I am a Data Science Enthusiast exploring the power of Analytics and Machine Learning.
Currently, I am working in the position of Senior Research Engineer at IBM Research Ireland on a European Innovation Framework H2020 project on the Renewable Energy Sources (RES) sector.
Previously, I have worked with Dr Edward Curry in Multimedia Complex Event Processing in the Smart Cities and Sustainable IT group at the Insight Centre for Data Analytics at NUI Galway (NUIG). Here, I was researching in the field of real-time analytics and pattern detection for Multimedia Data Streams.
I am an experienced software professional with 7+ years of diversified industry experience. Led projects on developing ML solutions for multi-modal analytics using Computer Vision and Neuro Symbolic AI. I have worked on Computer Vision problems, multi-modal data analysis, Knowledge Graphs, Complex Event Processing and Deep Learning. Experienced in MLOps / AIOps processes including ML training / serving pipelines, CI/CD pipelines.
Passionate about building computer vision AI tools with research interests in Big Data and Reinforcement Learning (RL).
MSc. Computer Science - Data Analytics, 2019
National University of Ireland, Galway
BTech. Information Technology, 2012
Gujarat Technological University, Ahmedabad
Technologies: Python3, TensorFlow, Pytorch, Docker, RedisGraph, RedisStreams, DNN models.
Technologies: Java8, EJB3, Python3, Spring Boot, Hibernate, Apache Qpid, Jboss7, PostgreSQL, Git, Maven, Protocol Buffers.
Technologies: Java1.6, Adobe Flex, Spring, Hibernate, IBM Websphere, Oracle 10g, Git, Maven, HP Load Runner.
The work presents GNOSIS an urban analytics event engine that continuously monitors the incoming stream of pavements and generates notifications about the Crossing Type. It uses the colour of the pavings and paving type to make predictions. The research demonstrates how GNOSIS can automate the pavement detection process and guidance analysis.
The paper demonstrates the Occupational Health and Safety use case queries. In future, multimodal data integration, edge-centric optimizations and developing more complex spatiotemporal operators are the key focus area of development in GNOSIS.
Multi-agent implementation of the popular Reinforcement Learning algorithms.
Built a LeNet5 based deep convolutional model in Keras with a triplet loss function