I am a PhD student affiliated with the Big Data and Machine Learning Lab at the University of Mons, Belgium. My research interests lie in exploring the theory of deep learning and its applications, focusing on problems related to image data. Presently, my research is centred around deep anomaly detection under the supervision of Professor Souhaib Ben Taieb. My work focuses on developing novel anomaly detection methods that can address some of the most challenging aspects of industrial applications, which include tackling non-stationarity in data and working with limited, weak labels. Prior to my current position, I received a Master's degree in Data Science from the Eindhoven University of Technology, The Netherlands.
Conducting research on Anomaly Detection in Image Sequences under Prof Souhaib ben Taieb
Key responsibilities:
• Building a context-aware machine learning framework that can adapt to concept drift
• Finding hidden patterns and interactions among more than 50 features
• Dealing with the unbalanced dataset
Key responsibilities:
• Performed an extensive literature review for emotion detection using facial expression
• Implemented a hybrid CNN-LSTM model
• Achieved an accuracy of 60% on CREMA-D and 54% on RAVDESS datasets
• Tested the model in real-time using a live video feed via webcam
Key responsibilities:
• Enhancement, support, and maintenance activity of the delivered processes (Personal, and Job Data, Recruitment, Performance Management etc.) in the stringent timeline
• Responsible for 2 major clients having a total of 10,000+ employees
• Worked on XML Publisher, approval workflow engine (AWE) security-related activity, enhancements, and testing
• Modify several SQR reports based on client requirements
Key responsibilities:
• The following algorithms were used - User-based collaborative filtering (UBCF), Item-based collaborative filtering (IBCF), and Singular Vector Decomposition (SVD)
• Experiments were performed with the MovieLens dataset
• Multiple distance measures were employed: Cosine, Pearson correlation, and Jaccard
GPA: 8.76