Santosh Srinivasaiah

I work as a Scientific Programming Lead at Booz Allen Hamilton. Bridging the gap between Software Engineering and Machine Learning model to scale for Federal and Commercial clients. My work has been on applying Computational Neuroscience, engineering and science, & technology. For the past 19 years, I have been learning and taking a unique polymath approach when developing an ML system to scale and take on roles to specialize into domain experts who deeply understand the business problems, modeling to develop predictive models, and platform builders to create the cloud-based infrastructure. To help me with these skills, I apply a variety of tactics: organize and attend Meetups, Hackathons, attend conferences on machine learning and data science. I fervently read books on, statistical algorithms, Software technologies and best practices, Computational Neuroscience, Fourier Transform, build POC, experiment with Open Source and more; I also provide internal talks year round on engineering details behind projects, and cutting-edge advances from academic research; Having a seamless development experience covering [possibly] all the different stages in the process is what I have from many years of experience. But getting here is far from easy! To me education and learning attitude is the key to developing our talents. My current projects are in the field of Human Dimension performance measures, Financial Fraud and Brain Computing. We apply complex machine learning algorithms and models using tools such as EC2, Apache Spark, Apache Nifi, Hadoop, Redshift, Solr, Elastic, Microservices to sequence data models. We work on applying Deep Learning skills to an unstructured data using the ConvNet [LSTM], and Markov Chain model design. For Brain Computing, We use an non-invasive EEG recorder to measure brain waves and analyze cognitive thoughts and patterns for Stress level measurements, and analytical processing using EC2, Apache Spark, Hadoop, Python, Java and different ML models. Machine Learning workflows are typically non-linear and may contain several feedback loops. I look forward to connecting with you. Happy Learning!