Sowjanya Deva

I’m Sowjanya Deva, a AI researcher and data engineer with over 4 years of experience working at the intersection of machine learning, distributed systems, and data engineering. My primary interests lie in scalable AI infrastructure, large language model data pipelines, privacy-preserving machine learning, and cloud-native MLOps. I have authored and co-authored research papers focused on privacy-preserving customer segmentation, scalable real-time feature engineering for large language model training, and modular serverless architectures for machine learning systems, with additional work currently accepted for publication. My research emphasizes reproducibility, system design, and the practical constraints of deploying AI responsibly at scale. Beyond research, I actively contribute to the community through peer review, judging, and mentoring. I have served as a reviewer and judge for technical programs, hackathons, and academic or industry-aligned events, where I evaluate projects based on technical rigor, originality, ethical considerations, and real-world applicability. I value constructive feedback and enjoy supporting students and early-career teams as they translate ideas into well-designed technical solutions. My goal in judging and volunteering is to help foster thoughtful, responsible innovation while encouraging strong engineering fundamentals and clear problem-solving approaches.