End-to-end AI/ML builder with a strong foundation in physics, hands-on IoT and embedded systems experience, and demonstrated ability to deploy machine learning solutions in real-world, resource-constrained environments. …
End-to-end AI/ML builder with a strong foundation in physics, hands-on IoT and embedded systems experience, and demonstrated ability to deploy machine learning solutions in real-world, resource-constrained environments. Experienced in collaborating with research institutions and domain experts to translate complex problems into practical, impactful AI solutions. Passionate about responsible AI for public good in LMICs.
<p>Collaborated with Bharathidasan University to develop an ANN-based prediction interface estimating optimal algae dosage for polluted water treatment<br>
Reduced calculation time from several days to seconds with 95%+ model accuracy<br>
Deployed on AWS SageMaker and EC2<br>
Designed and deployed an automated plant growth monitoring system for a PhD candidate using Raspberry Pi and Arduino<br>
Engineered UV day/night simulation, dual-camera image capture every 30 minutes, and real-time temperature/humidity logging<br>
System handed over and still operational<br>
Developed an R programming package for research purposes<br>
Currently in the process of submission to CRAN<br>
Built automatic data logging systems using Arduino for various research and IoT use cases</p>
Collaborated with Bharathidasan University to develop an ANN-based prediction interface estimating optimal algae dosage for polluted water treatment — reduced calculation time from several days to seconds with 95%+ model accuracy; deployed on AWS SageMaker and EC2, Designed and deployed an automated plant growth monitoring system for a PhD candidate using Raspberry Pi and Arduino — engineered UV day/night simulation, dual-camera image capture every 30 minutes, and real-time temperature/humidity logging; system handed over and still operational, Developed an R programming package for research purposes — currently in the process of submission to CRAN, Built automatic data logging systems using Arduino for various research and IoT use cases
<p>Designed and maintained automated Python-based ETL pipelines to ingest, clean, and deliver sanitised data into Power BI dashboards, enabling weekly C-suite business insights<br>
Reduced pipeline execution time from 40 minutes to 9 minutes (77% improvement) by redesigning input file formats<br>
Built an end-to-end daily automation workflow ingesting customer data from the company website, processing via cleaning scripts, pushing to SharePoint, and auto-refreshing Power BI<br>
Collaborated with manager to identify manual workflows and convert them into automated Python solutions, reducing operational overhead across the team</p>
Designed and maintained automated Python-based ETL pipelines to ingest, clean, and deliver sanitised data into Power BI dashboards, enabling weekly C-suite business insights, Reduced pipeline execution time from 40 minutes to 9 minutes (77% improvement) by redesigning input file formats — a systematic, root-cause approach to performance optimisation, Built an end-to-end daily automation workflow ingesting customer data from the company website, processing via cleaning scripts, pushing to SharePoint, and auto-refreshing Power BI — completed within a 2-hour window, 6 days a week, Collaborated with manager to identify manual workflows and convert them into automated Python solutions, reducing operational overhead across the team
<p>Applied ML and Deep Learning techniques to real-world client projects under mentorship<br>
Gained hands-on experience in model development, evaluation, and deployment workflows</p>
Applied ML and Deep Learning techniques to real-world client projects under mentorship, Gained hands-on experience in model development, evaluation, and deployment workflows
<p>Converted Audio signals into mel-spectrogram images, created data pipelines and trained CNN and Transformer models to classify the genres. Deployes the model in Hugging Face for user interaction.</p>
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