Vaibhavi Itkyal

Computational data scientist and machine learning engineer with 5+ years of experience building scalable AI solutions across finance, infrastructure optimization, and healthcare. Skilled in developing and deploying end-to-end systems for forecasting, personalization, and decision intelligence using large language models (LLMs), and multimodal data fusion. Proven track record of leading cross-functional teams and delivering production-ready solutions in startups, enterprise R&D, and global research labs.

Passionate about bridging experimental research with real-world value through platform engineering, interpretable modeling, and business-aligned AI integration.

I bring hands-on experience delivering AI-driven solutions across infrastructure, healthcare, and enterprise tech. At Teichert, I’m building forecasting models and document intelligence tools to optimize resource allocation and streamline operational decisions. As a lead consultant at Emory Biotechnology Consulting, I developed go-to-market and financial strategies for early-stage therapeutics, simulating venture diligence.

At 28ish, I led a 12-person team to launch a personalized health platform powered by generative AI, and at Avesha, I deployed scalable ML algorithms to optimize cloud resource usage, reducing infrastructure costs by 70% and improving system efficiency.

I am currently a Ph.D. candidate in Computational Neuroscience at Emory University and a fellow in Computational Neural Engineering through a joint program with Georgia Tech. My research focuses on applying deep learning, time-series modeling, and multimodal data fusion to large-scale neuroimaging datasets. I’ve developed interpretable AI models for disease classification, built 3D segmentation tools, and optimized signal extraction techniques across over 100,000 high-dimensional brain imaging records—translating complex biomedical data into actionable insights for clinical and global health applications.