• Managed multiple distributed teams. Tasked with leading the R&D, Software Engineering, Hardware Engineering, Manufacturing and QA groups.• Improved gross margin by reducing COGS by reducing manufacturing production costs by 40% through product redesign, contract manufacturing selection.• Successfully managed a $1.3M NIH grant as the Principal Investigator. Involved prototype deployment, support, clinical study and data analysis. The results showed 95% medication error reduction when the device was used in long term care facilities.• Managed the patent portfolio. Produced key patents for new product features.• Introduced manufacturing design changes to reduce overall product installation and deployment costs. Reduced deployment and installation costs by 60%. Tackled over all RMA costs to reduce RMAs by 90%.• Reorganized engineering resources to reduced engineering costs by 30%, by expanding the off shore teams and introducing a task based expenditure tracking for engineering projects.

• Responsible for project management, product development and product delivery. Took the products from concept to final customer deployment. Scaled the product to support enterprise customers.• Responsible for company IT infrastructure and compliance. This included managing desktop support via 3rd party support company. Specifying and managing IT and HIPAA compliance policies.

• Established contacts with multiple pharmacy software vendors to implement interfaces with the pharmacy software vendors. Developed and designed interfaces to interact with 3rd party vendors. Established connectivity with 95% of pharmacy systems in 3 years.• Managed the development activities. This involved architecting the various modules and components of the software, hardware and firmware for multiple products. Developed back end infrastructure to support testing, releases, deployments and backup. Designed internal tools for image QA, manufacturing. Instituted processes for automated build, task tracking and automated testing. Created and managed an off shore engineering (software and hardware) development team.• Managed the early phase customer support infrastructure. Performed initial customer install and go-live procedure.• As a member of the sales and marketing team I was involved in sales and marketing efforts. Developed and streamlined product setups for trade shows demos. Worked to evangelize, market and sell the product at trade shows. Engaged with customers to obtain insights on requirements and features.

The primary focus for PerceptiMed Inc. is medication safety. The products are targeted to eliminating errors that occur in pharmacies, hospitals and long term care facilities. One of the two products is a medication verification device that incorporates machine vision and AI to capture images of medications (pills) and identifies them (verifies every pill being dispensed). The system is designed to be 98100% accurate in identifying medication from the images of each pill. The other product is a will- call automation system that prevents the wrong prescription from being given to the customer.Directed research in machine learning and computer vision, applied to medication verification. Worked on classical machine learning and deep learning techniques. Achieved 98 100% medication identification accuracy on thousands of medications. I designed the training pipeline for the classifiers. Developed the cloud compute infrastructure for machine learning algorithm training. Improved the throughput of the image processing algorithm. Streamlined the machine learning training pipeline.

• Lead engineer for computer vision based projects. Developed and deployed a low cost vision system for wafer inspection. Designed to monitor the pose of a silicon wafer in an evacuated environment through the process of ion implantation.• Responsible for designing an adaptive vision system for next generation ion implanters. Member of the group involved in aiding development of future standards for silicon wafer orientation.

• Designed a high throughput robotic system for automated Plant phenotype studies. The responsibilities spanned system design, component sourcing and machining, circuit fabrication, software development, turn key deployment and system throughput analysis of the robotic system. This research has been featured at the Redhat Linux Conference 2011 and has been featured as a part of National Science Foundations Science Nation in spring 2012.• Engaged in collaborative research with other research labs on campus and developed solutions for various applications for image based metrology using image processing, computer vision and machine learning techniques.• Designed an image based navigation algorithm for the IEEE robot team for IGVC 2008, an autonomous vehicle navigation competition.• Mentored and supervised graduate research assistants and undergraduate stu- dents.• Assisted with handling of the robotics course (ME439) lab sessions and other outreach activities.• Organized lab research reading groups and talks.• Lab computer system, network and website administrator.

An Introduction to Robotics and Automation - Created a summer course where 6th to 9th grade students were exposed to the field of robotics and automation through a three week long program, during the month of June, that included lectures and hands on experience with robots.

- Developed programs using MATLAB for hardware-software interfacing and data analysis.- In charge of setting up data acquisition systems.- Providing researchers with technical support with their experimental setup.

- Redesigned the American Indian Studies Program website.- Provided computer system maintenance and support, and video editing for outreach activities.

- Developed a system for measuring accommodation dynamics in human lens.- Designed instrumentation for intraocular pressure measurements in live mice.- Prepared an NIH SBIR Grant proposal.

Worked on developing machine vision systems to image plant seeds and seedlings. Image orocessing techniques were developed to extract features for phenotyping. Machine learning techniques were employed to identify the most prominent features for the purpose of phenotyping.

Geometric Modeling for Engineering Applications - Handled one of four sections of the lab component of the undergraduate course. Responsibilities included aiding in formulation and grading of homework, projects, lab tutorials and exams.

- Researched techniques available for automatic face recognition.- Implemented and tested a MATLAB based face authentication system.

Designed a CNC lathe process simulator for precision machining.