• Led the development of a chatbot to enhance tool adoption and usability.• Designed functionalities to provide accessible training content and quick answers.• Ensured the chatbot was intuitive, easy to use, and capable of finding accurate references.• Integrated conversational AI functionality, image, and video capabilities for a comprehensive user experience.• Leveraged Microsoft Copilot’s conversational AI with RAG-based powerful AI search engine.• Established optimal performance data thresholds for unlocking product insights, enabling precise decision-making and timely testing iterations.• Analyzed relationships between material changes, product performance, and consumer responses, providing unprecedented insights.• Used historical data to construct models that unveil new benefit spaces and innovation, propelling product development and differentiation.• Automated report generation, identified hidden patterns in test results, and reduced duplication of work, leading to extraordinary insights and efficiency gains.• Explored opportunities to expand chatbot integration into other systems, fostering innovation and enabling scalability in intellectual property, specification management, and chemical inventory control.• Established governance, access controls, and support models to ensure the scalability and reliability of the chatbot solution.• Coordinated with internal teams and vendors for development and ongoing support.

• Owned, and spearheaded GenAI-based end-to-end digital twin development and synthetic image generation roadmap and pipeline for training, evaluating, exploratory image analysis and optimizing AI-based models.• Proficient in understanding customer pain points and swiftly translating requirements into actionable insights and solutions, enabling development teams to rapidly address and resolve customer issues, while collaborating with R&D, Marketing, Manufacturing, Quality, and Instrumentation teams to ensure tailored and efficient project solutions and feature delivery.• Collaboratively led developers to develop an integrated physics and procedural-based simulation of 3D objects for image generation using Duality Falcon, USD, Unreal Engine, Nvidia A10 GPUs, DirectX12, Vulkan Ray Tracing, and OpenGL.• Managed a high-performance networking system for an online AI-based inspection system, utilizing fiber optics to ensure high speeds, low latency, and high reliability, resulting in efficient and reliable real-time data transfer and processing.• Enabled online deep learning-based vision inspection using the Nvidia DGX platform, eliminating offline inspections, and providing adjustable response times for defect identification, resulting in anticipated savings of $1.5 million in scrap and lead time over 5 years, enhancing end-user satisfaction and profit margins.• Automated the CAD to polygonal mesh conversion process using FreeCAD/Python API and streamlined the 3D object appearance variation workflow reducing digital twin processing time from 6 months to less than 1 hour.• Demonstrated exceptional troubleshooting, debugging, and code review skills • Designed and documented technical applications and findings, delivered review presentations with over 90% approval from external partners, aligned business goals with stakeholders achieving a 95% alignment rate, and secured additional project funding through effective communication and demonstration of project value.

• Generated, acquired, assembled, labeled, and accurately annotated synthetic semantic labels and radar point cloud data for autonomous driving scenarios that might be difficult to test in a real-world situation like foggy weather using CARLA simulator/Python API/Linux.• Researched, modeled, and built 3D image processing models, YOLOv5-based fused camera-radar object detector for autonomous vehicles using Python/TensorFlow/PyTorch/CUDA cuDNN v11/CARLA/Unreal Engine/Ubuntu, improved with spatial & channel attention to focus on relevant feature maps, mitigated false positives, errors & missed detection, & improved detection accuracy by 35% in fog.• Modeled, simulated and developed a DeepSORT-based multi-object tracking model improved with GhostNet to generate more feature maps, reduce computational complexity and cost, and improve tracking speed. The segmentation module, which adds rich semantic information to the low-level appearance feature maps, aids in the differentiation of objects with high appearance similarities while reducing object identity switches and track failures in fog by 47%.• Predicted electricity prices by modeling linear and logistic regression in K-Nearest Neighbor and Support Vector Machine algorithms in Python to create energy savings awareness in consumers and cut utility costs by 50% and save $500.• Developed and deployed Django application to Docker Container using Docker Compose with version control (Git/CI/CD)• Developed and deployed Django application to Kubernetes nodes for scaling on both server and serverless cloud - AWS EC2.• Mentored about 20 undergraduates and high school students improving STEM enrollment among minorities by 30%.

• I supervised and examined the lab to guarantee that all 15 employees had access to and were properly using the necessary safety gear. • Responsible for liaising with the laboratory and the FAMUFSU College of Engineering's safety department to guarantee compliance with all regulations.

• Developed and modified scripts for workflow management to meet clients' needs using JavaScript, SQL, and Python.• Performed quality assurance and validation after data acquisition, profiling, and analysis using agile methods and lean principles, reducing lead time by 40%. • Documented customer problems/solutions to create easy-to-follow end-user documentation and constantly updated design documents improving client productivity by 35%.

Center for Intelligent Systems, Control, and Robotics.• Performed experiments demonstrating that bandstop wave filter is capable of decreasing wave reflections (instabilities) visualized as FFTs using a telerobotic system consisting of two Force multi-dimensional parallel manipulators.• Evaluated metrics (cut-off frequency) showed that the bandstop wave filter performed better by 81% and 67% compared to the traditional wave variable method and wave shaping filter respectively.

• Tutored 45 students during office hours and provided instructions and guidance to during examination (Core course in mechanical engineering undergraduate program)• Taught laboratory sessions and performed laboratory demonstrations• Provided technical support to students during laboratory sessions• Collated and graded student’s assessments

• Shadowed (Manager of Avionics, Electrical, and Software) to increase knowledge of career path and skills needed to be successful in software engineering• Worked with the software engineering team on testing and validating newly developed and updated software to be used on aircraft• Introduced to software bench test, ground test and pre-flight test.

Center for Soil and Water Quality.• Assisted in obtaining data at Apalachicola forest for climate monitoring purpose.• Analyzed data collected from the upper Floridian aquifer system in order to determine ground water quality.

Center for Accessibility and Safety for Aging Population.• Assisted in reviewing technical papers written on the implementation of self-driving cars on the United States roads.