Chief Data Scientist | Generative AI | Author “Keras to Kubernetes" | ex GE | 11 Patents
23 Years of Experience
Goa, Goa, India
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Not Available
I am the Chief Data Scientist at Persistent driving the overall AI strategy with particular focus on Generative AI. I show a path for enterprises to move from automation to intelligence. I lead a team of world-class data scientists building accelerators around large language models (LLM), knowledge graphs, federated learning, hyper-personalisation and computer vision. We partner with strategic customers in BFSI, Healthcare, Pharmaceuticals space to deliver outcomes like improved productivity, intelligent integrations, conversational AI and actionable insights. Earlier, I worked for 20 years at General Electric (GE) incubating innovation offerings around gas turbine remote monitoring & diagnostics (RM&D), machine prognostics and video analytics for track inspection. I am a published author, regular contributor to VentureBeat and have 11 patents granted in the US.
Persistent Systems, IT Services & Solutions, Computer Software
GE Transportation, a Wabtec company
GE Power
Persistent Systems, GE Transportation, a Wabtec company, GE Power, GE Power, GE Global Research
Job Title : Chief Data Scientist
Company name : Persistent Systems
Period : May 2019 - Present
Summary : Championing the Generative AI strategy for the company focused on specific outcomes around developer productivity, workflow automation and smart virtual assistants. Incubated task force on Generative AI for evaluating large language models (LLM) and applying to niche areas like clinical trials, drug label search, financial insights, policy document q&a and loan underwriting. Leading Responsible AI offering with analysis of fairness, bias, explainability and interpretability. Developed a Knowledge Platform offering that leverages state-of-the-art language models, graph databases, embeddings and GNNs to enable diverse outcomes from drug discovery to anti-money laundering, fraud prediction and recommender systems. Applying the Knowledge Platform to develop a clinical KG to help predict drug-drug interactions using genomic relations. Building an adaptive enterprise-wide Cybersecurity platform to enable network anomaly detection (using auto-encoders), Transformers for DGA prediction and adaptive incident response (contextual bandits). Championing a deep learning liquid biopsy platform to process blood microscopy images and count circulating tumour cells.
Location : Goa
Job Title : Principal Architect
Company name : GE Transportation, a Wabtec company
Period : January 2013 - May 2019
Summary : Played role of Innovation Leader for a 400+ strong India Engineering team. Championed the remote Track Inspection solution using video from Locomotive-mounted camera called LocoVISION. Incubated LocoVISION inspection from an idea to an Industrial Internet solution with state-of-the-art video processing and Computer Vision algorithms. Extended this idea to build demonstrations around driver fatigue monitoring, thermal camera inspection and PTC assets inventory management.
Architected a Kubernetes-based Cloud Platform to deliver a standardized path-to-production and DevOps for Machine Learning (ML) algorithms. Empowered Data Scientists with cutting-edge tools like AI workbenches (H2O.ai, Jupyter), ML workflow pipelines (Kubeflow), Model Deployment (TensorFlow-Serving) and distributed runtimes with BigData and GPU clusters.
Location : Bengaluru Area, India
Job Title : Chief Software Architect
Company name : GE Power
Period : January 2007 - January 2013
Summary : Developed the Technology road-map for GE Power's Remote Monitoring & Diagnostics (RM&D) center at Atlanta that monitors more than 2000 Gas Turbines 24/7 across the world. Championed the simplification of overall System Architecture for Edge to Back-office data transfer, scalable Analytics and Business Intelligence. Incubated major initiatives like Common Rules Engine program - that integrates individual AI engines like Fuzzy Inference and Neural Networks into a unified environment with shared Asset model, Orchestration and Dashboards. Actively represented RM&D in synergy efforts with other Power businesses like Oil & Gas and Electric Utilities. Adopted best practices like Common Information Model (CIM) from Utilities domain and applied to Power-Gen by adopting standards like OpenO&M.
Location : Norfolk, Virginia Area
Job Title : Lead Software Engineer
Company name : GE Power
Period : June 2004 - January 2007
Summary : Part of team that built an AI Expert system for Condition Monitoring of rotating Machinery. Using a Knowledge-base of monitoring rules, the Fuzzy Logic inference engine tries to infer patterns of failure. Led the development of a Java-based Enterprise portal that packaged and deployed these rule-packs to 1000s of Gas Turbines at remote locations. Developed solutions to interface with Power Plant Software like HMI, Historians and CMMS using open standards like MIMOSA, OPC and OPC-UA.
Location : Norfolk, Virginia Area
Job Title : Research Engineer
Company name : GE Global Research
Period : August 2000 - June 2004
Summary : Led the development of a Knowledge-based Engineering (KBE) solution for Transportation CAD systems. Leveraged System-level thinking to co-relate high level requirements and flow them down to individual component geometry changes. Developed solutions using Unigraphics and Knowledge Fusion to capture Design Knowledge into the system - through multiple interviews with Designers understanding their thought process. Achieved significant reduction in model building time and improved overall Design Quality.
Location : Bangalore, India
Title : Neural Networks and Deep Learning
Period : September 2017 - Present
Summary : ZGGAV9YSX5H8, https://s3.ap-south-1.amazonaws.com/dattaraj/Coursera+ZGGAV9YSX5H8.pdf
Issuing Authority : Coursera
Title : Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization
Period : August 2017 - Present
Summary : EVSW2UZQGWBQ, coursera.org, https://www.coursera.org/account/accomplishments/verify/EVSW2UZQGWBQ
Issuing Authority : Coursera
Title : Structuring Machine Learning Projects
Period : August 2017 - Present
Summary : VZD8Q7QVYZ4R, coursera.org, https://www.coursera.org/account/accomplishments/verify/VZD8Q7QVYZ4R
Issuing Authority : Coursera
Title : Developing Innovative Ideas for New Companies: The First Step in Entrepreneurship
Period : August 2014 - Present
Summary : coursera.org, https://www.coursera.org/course/innovativeideas
Issuing Authority : Coursera
Title : Cryptography I
Period : August 2013 - Present
Summary : CS255, dropbox.com, https://www.dropbox.com/s/opsmenq9gmjdieg/Coursera%20Crypto%202014.pdf
Issuing Authority : Coursera
Title : Machine Learning
Period : August 2013 - Present
Summary : VZD8Q7QVYZ4R, https://s3.ap-south-1.amazonaws.com/dattaraj/Coursera+ml+2017.pdf
Issuing Authority : Coursera
Title : Introduction to Data Science
Period : July 2013 - Present
Summary : dropbox.com, https://www.dropbox.com/s/tnvtmbxvqcnz7uq/Coursera%20datasci%202014.pdf
Issuing Authority : Coursera
Title : Healthcare NER Models Using Language Model Pretraining
Publisher : Cornell University
Publication time : 2020
Summary : In this paper, we present our approach to extracting structured
information from unstructured Electronic Health Records (E
Title : VIDEO SYSTEM AND METHOD FOR DATA COMMUNICATION Patent number : US2019042861 Publication time : 17.1.2019 Summary : A camera system and method capture image data with a camera, a data storage device electrically connected to the camera and con
English (Full Professional), Hindi (Professional Working), Konkani (Native Or Bilingual), Marathi (Elementary)
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