Developing a multi-class classification model to predict plant composition and its spatial and temporal changes using predictors, including satellite image, climate time series, and other environmental data such as land cover, human footprint, bioclimatic, and soil variables. The goal is to enhance biodiversity management, improve species identification tools and support educational efforts.
Developing recommender systems using contextual bandits for an e-commerce platform.
Building Deep Neural network models that predict floods affected areas
Leading and coaching a team of Data Scientists in developing advanced analytic models and bringing them to production
Coordinating the implementation of data science best practices and liaising with the Data Engineering and IT team in setting up the infrastructure needed and monitoring the guidelines implementation and governance
Conducting advanced statistical and other analysis to provide actionable insights identify trends, and measure performance within the DS models
Engineering features by using business acumen to find new ways to combine disparate internal and external data sources
Coordinating with data engineers, business leads, Commercial and IT to deliver holistic analytical solutions that are seamlessly incorporated into analytic data products
Ensuring functionality & insights in "run" through timely analysis and testing for regular maintenance of solutions over time
Liaising with stakeholders to disseminate AA-driven culture by supporting the Business Analytic translator in communicating the design, functioning and output of the analytical models/solutions developed
Advocating the value of data driven decision focusing on the "how and why" of solving problems and educating Translators in Data Science Models
Developing informed machine learning algorithms to enhance pedestrian detection, lane change and rule breaking scenarios in autonomous vehicles
Setup of big data pipelines in AWS for Test and Verification of ADAS functions
Created pipeline and dashboard for monitoring data ingest and storage using Elastic Stack (Beats, Logstash, Elasticsearch and Kibana).
Integrating new data by creating a full pipeline from ingestion to ETL process pipelines using airflow. The automated ETL pipelines extract 3 TB of data per month
Coordinating and collaborating with multiple departments and stakeholders to collect each team data requirements and developing a data strategy to support them in making data driven decisions
Developed machine learning algorithms used to increased efficiency in drug discovery by automating the identification of monoclonal wells
Build real time monitoring and advanced analytics of data from a battery storage farm using IoT Hub, Blob storage, Stream Analytics, SQL, Power BI
Working in an agile team, which strongly believes in the culture of shared code ownership, pair programming and code reviews
Designed and developed a system prototype which automatically classify and recognize specific object from huge amount of satellite images of different satellite sensors
Automatic feature detection from 1000 satellite images using convolution neural network (CNN)
Defined the output data product formats with automatic annotation and interfaces to enable users appropriate and effective access to the data
Assisted in developing in-house software for satellite data processing
Developed quantum impurity model technique (NRG and Monte Carlo) to simulate strongly correlated electron systems in condensed matter physics
Created software in C/C++ for parallel computing using hybrid parallelization technique (MPI and OpenMP)
Developed software in python for data visualization using Seaborn
Implementation, administration, monitoring and optimization of linux cluster of computing servers
Configure High Performance Data Storage/RAID, Archiving and Networking in a mixed NFS/CIFS environment
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