Overseeing the development and implementation of machine vision solutions, within various industries including printing, packaging, manufacturing, and pharmaceutical applications. The primary responsibilities include:• Leading and managing machine vision projects from conception to implementation, ensuring timelines, budgets, and deliverables are met. • Designing machine vision systems tailored to the specific needs of a company, which can include image processing, object detection, pattern recognition, and automation. Coordinating with cross-functional teams, such as software developers, hardware engineers, and product managers, to develop and deploy machine vision solutions.• Engaging clients to understand their requirements, providing technical expertise, and offering solutions to meet their business needs. Ensuring that machine vision systems are integrated seamlessly with existing production systems, automation processes, and workflows.• Staying updated with the latest advancements in machine vision technologies (such as AI and deep learning) and exploring how they can be applied to improve the company's products or services.• Providing training for technical staff or end users on the operation and maintenance of machine vision systems, as well as offering ongoing technical support.• Ensuring that all machine vision solutions comply with industry standards, safety regulations, and company policies.

• Product specialist for all Cognex line of products on machine vision. • Develop custom machine vision applications and manage all machine vision related data and analytics using Al, Machine Learning, and Deep learning based tools . • Generate, collect, and test data models to provide robust solution for machine vision applications.• Develop deep learning and machine learning models, design supervised and unsupervised deep learning models. • Interact with internal/external customers to understand needs, develop specifications, and ultimately deliver outstanding integrated customized turnkey solutions. • Conduct demonstrations and trials of the product at customer sites, trade shows, seminars, and events.• Complete evaluation reports and provide the best recommendation that fits within the requirements of the application. • Provide customer and engineers training as per need.• Manage data analytics, computational systems, and AI/deep learning tools.

• Data mining and extracting usable information from valuable data sources.• Creating new datasets and variables that can be leveraged through the project capabilities, work closely with the research, business, and other team members to develop the final data product. • Testing and validating the integrity of data which can be used in analytical modeling.• Performing error analysis and using algorithms to improve models and maintain uniformity and accuracy.• Analyzing large datasets to find relationships, linkages, and patterns – develop prediction and statistical models in SAS and Python - and implement these models in collaborating with machine learning team. • Design machine learning algorithm, if needed develop novel algorithm, and generate explanatory data to test working hypotheses.• Interpreting final data and results with clear objectives - presenting valuable information with other team members and business partners in a communicable way.

• Established instructional and research labs and trained lab instructors on safety, usage, installation, and demonstration of electronics and optics experiments. • Managed data analytics team for data collection, data management, and data analyses to accomplished the research projects. • Managed research and data management projects and help of academic team in research. • Designed computational and analytical framework of virtual models and simulations for graduate/undergraduate physics, optics, and electronics lab experiments. • Taught various undergraduate and graduate courses including Physics, Optics, Electronics, Computational techniques, MATLAB, Python, JAVA, C, and Assembly

• Headed graduate research team on optics, single photon detection techniques, solar cells and photovoltaics.• Built computational and statistical models for data analysis for the quantitative and qualitative research, data management, and data wrangling.• Generated large Monte Carlo data to developed simulations and test the theoretical models using multiprocessing and threading techniques. • Developed two-dimensional computer analysis of a tandem solar cell: c-Si/a-Si:H/μc-SiGe, with Lumerical FDTD/DEVICE 4.6• Performed optical characterization of solar cells in FDTD to transport total generation into DEVICE for electrical characterization.• Simulated it 3D model and designed computational algorithm with MATLAB and Python