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RecruitBot.com is an all-in-one recruiting tool for hard to fill roles, and Salesbot.io is an end-to-end tool for lead generation. We use AI-based candidate matching and powerful search to identify people that would normally require you visiting 3 or 4 different websites target. From there, send personalized but automated communication to verified email and phone numbers, and review powerful analytics to optimize outreach performance and user activity. We're hiring! https://www.recruitbot.com/careers/

Self development is important too!

Responsible for building out the Data Science team. We drive revenue through data driven products & insights.

Ness is a Restaurant Recommendation company, that understands the tastes of users, to provide personalized recommendations.A significant aspect of my role has included product strategy, and bridging the gap between product and technical implementation.I was responsible for leading teams to deliver:* Data Conflation & Data Acquisition Pipeline - I am particularly proud of our solution for Data Conflation that involves a novel approach involving Machine Learning. * Search & Recommendation System - Query Understanding & Rewriting, Retrieval, Spelling Correction, Ranking, Recommendation Explanations, and Group Recommendations. In particular, my focus was on ranking quality, providing intuitive results to users. * User Similarity: Invented and implemented algorithm for providing similarity scores between two users.* Collaborative Filtering - Responsible for generation of rating predictions, including the regression formulations. This includes a 3-part system: Hyper-Parameter Tuning using Map-Reduce, a collaborative filter, and an incremental collaborative filter (so we can provide recommendations within 10 seconds of a user providing information).* Natural Language Processing of Review Data - Oversaw algorithmic direction for the generation of algorithmic tags, which are predicted using Machine Learning based upon textual dataTechnologies that were used to solve these problems include: * Java Stack: Jetty, Guice, Jackson, Lucene* Python Stack: Django* Web: (Limited) Javascript, HTML, CSS, JQuery* Algorithms: Matrix Factorization (Alternating Least Square & Stochastic Gradient Descent), Logistic Regression / SVMs, Bayesian Shrinkage, Bayesian Inference, MapReduce, Quadratic & Linear Programming* Tools: AWS EC2 & S3, Postgres, Mongo

* Developed an Expert System involving parsing a graphical representation of finite automata to provide a medical diagnosis and treatment regimen for HIV/AIDS patients in the third world. * Implemented prototype, which was essential to raise the initial angel capital for the company. * Supplied ongoing consulting and collaboration to DMS' medical and technical team.* DMS implemented my solution in South Africa, where over 18,000 patients were treated requiring minimal doctor oversight.Technologies: Microsoft Visio Plugin, Visual Studio, Microsoft Access, C#

* Perceptive Pallets: Real-time spatial tracking systems for ensuring safety in BioPharma warehouses. * Actuator Networks: Autonomous navigation of an unobserved robot with active beacons. * Respectful Cameras: Providing visual privacy to people observed by vision systems. Our demos automatically obscured the faces of people in multiple environments including in-lab, a museum, and a construction site. * StatSense: Framework for sensor-network localization, and distributed sensor-network inference using graphical modeling. Our demo provided a temperature prediction library for an array of distributed sensors.* SNARES: Interpreted heterogeneous binary sensors triggering patterns in real time to track targets using Particle Filtering. For our demo, we interpreted the response to Passive Infrared Sensors to track an intruder in a room, which we in turn documented with a robotic camera. * Advised undergraduates on Dynamic Panorama Generation, Demonstrate Applet demo and Real-Time Intruder Tracking. * Designed, implemented, and integrated photo capture program into a robotic webcam used for multi-user collaboration Technologies that were used to solve these problems include: * Languages: Java, C++, Matlab, PHP, nesC (variant of C for sensor network programming)* Frameworks: Visual Studio* Algorithms: Bayesian Inference, Belief Propagation (NonParametric and Parametric) - a generalization of Bayesian Inference, Particle Filtering, AdaBoost, SVMs, Computer Vision

FotoFlexer is the world's most advanced online digital photo editor. It made advanced effects previously only available to professionals using expensive software accessible to the average consumer. * We grew to over 10 million users per month over our network of integration partners which included companies such as MySpace, Photobucket, and eHarmony.* Under my leadership, we grew the team to 14 people, primarily consisting of software engineers.* I was primarily responsible for the product and technical roadmaps, architecture, and key technical problems including the use of Machine Learning (AdaBoost) to provide key image-processing features.* Responsible for revenue generation, particularly through Ad-Network optimization* Other responsibilities included press releases, and business development.Languages: PHP, HTML, CSS, Adobe Flex, JavascriptAlgorithms: AdaBoost, Image ProcessingTools: OpenX (opensource advertising platform), Amazon S3

* Designed and implemented simulator of new version of Pursuer Evader Game that utilized a detection scheme, sacrificing granularity for frequency of wireless transmissionsLanguages: nesC (variant of C for sensor network programming)

* Ported the Harmonia compiler from Linux to Windows .Net. * Designed and implemented checking algorithm to verify correct semantics of lexing and parsing files for Harmonia.