement
Learning, Robotics, Natural Language Processing,
Computer Vision, Recommender Systems, Internet
Of Things, Research Topics for PhD Manuscripts,
Artificial intelligence & machine learning, PhD
Manuscripts Writing Help, Research in Artificial
Intelligences, Artificial Intelligence Research
Topics, Best Computer Science PhD Programs, PhD
Manuscripts Help, Computer Data Science, Topics
for PhD manuscripts, PhD Research Topics,
Computer Programme.
I. INTRODUCTION
Imagine a world where knowledge isn't limited to
humans!!! A world in which computers will think and
collaborate with humans to create a more exciting
universe. Although this future is still a long way off,
Artificial Intelligence has made significant progress
in recent years. In almost every area of AI, such as
quantum computing, healthcare, autonomous
vehicles, the internet of things, robotics, and so on,
there is a lot of research going on. So much so that
the number of annual Published Research Papers on
Artificial Intelligence has increased by 90% since
1996.
Keeping this in mind, there are several sub-topics on
which you can concentrate if you want to study and
write a thesis on Artificial Intelligence. This article
covers a few of these subjects and provides a short
overview. Here some of the recent Research Topics,
1. Artificial Intelligence and Machine learning –
Recent Trands
2. How AI and ML can aid healthcare systems in
their response to COVID-19
3. Machine learning and artificial intelligence in
haematology
4. Tackling the risk of stranded electricity assets
with machine learning and artificial intelligence
II. DEEP LEARNING
Deep Learning is a type of machine learning that
learns by simulating the internal workings of the
human brain in order to process data and make
decisions. Deep Learning is a form of machine
learning that employs artificial neural networks.
These neural networks are linked in a web-like
structure, similar to the human brain's networks
(basically a condensed version of our brain!).
Artificial neural networks have a web-like structure
that allows them to process data in a nonlinear
manner, which is a major advantage over
conventional algorithms that can only process data in
a linear manner. Rank Brain, one of the variables in
the Google Search algorithm, is an example of a deep
neural network.
Recent research topics
1. Artificial intelligence & deep learning : PET and
SPECT imaging
2. Hierarchical Deep Learning Neural Network
(HiDeNN): A computational science and
3. engineering
4. in AI architecture.
5. AI for surgical safety: automatic assessment of
the critical view of safety in laparoscopic
cholecystectomy using Deep Learning
6. Deep learning-enabled medical computer
vision
III. REINFORCEMENT LEARNING
Reinforcing Learning is an aspect of Artificial
Intelligence in which a computer learns something
in the same way as humans do. Assume the
computer is a student, for example. Over time, the
hypothetical student learns from its errors. As a
outcome of trial and error, Reinforcement Machine
Learning Algorithms learn optimal behaviour.
This means that the algorithm determines the next
way to proceed by learning behaviours based on its
current state that will increase the reward in the
future. This also works for robots, just as it does for
humans!
Google's AlphaGo Computer Programme, for
example, used Reinforcement Learning to defeat
the world champion in the game of Go (a human!)
in 2017.
Recent research topics
1. Experimental quantum speed-up in
reinforcement learning agents
2. Potential-based multiobjective reinforcement
learning approaches to low-impact agents for
AI safety

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IV. ROBOTICS
Robotics is an area concerned with the creation of
humanoid robots that can assist humans and perform
several acts. In certain cases, robots can behave like
humans, but can they think like humans as well?
Kismet, a social interaction robot developed at
M.I.T.'s Artificial Intelligence Lab, is an example of
this. It understands human body language as well as
our voice and responds to them appropriately.
Another example is NASA's Robonaut, which was
designed to assist astronauts in space.
Recent research topics
1. Regulating artificial intelligence and robotics:
ethics by design in a digital society
2. Regional anaesthesia :usages of artificial
intelligence and robotics in
3. Third Millennium Life Saving Smart Cyberspace
Driven by AI and Robotics
V. NATURAL LANGUAGE PROCESSING
Humans can obviously communicate with each other
by speech, but now machines can as well! This is
known as Natural Language Processing, and it
involves machines analysing and understanding
language and expression as it is spoken (which means
that if you speak to a computer, it might only
respond!). Speech recognition, natural language
production, natural language translation, and other
aspects of NLP are all concerned with language. NLP
is recently very important in customer service
applications, particularly chatbots. These chatbots use
machine learning and natural language processing to
communicate with users in textual form and respond
to their questions. As a result, you get a personal
touch in your customer service experiences without
actually speaking with a human.
Here are several research papers in the field of
Natural Language Processing that have been
published. You can look at them to get more ideas for
research and thesis topics on this subject.
