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Ramakrishna Koganti

Ramakrishna Koganti

Ramakrishna Koganti, UT Arlington & UT Dallas

Rama Koganti is currently working in Healthcare Industry as a Data Analytics Program Director. Rama Koganti is an Adjunct Professor at UT Arlington and UT Dallas and his research interests are Machine Learning, Autonomous Vehciles, Big Data, Data Analytics, and Predictive Modeling. Rama also worked in Automotive Manufacturing (Ford Motor Company), DoD (US Army) and in healthcare (Baylor Scott and White, JPS Health Network, Cook Children's Healthcare System, and UT Southwestern). Rama's work in Automotive include lightweight materials, automotive body construction, occupant safety (active and passve), Autonomous vehicles and automotive manufacturing processes. He was also responsible for advanced vehicle safety and he spearheaded design and crash testing of the vehicle components, sub-systems and body structures. Rama launched many vehicle programs and he was a subject matter expert at Ford, Jaguar, Land Rover, Aston Martin, Volvo, Mazda. He holds 5 patents in Automotive Engineering and few in pending. He published over 100 papers in Automotive Engineering, Process Optimization, Product Design and Manufacturing, Vehicle Safety, Technology Development and Deployment and Data Analytics.

Rama Worked at US Army (at White Sands Missile Range, NM) and he was responsible for strategy and implementation of Solar Energy Plant (Mobile). Rama also led the strategy and execution of spectrum management project. Rama has executed numerous programs in Healthcare Systems related to Process Improvement and Operational Efficiencies (eliminating waste, improving throughput, optimizing resources etc...).

He gave numerous talks at National and International Conferences. He has been serving various leadership roles at International Mechanical Engineers World Congress (IMECE) for the past 10 years. He was IMECE Congress Steering Committee Senate Chair from 2018 to 2019. He received two Henry Ford Technology Awards (Most prestigious award at Ford) from Research and Innovation Center (RIC)/Ford Motor Company. He also received Henry Ford II award for Automotive Excellence from Society of Automotive Engineers (SAE). He is currently serving a Track chair at SAE for Big Data, Artificial Intelligence and Machine Learning Tracks. He served as Vice Chair for Integrated Design and Manufacturing Division at Society of Automotive Engineers for 2022 SAE World Congress. He is the Chair for the Integrated Design and Manufacturing for 2023 SAE World Congress. He is also member of Sustainable Development Committee.

He received his MS in Mechanical Engineering from Concordia University, Montreal, Canada. He also received an MS in Total Quality Management from Eastern Michigan University. He is a certified Lean Six Sigma Master Black Belt and Six Sigma Black Belt.