| | | 20,000+ Fresh Resumes Monthly | |
|
|
| |
Click here or scroll down to respond to this candidateCandidate's Name
EMAIL AVAILABLE PHONE NUMBER AVAILABLE GitHub LinkedInProfessional ExperienceMechanical Engineer Research Scientists, Lighthouse Regulatory Consulting Group May 2024 Present Developed advanced control algorithms for AI-based biomedical devices, achieving up to a 30% improvement in system efficiency and a 25% reduction in processing time, ensuring peak performance across various applications Created an automatic defect detection system using AI-based control systems. Used the identified faults as feedback to the controller reducing error rates by 35% Performed thermal and failure analysis for product development, optimizing control algorithms and validating solutions to enhance system reliability for 6 biomedical device companies Tech Lead of Engineering Team, Sloan Lubricating Systems Aug 2023 - Mar 2024 Led cross functional engineering and analytics team of five people Designed a digital twin framework for Sloan Lubrication Systems which reduced maintenance costs by 30% Guided the technology selection process for designing a digital twin framework, integrating machine learning models, IoT devices, and PLCs to enable predictive maintenance Optimized the performance and the design of the products using GD&T, ANSYS, and SolidWorks while ensuring reliability and reducing the production costs by 20% PhD Research Assistant (Digital Twins), University of Pittsburgh Aug 2021 Mar 2024 Designed an explainable double-agent actor-critic Deep Reinforcement Learning based control algorithm for replacing manual control strategies with automated AI based control strategies resulting in 50% cost reduction in nuclear power plant operations and maintenance Created a control system for heat water reactor of power plant using Simulink MATLAB and Creo Created a digital twin for PPs heatwater reactor using the XDRL algorithm and Simulink + controls and dynamics of the heatwater reactorResearch Assistant, Rowan University Aug 2019 Aug 2021 Designed, manufactured and optimized a novel soft robotic actuator for pressure injury prevention which indepen- dently controls normal and shear stresses at the human-machine interface using SOLIDWORKS and physics-based hybrid firefly and ant-colony algorithms for optimization. This design was validated using FEA (ANSYS), and physical prototypes were characterized, using image processing techniques such as Convolutional Neural Networks (CNNs) Optimized the performance and design of a pneumatic soft robotic actuator using physics-based optimization and Deep Reinforcement Learning (DRL). Evaluated the actuators performance experimentally, utilizing Finite Element Analysis (FEA) in ANSYS, 3D printing, and mold creation EducationMasters of Science, Mechanical Engineering, University of Pittsburgh Sep 2021 Sep 2023 Masters of Science, Computer Science, Rowan University Sep 2019 May 2021 Publications Candidate's Name , et al. "Explainable, Deep Reinforcement LearningBased Decision Making for Operations and Maintenance." NUCLEAR TECHNOLOGY Candidate's Name , et al. "Design Optimization of a Pneumatic Soft Robotic Actuator Using Model-Based Optimiza- tion and Deep Reinforcement Learning" Frontiers in Robotics and AI Candidate's Name , et al. "Intelligent Soft Robotic Pad for Pressure Injury Prevention" IEEE Technical SkillsDeep Reinforcement Learning - SOLIDWORKS - Matlab - Python - R - ANSYS Icepak - COMSOL Multiphysics - C++ - Revit - Creo - CNC Programming (Mastercam, G-Code) - Jira - OPCUA - AsyncUA - PID controllers - PLCs - PXIe-NI Chassis-Based Systems - ANSYS FEA - data analysis - algorithm development - FEA analysis - Siemens NX - Geometric Autodesk Inventor - Fusion360 - LabVIEW |
