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Sarthak Yadav
Intern AI/ML Engineer specializing in NLP, computer vision, and reinforcement learning
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About
Built an Arduino-based obstacle-avoiding robot using sonar/laser sensors and improved performance from 0.60 to 0.87 accuracy through sensor-fusion thresholding and iterative tuning. In an internship, optimized a legal-document NLP pipeline by switching to a distilled/quantized transformer and offloading inference to a GPU-backed Flask service, cutting inference time by 40%+ without added infrastructure spend.
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Key Strengths
- Improved obstacle-avoidance robot accuracy from 0.60 to 0.87 via sensor/code optimization
- Practical robotics AI using sensor-fusion + rule-based control with iterative testing
- Production-minded ML optimization (distillation + quantization) to reduce inference time >40%
- System-level engineering for deployment (GPU-backed Flask service, monitoring, fallback logic)
- Strong grasp of embodied AI challenges (grounding, data cost, sim-to-real) and mitigation via domain randomization
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