I have over 5 years of work experience in Data Science / Machine Learning and building production ready tools. My projects span a wide spectrum of applications and techniques: Automated Essay Scoring (NLP) to Robust AI (CV) to Aircraft performance prediction (Stochastic Regression).
- Developed robust defense against adversarial attacks on ground-based and overhead tracking in PyTorch.
- Improved accuracies of single- and Faster-RCNN based multi-object trackers by 10 and 15 percentage points respectively.
- Designed novel small scale filtering strategy to negate the effect of moving adversarial patch.
- Achieved 4x increase in computational throughput by optimizing function calls and variables within GPU.
- Executed stochastic regression toolbox development project to fuse multiple data sources and provided quantitative estimates on uncertainty, resulting in significant reduction in aircraft certification costs.
- Supervised the integration of statistical modeling framework from Matlab into Python to achieve seamless interaction with Boeing’s existing design tools, thus achieved multi-fold increase in the toolbox’s reach.
- Formulated cross-functional research projects to meet the requirements of business and engineering units.
- Characterized large-scale coherent structures in swirling jets through dimensionality reduction (PCA, DMD) and established the causality based on the underlying physics through global stability analysis.
Reports for each of these projects may be obtained by clicking the project name. However, the codes cannot be shared due to Georgia Tech policies. I am listed as "Vamsi Ravilla" or "Vamsi Krishna Chakravarthy Ravilla" in these projects.
Publications & Conferences
I am listed as “R. V. K. Chakravarthy” in these articles.