Priyanka V Galagali
Development
Karnataka , India
Skills
Data Science
About
Priyanka V Galagali's skills align with Programmers (Information and Communication Technology). Priyanka also has skills associated with IT R&D Professionals (Information and Communication Technology). Priyanka V Galagali has 5 years of work experience.
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Work Experience
AIML Engineer
DIMAAG-AI
October 2022 - Present
- Led the design and execution of a computer vision-based quality control system for a manufacturing company, utilizing image analysis techniques to identify product defects, leading to improved quality standards and waste reduction. Developed and implemented machine learning algorithms tailored for hyper spectral image analysis, enabling accurate prediction of brix and pH values in grapes. Leveraged computer vision methodologies to efficiently segment images and extract pertinent features to support in-depth analysis. Collaborated on research and development initiatives, working closely with experts in AI/ML and computer vision domains. Employed a technology stack encompassing NG Transfer, image segmentation, regression algorithms, and various advanced computer vision techniques. Experienced in leveraging the computational power of NVIDIA CUDA technology for high-performance GPU computing in computer vision tasks. Proficient in utilizing TensorFlow to construct and train advanced machine learning models, including convolutional neural networks for image recognition and segmentation Skilled in applying Python packages such as NumPy, Pandas, Matplotlib, OpenCV, and scikit-learn for data analysis, image processing, and visual representation of complex data sets. Demonstrated ability to optimize computer vision algorithms for real-time processing and integrate machine learning solutions into practical applications. CONTRIBUTIONS: Involved in the development and deployment of machine learning algorithms for autonomous vehicle navigation and decision-making systems. This includes: Designing and implementing image segmentation techniques to distinguish between various onroad scenarios, improving the vehicle's perception systems using state-of-the-art machine learning models. Developing object detection models using TensorFlow to recognize pedestrians, traffic signs, and other vehicles in real-time, enhancing situational awareness and safety. Utilizing CUDA-enabled GPUs to accelerate deep learning inference tasks, resulting in efficient and faster processing times suitable for real-time applications in autonomous driving. Employing sensor fusion techniques to integrate data from LiDAR, radar, and cameras, crafting a comprehensive environmental model for precise vehicle localization. Applying reinforcement learning for route planning and optimization, enabling the vehicle to make intelligent path decisions in dynamic and unpredictable traffic conditions. Conducting rigorous testing and validation of machine learning models against large datasets to ensure reliability and accuracy under diverse driving scenarios. Collaborating cross-functionally with software developers, engineers, and data scientists to translate machine learning insights into actionable driving strategies for prototype development." "Engineered machine learning models for accurate depth estimation from stereo imagery, critical for autonomous navigation and 3D reconstruction. Key projects and responsibilities included: Optimizing convolutional neural networks (CNNs) for depth estimation tasks, utilizing TensorFlow and Keras to improve model performance and efficiency. Integrating depth sensing with real-time image processing algorithms on CUDA-enabled devices, achieving significant improvements in processing speeds. Developing simulation environments to test depth estimation models under controlled scenarios, using synthesized datasets to train models before real-world deployment. "Specialized in developing advanced image segmentation models to accurately classify and delineate different objects within digital images, facilitating precise analysis and interpretation. Key accomplishments and projects included: Model Development: Engineered and fine-tuned deep learning models using U-Net and Mask R-CNN architectures, successfully improving the granularity and accuracy of segmentation for complex scenes. Technology Integration: Implemented image segmentation pipelines integrating TensorFlow and PyTorch frameworks with Python's scientific stack (NumPy, SciPy) and OpenCV for image manipulation and processing tasks. Performance Optimization: Leveraged CUDA acceleration to enhance algorithm performance, enabling real-time segmentation and analysis of high-resolution images for dynamic environments. Data Management: Curated and augmented diverse image datasets, ensuring robust model training that accounts for a variety of environmental and lighting conditions common in real-world scenarios. Cross-functional Teamwork: Collaborated with software engineers, UI/UX designers, and product managers to integrate segmentation models into user-centered applications, enhancing the interactive experience of end-users. Research and Development: Stayed abreast of cutting-edge advancements in machine learning and computer vision, applying the latest research findings to ongoing projects to maintain technological edge and leadership. Quality Assurance: Established rigorous testing protocols for model validation, using precisionrecall metrics to ensure high reliability and accuracy of segmentation outputs for critical applications."
Internship Trainee
Nokia, Bangalore Urban
August 2021 - February 2022
- Engaged as an intern, focusing on cloud technologies to enhance my skills and knowledge. Gained practical experience with various cloud platforms, including AWS, Azure, and Google Cloud. Assisted in the setup and configuration of virtual machines, storage solutions, and networking services within cloud environments. Collaborated on the deployment of applications using cloud-based infrastructure and services. Acquired proficiency in containerization technologies like Docker and orchestration with Kubernetes. Worked alongside experienced professionals, learning the intricacies of cloud architecture and management.
AI Engineer
UNV IT software Pvt Ltd
June 2019 - July 2021
- Engaged with a startup focused on AI and machine learning, specializing in cutting-edge technologies. Introduced a groundbreaking product: an IoT-based online smart parking system. Orchestrated the backend operations using Java, while employing HTML & CSS for the frontend. Managed the database using MySQL for seamless data management. Pioneered the creation of the smart parking system from the ground up, leveraging the Python/Django framework. Undertook complete end-to-end development and thorough website testing. Led the product development cycle, spanning from initial business case comprehension to final implementation. Placed a strong emphasis on data security and seamless API integration.
Intern
Hughes Systique
June 2018 - June 2019
- Engaged in a recommendation project centered on analyzing user behavior data to create tailored suggestions for users. Constructed machine learning algorithms to enhance recommendation precision by predicting user preferences. Executed exploratory data analysis and implemented data cleansing techniques to uphold data integrity. Employed A/B testing methodologies to gauge the effectiveness of recommendation models. Collaborated closely with diverse teams to grasp business needs and translate them into feasible technical solutions. Delivered insights and suggestions to senior management, encapsulating project findings and outcomes.
Education
BNM Institute Of Technology
Master's degree
January 2021 - January 2022
S J B Institute of Technology
Bachelor's degree
January 2015 - January 2019
