Applied Scientist with 3+ years of experience in Computer Vision and Natural Language Processing. Recently acquired a master’s degree in Computer Science with a specialization in Artificial Intelligence from the University of Ottawa. Listed below are some of my past experiences: • Data acquisition, feature engineering, development, and deployment of state-of-the-art Deep Learning architectures for various industrial use cases. • Worked on distributed large-scale pre-training of Image Classification and Object Detection models for the identification of over 2000+ generic concepts from real-world images and developed customized OCR models and GNNs for multi-modal information extraction from visually rich documents with performance gains of over 20% from the baseline approach. • Recognized at the organizational level as one of the top performers in the quarter and for demonstrating core company values. • Lead author of a publication in the IEEE Journal of Biomedical and Health Informatics (JBHI), that addresses the problem of early detection of abnormal brain cells from MRI images based on a novel approach that uses only ~50% of baseline parameters and achieves performance gains of over 5%. • Completed several research internships at National Research Council Canada and Kinaxis focussing on developing state-of-the-art NLU models and graph machine learning approaches. Lead author of publications to NAACL 2024, LREC-COLING 2024. I am passionate about using Artificial Intelligence to create a positive impact in people's lives. Looking forward to connecting with you ! Applied Scientist with 3+ years of experience in Computer Vision and Natural Language Processing. Recently acquired a master’s degree in Computer Science with a specialization in Artificial Intelligence from the University of Ottawa. Listed below are some of my past experiences: • Data acquisition, feature engineering, development, and deployment of state-of-the-art Deep Learning architectures for various industrial use cases. • Worked on distributed large-scale pre-training of Image Classification and Object Detection models for the identification of over 2000+ generic concepts from real-world images and developed customized OCR models and GNNs for multi-modal information extraction from visually rich documents with performance gains of over 20% from the baseline approach. • Recognized at the organizational level as one of the top performers in the quarter and for demonstrating core company values. • Lead author of a publication in the IEEE Journal of Biomedical and Health Informatics (JBHI), that addresses the problem of early detection of abnormal brain cells from MRI images based on a novel approach that uses only ~50% of baseline parameters and achieves performance gains of over 5%. • Completed several research internships at National Research Council Canada and Kinaxis focussing on developing state-of-the-art NLU models and graph machine learning approaches. Lead author of publications to NAACL 2024, LREC-COLING 2024. I am passionate about using Artificial Intelligence to create a positive impact in people's lives. Looking forward to connecting with you !

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  Machine Learning Engineer in GPTZero

  Building the safeguards for responsible AI adoption in education and our world.