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VenkataJyothiPriya Mulaka
Entry-Level Data Scientist specializing in ML, Azure, and LLM applications
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About
ML/computer-vision practitioner who shipped a CycleGAN-based bilingual handwriting translation demo (English↔Telugu) for low-resource scripts using unpaired datasets, focusing on preserving handwriting style and real-time deployment via Gradio. Also delivered a medical imaging pipeline by fine-tuning ResNet-50 and ViT-B/16 for pneumonia detection, emphasizing reproducibility, measurable evaluation, and stakeholder-friendly iteration.
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Key Strengths
- Built and deployed a production AI bilingual handwriting translation system (English↔Telugu) using CycleGAN with unpaired data
- Deep practical understanding of stabilizing GAN training (addressed mode collapse via LR tuning, loss balancing, selective layer freezing)
- End-to-end ML ownership: data prep, training, evaluation, deployment, and user-facing demo interfaces
- Deployment optimization for real-time inference (fixed input resolution, minimal model footprint, CPU/GPU preprocessing split, latency timing)
- Applied computer vision in healthcare (fine-tuned ResNet-50 and ViT-B/16 for pneumonia detection from chest X-rays)
- Modular, testable workflow design with measurable metrics and regression checks
- Able to translate non-technical stakeholder needs into technical requirements and iterate using visual results
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Experience
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Publications
1 publication
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