Building the 1st Multichain Infra Provider specialized for UTxO-based Dapps & Defi | Bitcoin (Runes ▣, Ordinals ◉), Cardano, Dogecoin.

Machine Learning & AI software development consulting firm for blockchain and Defi (decentralized finance) applications

Genius Yield was designed to address the complexity of navigating yield opportunities in DeFi. Our mission is to democratize DeFi for everyone by providing best-in-class automated liquidity management, powered by AI.

Sommelier (https://sommelier.finance) Ethereum-based Defi application aim at automating digital asset management.As a data science consultant, I design and develop Sommelier's core predictive models to automate portfolio rebalancing of Liquidity Providers to maximize high yield opportunities on Uniswap V3.

Senior Machine Learning Engineering Manager leading the Research Platform team, in charge of building a scalable, reliable and flexible ML training and evaluation platform for supporting our internal cancer detection R&D, leveraging NGS (next-generation sequencing) genomic data.

Computation Research team working on our AI genomics platform.Developing deep learning and machine learning algorithms to detect cancer at its earliest stages and help clinicians optimize the next generation of precision cancer therapies.

Driver is a consumer technology company building a treatment access platform for cancer patients. Our team consists of 70+ radicals, including engineers, scientists, and physicians, all of whom share a common mission to give patients access to new treatments.

### Top 7 startups from Y Combinator 2016 ###- Spearheaded by Skymind, Deeplearning4j is the first commercial-grade, open-source, distributed deep-learning library written for Java and Scala.Research Topics:- Real-time Demographic Classification with video feeds. Developing hybrid deep architecture combining Convolutional Neural Networks and Recurrent LSTM Networks to extract both spatial and temporal latent features.- Developed like2vec = product co-purchased graph + DeepWalk + Recommender System.Speaker at Data By the Bay (May 16th-20th) :- Sparse data alternatives with neural network embeddings (co-presented with Mike Tamir)

The Master's of Science in Data Science is an immersive industry focused program. It prepares students for positions in data science conducting high-volume data management, predictive analysis, and visualization.Skills include:- Deep Learning- Advanced machine learning and data analysis- Unstructured data and natural language processing- Big data technologies- Big data infrastructure- Leadership and entrepreneurism- Internship and practicum- Capstone/thesis

Awarded 1st place overall in Baja SAE intercollegiate design competition (Rochester, US 2013) out of over 140 design teams from top North American Universities. McGill Baja Design’s goal is to design, build and race every year an off-road vehicle that can withstand the roughest terrains. I co-headed the aerodynamics team to reduce the drag coefficient of the vehicle. I performed CFD, Wind Tunnel and Prototype Testing with 3D printing . We designed and manufactured flow-optimized carbon fiber body panels that achieved 11% in drag reduction. McGill Baja Notable Finishes1st Place Overall Rochester 2013 (historically McGill Baja's best competition result)3rd Place Overall Illinois 20141st Place Acceleration Kansas 20141st Place Acceleration Rochester 20131st Place Hill Climb Rochester 20132nd Place Endurance Illinois 20142nd Place Engineering Design Illinois 2014

- Developed multi-body suspension simulations on Matlab/Simulink and SIMPACK- Performed optimization research on hydro-pneumatic semi-active suspension systems for tractors designed by Jan Kruger (supervisor).

Performed a study on risk and reliability of equipment under extreme weather conditions at three different LNG terminals. Results of study were taken into account in Elengy’s restructuring report, resulting in lower potential loss and vulnerability of terminal.