About Me
I am a Ph.D. candidate at Baylor University with over 4 years of experience in Deep Learning and Computer Vision.
My research focuses on developing AI models and scalable solutions. I am passionate about exploring impactful opportunities
in Machine Learning research and development.
Recent Updates
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August 2024
Completed Machine Learning Internship at Dow, Midland, MI.
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August 2024
Became a reviewer for ICLR.
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June 2024
Reviewed papers for NEURIPS 2024 and WACV 2025.
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January 2024
Published paper: "Active Learning Strategy Using Contrastive Learning and K-means for Aquatic Invasive Species Recognition" at WACV24 Workshop.
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September 2023
Published paper on "Video-Based Recognition of Aquatic Invasive Species Larvae Using Attention-LSTM Transformers" at ISVC 2023.
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May 2023
Completed Data Science Internship at AI Camp, Palo Alto, CA.
Education
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PhD in Computer Science, Baylor University, TX, USA (Aug 2020 - May 2025)
Research on Deep Learning and Computer Vision. Dissertation on “Deep Learning of Visual Features with Limited Supervision.”
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B.Tech in Information Technology, Institute of Engineering & Management, Kolkata, India (Aug 2013 - May 2017)
Experience
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Machine Learning Intern (ADISE), Dow, Midland, MI, USA (May 2024 - Aug 2024)
Developed and implemented lane detection and quality measurement algorithms using dashcam video data.
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Data Science Intern, AI Camp, Palo Alto, CA, USA (May 2023 - Sep 2023)
Improved quality of response from Large Language Model (GPT) using Augmentation technique with LangChain and OpenAI API.
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Graduate Research Assistant, Baylor University, Waco, TX, USA (Aug 2020 - Present)
Worked on research grants, publications, and developed models for invasive species recognition and life stage identification.
