- Leading the AI strategy and development for WOMBO.ai, growing the app to over 200 million downloads globally, becoming the #1 app in multiple countries within 8 weeks of launch.- Spearheading the creation of proprietary AI models for lip-syncing and image generation, significantly reducing costs by self-hosting AI models and optimizing infrastructure.- Managing a team of AI engineers, overseeing the research and implementation of deep learning algorithms to enhance user experience and scalability.- Developing AI-powered tools used by millions daily, demonstrating significant innovation in consumer AI applications, shaping WOMBO as a leader in AI-powered entertainment.

- Leading the development of foundational AI architectures for the largest open-source AGI multimodal dataset, integrating cutting-edge AI models for video, text, and audio processing.- Pioneering a decentralized AI task marketplace that monetizes productivity through token-based rewards, focusing on AI’s application in the real world to boost efficiency.- Building partnerships and leading research initiatives in decentralized AI infrastructures using Bittensor, positioning OMEGA Labs at the forefront of next-generation AI development.- Managing a cross-functional team of AI researchers and engineers, driving innovation in AI productivity tools and contributing to advancements in autonomous systems.

- Researched and developed surrogate machine learning models to approximate solutions for complex partial differential equations related to superconductive tape modeling.- Deployed Temporal Convolutional Networks (TCN) on sequential problems where traditional LSTM networks failed, improving model accuracy and computational efficiency.- Collaborated with leading AI researchers on government-backed projects, driving advancements in AI's application to solve real-world physics challenges.

- Designed and deployed AI-based automation systems for biotech applications, significantly enhancing lab efficiency through predictive modeling and process optimization.- Created data processing pipelines to analyze high volumes of biological data, achieving near real-time insights for the company's diagnostic products.

- Developed a highly user-friendly GUI with easy and efficient browsing of thousands of protiens found in blood-samples using Tkinter python- Achieved clear, interactive, well labeled graphs with interpolated and extrapolated values using Matplotlib - Achieved results accurate to 1 - 2% of original data by optimized parameters for regression models (4PL,5PL, etc) predicted for the dataset leveraging Scipy optimize curve-fitting algorithms.- Prepared a database of relevant biomarkers and interpolated relative intensities in mass-spectrometery based experiments by extracting, transforming, and tabulating data using Pandas, XLRD, and XLSW.- Exploited scikit-learn classifiers to clear up the unnecessary data around significant results

Working as an Algorithm developer with Dr. Carl Haas for 3D Packing of irregular objects. Objectives:Develop genetic algorithms to find the best way to pack objects in the smallest 3D space possible using visual programming called Grasshopper for Rhino.Expand the working prototype from 3 degrees of freedom to 6 degrees of freedom by adding rotation using PyVolution and DEAP in Python.Perform tests on algorithms developed by inputting 3D laser scans of objects of interest.