Srinjoy Das

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About

Srinjoy Das is a researcher at the intersection of machine learning and advanced manufacturing, with a focus on applying foundation models to industrial computer vision challenges. His work explores how state-of-the-art AI architectures, particularly Segment Anything, can be adapted for defect detection in laser-based additive manufacturing—a critical area where precision directly impacts part quality and safety. Das has pioneered an unsupervised approach to promptable defect segmentation, demonstrating how large vision models can be fine-tuned for specialized manufacturing environments without requiring extensive labeled datasets. This methodology leverages the paradigm shift toward user-generated prompts in computer vision, translating innovations from fields like biology and robotics into practical manufacturing solutions. His research on dictionaries in machine learning further underscores his commitment to developing robust, interpretable AI systems. While his most-cited papers have garnered 2 citations each, Das’s work represents an important bridge between cutting-edge AI research and real-world industrial applications, positioning him as an emerging voice in the growing field of AI-driven manufacturing quality control.