ML, AI, Deep Learning, NLP, Computer Vision, CS

Bhavya Minesh Shah

Email: *******@***.*** Phone: +1-623-***-**** Location: Tempe, Arizona

LinkedIn: www.linkedin.com/in/bhavya-minesh-shah GitHub: www.github.com/BhavyaShah1234 Research: https://scholar.google.com/citations?user=34NoLQ8AAAAJ&hl=en EDUCATION

Master of Science in Robotics and Autonomous Systems (Artificial Intelligence) Expected May 2026 Arizona State University, GPA: 4.0 / 4.0 Tempe, Arizona, United States Bachelor of Technology in Computer Science and Engineering July 2023 Vellore Institute of Technology, CGPA: 7.8 / 10 Vellore, Tamil Nadu, India PROFESSIONAL EXPERIENCE

Artificial Intelligence Engineer August 2023 - May 2024 Accurate Industrial Controls Pvt Ltd Pune, Maharashtra, India

• To enhance efficiency and scalability, I developed a machine learning pipeline for automating defect detection in LPG cylinders, leveraging computer vision and AI techniques. The pipeline was optimized to generalize across various manufacturing processes, ensuring adaptability for diverse industries. This solution streamlined defect detection, significantly reducing manual efforts and enabling a scalable, automated workflow.

• I designed the B-Star algorithm to address the inefficiencies of the existing path-planning system for an Autonomous Boat project, focusing on real-time marine navigation. By leveraging graph-based approaches and heuristic optimization, B-Star replaced the A-Star algorithm for grid-based path planning. This innovation improved algorithm speed by 300%, significantly enhancing the boat's autonomous navigation capabilities.

• To address inconsistencies in synchronizing camera and radar sensor data caused by hardware clock variations, I proposed using UNIX timestamps for accurate data fusion. Collaborating with the development team, I implemented this solution, replacing the microcontroller-based clock system. This improvement significantly enhanced data integration accuracy, boosting the reliability of real-time sensor fusion systems.

• I mentored a team of interns, guiding them in applying AI concepts to practical projects in industrial automation. Through hands-on training and collaboration with hardware and software teams, I facilitated their learning and project execution. This effort enhanced team productivity, deepened the interns' understanding of AI applications, and ensured successful completion of key initiatives. INTERNSHIP EXPERIENCE

Machine Learning Intern September 2022 - March 2023 Swasthya.ai Mumbai, Maharashtra, India

• The company sought to digitize and structure extensive unstructured medical data from OPD records and prescription notes. To address this, I developed and implemented a Python-based pipeline using NLP techniques like lemmatization, stemming, and regex processing to clean and process medical records. This solution automated data extraction, significantly reducing manual effort and improving efficiency.

• Medical abbreviations and inconsistencies were causing inaccuracies in information extraction from records, impacting downstream machine learning models. To address this, I expanded abbreviations and standardized medical terminology in the data pipeline, utilizing BERT for named entity recognition. This improved model accuracy and reduced false positives by 80%, ensuring reliable and consistent data extraction.

• To ensure the accuracy of the extracted medical entities, I collaborated with an oncologist to review and refine the extraction pipeline. Incorporating their feedback, I made adjustments to align the results with clinical standards, enhancing the tool’s practicality. This collaboration led to the delivery of a clinically validated extraction tool, increasing its reliability and trustworthiness among stakeholders.

• To manage the growing dataset and computational needs, I deployed machine learning models on cloud platforms such as AWS and Microsoft Azure. By optimizing the performance of the models for cloud environments, I ensured scalability and efficiency in handling large datasets. This approach significantly enhanced the reliability and seamless operation of the system.

TECHNICAL SKILLS

• Programming Languages: Python, C/C++, Java, JavaScript, MATLAB, PHP, HTML, CSS, JQuery, AJAX, Bootstrap, SQL, NoSQL, MongoDB, PostgreSQL

• Domains: Artificial Intelligence, Machine Learning, Deep Learning, Robotics, Computer Vision, Natural Language Processing, Computer Science, Web Development, Automation, Reinforcement Learning, Statistics, Calculus, Linear Algebra

• Technologies: Docker, Robotic Operating System, Gazebo, OpenCV, Django, Flask, TensorFlow, PyTorch, MediaPipe, Selenium, BeautifulSoup, LangChain, NVIDIA Triton Inference Server and Client, ONNX, TensorRT, Large Language Models, Transformers, Robot Kinematics, Robot Dynamics, Sensor Fusion, Path Planning, AWS, Microsoft Azure, Microsoft Office 365.

PROJECT EXPERIENCE

• Object Measurement using Computer Vision [March 2021 - May 2021]

• Maze Solver Robot [November 2024 - December 2024]

• Image Captioning, Text Summarization and Language Translation Transformer [July 2023 - August 2023]

• Simulation of BStar for Path Planning [May 2024 - July 2024]

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