I began my PhD with the support of a Marie Curie Scholarship (MSCA)-2020. This PhD contribution includes eight international universities and sixteen multinational firms from Europe and the United States. ODECO is a 4-year Horizon 2020 Marie Skłodowska-Curie Innovative Training Network initiative (H2020-MSCA-ITN-2020, grant agreement 955569). The full details of the project may be seen on the ODECO website at odeco-researchUniversity of Aegean, Greece
It is a post-graduate degree, according to Pakistan's educational system. I am currently enrolling in a PhD program following the completion of my MSCS. MSCS is a computer science-specific degree. I earned a distinction in my MSCS degree (Gold Medal)Air University, Islamabad, Pakistan
Bachelor of science in computer science is a four-year degree. It contains theory and has a strong connection to practical labs. This degree program includes more than fifty courses. I was ranked third in my department of computer science.University Institute of Information Technology, PMAS Arid Agriculture University, Rawalpindi
ODECO is a 4-year Horizon 2020 Marie Skłodowska-Curie Innovative Training Network initiative (H2020-MSCA-ITN-2020, grant agreement 955569). The central aim of the ODECO consortium network is to train the next generation of creative and innovative early stage open data researchers, to unlock their creative and innovative potential to address current and future challenges in the creation of user driven, circular and inclusive open data ecosystem. The programme runs between October 2021 and September 2025 and will deliver 15 PhD degrees, in joint supervision and training between the public and private sectors.Open Data ecosystem(ODECO)
On the internet, hate speech identification is critical for policing material in any country. The National Cyber Security Center(NCCS) is creating an automated hate detection tool for social media applications on the internet. I am part of the NCCS team, working on methods for detecting hate speech on the internet using natural language processing, machine learning, and deep learning. I have over three years of expertise detecting and classifying hate speech distributed via social media blogs and emails, and I have also published journal and conference publications in this field.CENTER FOR CYBER SECURITY AND NATIONAL FORENSIC CYBER AND CRIME LAB(NCCS AND NCFL)
I won the research scholarship award which included the MS Computer science degree and few compulsory requirements such as Lab conduction of data science subject, programming labs, software engineering, Compiler Construction, Theory of Computation, Web Development, and Databases Labs were included. Moreover, Research activities to enhance the impact of Master dissertation was also part of my job description. I completed this tenure with honor award from the Air University, Islamabad.Air University, Islamabad, Pakistan
I developed online store web application using web technologies such as C# dot net framework, databases, online payment methods, and reporting management modules. NodeJS, AngularJS, MongoDb, and Casandra Databases were also used during my this internship. I also developed any online Email designer for the creation of interactive emails to promote the business activities.Punjab Board of Technical Education, Pakistan
Beginning from scratch to obtain the Marie-Curie scholarship was a really enjoyable experience. the research opportunity that came about as a result of my involvement with the ODECO multi-national open government data initiative. The benefits of ODECO are immeasurable in the fields of culture, science, finance, statistics, meteorology, and the environment.
Machine Learning using R and Python Hate detection from videos and images uploaded on social media Hate speech detection using NLP and Artificial Intelligence Machine Learning algorithms Deep Learning algorithms development and Improvements Data Science Using R and Python Python for Deep Learning
Python for NLP Natural Language Processing using python Text Summerization Natural language processing for low resources languages Text Classification Text Analytics Hate speech detection Topic Modeling Text Generation Sentiment Analysis
Python development Graph theory applications Community detection on social media using interactions Networkx Python Data Analysis Python libraries (TensorFlow, Matplotlib, Seaborn)
FHate speech spread through the social media platforms have a wider impact over the countries economy and law enforcement agencies. I developed a tool to analyze the content of social media platforms to control the content over the social media using Deep neural networks such as LSTM and GRU.
each email sent through the email servers have a body area, body can have fraudulent, aggressive, or vulnerable content. My developed model is able to detect the harmful emails.
I extracted the video frames using the multi-tasking of the operating system and then each frame is analyzed with deep learning image processing model for the object detection from images. I also extracted the texts from the speech of video in fast track using multi-tasking.
How hatred content is spread with users information makes a community, we plotted this community in the graphical format to analyze them.
Community over the social media always plays a role to spread the post instantly, our tool will evaluate the parameters of the posted news to check the involvement of each user to particular post. for example, how the different people are supporting a post.
Anonyms searching is the current evolving technology, it have several advantages and dis-advantages. My developed application will differ the traffic generated from a Tor or Non tor browser based on the features.
Rumors are also a part of current social media platforms which can damage the economy of any country. Peoples are more at danger because of rumor stances. So, I developed a tool which decides on the basis of deep learning and machine learning algorithms that either a tweet is rumor or non rumor about COVID-19.
MRI images provides important information while diagnosing a patient affected by cancer disease. I developed a tool which will take a MRI image as input and returns on the basis of Features learned and Fuzzy segmentation that which part of the brain is effected by canser.
A audio file which is original will be different from the audio is replayed/fake. I got the features from the audio spectrogram and analyzed using the deep learning models.