Recent research topics
1. Natural Language Processing–Based Virtual
Cofacilitator for Online Cancer Support Groups:
Protocol for an Algorithm Development and
Validation Study
2. Sympathetic the temporal evolution of COVID-
19 Research Through machine learning and
natural language processing
VI. COMPUTER VISION
The internet is full of images! This is the selfie age,
and taking and posting a photo has never been easier.
Each day, millions of images are uploaded to the
internet and viewed. It's important for computers to
be able to see and understand images in order to make
the most of the vast amount of images available
online. And, while humans can do this without
thinking about it, computers find it more difficult!
This is where Computer Vision enters the image.
To extract information from images, Computer
Vision utilizes Artificial Intelligence. This
knowledge may include object detection in the
image, image content recognition to group images

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together, and so on. Navigation for autonomous
vehicles using images of the surroundings is one use
of computer vision, such as AutoNav, which was
used in the Spirit and Opportunity rovers that landed
on Mars.
Recent research topics
1. Deep learning-enabled medical computer vision
2. Artificial intelligence for surgical safety:
automatic assessment of the critical view of
safety in laparoscopic cholecystectomy using
deep learning
3. An Open‐Source Computer Vision Tool for
Automated Vocal Fold Tracking From Video
endoscopy
VII. RECOMMENDER SYSTEMS
Do you get movie and series recommendations from
Netflix based on your previous choices or favourite
genres? This is achieved by Recommender Systems,
which offer you advice about what to do next from
the vast array of options available online. Content-
based Recommendation or even Collaborative
Filtering may be used in a Recommender System.
The content of all the products is analysed in
Content-Based Recommendation. For example, based
on Natural Language Processing performed on the
books, you might be recommended books that you
may enjoy. Collaborative Filtering, on the other hand,
analyses your past reading behaviour and then
recommends books based on it.
Recent research topics
1. Artificial intelligence in recommender systems
2. Deep Transfer Tensor Decomposition with
Orthogonal Constraint for Recommender
Systems.
3. Recommender systems for configuration
knowledge engineering
VIII. INTERNET OF THINGS
Artificial intelligence is concerned with the creation
of systems that can learn to perform human-like tasks
based on prior experience and without the need for
human interaction. The Internet of Things, on the
other hand, is a network of different devices linked to
the internet and capable of collecting and exchanging
data.
All of these IoT devices now generate a large amount
of data, which must be collected and mined in order
to produce actionable results. Artificial Intelligence
enters the picture at this stage. The Internet of Things
is used to collect and manage the massive amounts of
data that Artificial Intelligence algorithms need. As a
consequence, these algorithms transform the data into
useful actionable results that IoT devices can use.
Recent research topics
1. Enhanced Medical Systems by using Artificial
Intelligence and Internet of Things
2. Artificial Intelligence and Internet of Things in
Instrumentation and Control in Waste
Biodegradation Plants: Recent Developments
3. AIoT-Artificial Intelligence of Things
IX. CONCLUSION
In this blog discussed the recent enhancement for
artificial intelligences and their sub field. This will
help to the PhD scholar who are interested to research
in artificial intelligences domain.
REFERENCES
1. Shouval, R., Fein, J. A., Savani, B., Mohty, M.,
& Nagler, A. (2021). Machine learning and
artificial intelligence in haematology. British
journal of haematology, 192(2), 239-250.
2. van der Schaar, M., Alaa, A. M., Floto, A.,
Gimson, A., Scholtes, S., Wood, A., ... & Ercole,
A. (2021). How artificial intelligence and
machine learning can help healthcare systems
respond to COVID-19. Machine Learning,
110(1), 1-14.
3. Nyangon, J. (2021). Tackling the risk of stranded
electricity assets with machine learning and
artificial intelligence. In Sustainable Energy
Investment-Technical, Market and Policy
Innovations to Address Risk. IntechOpen.
4. Saha, S., Gan, Z., Cheng, L., Gao, J., Kafka, O.
L., Xie, X., ... & Liu, W. K. (2021). Hierarchical
Deep Learning Neural Network (HiDeNN): An
artificial intelligence (AI) framework for
computational science and engineering.
Computer Methods in Applied Mechanics and
Engineering, 373, 113452.
5. Mascagni, P., Vardazaryan, A., Alapatt, D.,
Urade, T., Emre, T., Fiorillo, C., ... & Padoy, N.
(2021). Artificial intelligence for surgical safety:
automatic assessment of the critical view of
safety in laparoscopic cholecystectomy using
deep learning. Annals of Surgery.
6. Esteva, A., Chou, K., Yeung, S., Naik, N.,
Madani, A., Mottaghi, A., ... & Socher, R.
(2021). Deep learning-enabled medical computer
vision. npj Digital Medicine, 4(1), 1 9.