Ashwadip Garud

Analyzing and developing algorithms and models based on data science and AI for COVID-19 data:
• Worked on "Integrated and Unified Data Model for Publication and Sharing of Prolonged Pandemic Data as FAIR Semantic Data: COVID- 19 as a case study".
• Worked on knowledge modeling/ontology building, knowledge extraction, knowledge validation for covid-19 data.
• Developing statistical text computing algorithms and code optimization of various knowledge modeling projects. Have used sparql, rdf, protege, spacy, nltk, and python.
• Developing desktop application, web applications, and APIs of services used for knowledge modeling and ontology building with Python, Django, Tkinter, and Docker.
• Writing and evaluating SPARQL queries to extract data from knowledge graphs in order to show it on web.

• To make core banking and banking system processes intelligent, developed models for the core banking processes and banking system software components using data science, AI, machine learning, and deep learning, and then tested and deployed them using Docker containerized APIs
• Worked on and contributed to financial crime mitigation, payment repair, COB optimizations, outliers, anomaly analysis and detection, recommender systems, credit risk, and loan lending algorithms and models
• Implemented NLP-based components for next question pre-emption, question classification, questions, and word auto-completion to help the chatbot
• Worked on feature engineering to transform data, which helped train and build ML and DL models
• Developed and documented models on the XAI platform and mentored juniors.

• Multi-lingual computing (Indian scripts), Structured and unstructured ,text data extraction from different text data resources (pdfs, words, tables), web scraping, and crawling to build language corpus
• Applying statistical analysis on text data for finding some pattern to get the content of a paragraph
• Developing machine learning applications: human image identification for the ECI project; gender identification based on the photo and name of a person that reduces mismatches in photo and gender type information by 67%.

• Mathematical and statistical modeling, organization, calibration, analysis, and dissemination of space astronomy data
• Applied advanced probability and Bayesian concepts and methods for data sent by ASTROSAT for outer space sources to locate it
• Stochastic modeling and simulations on astronomical data for locating the gamma-ray radiating sources
• Applied computational geometry for the CZTI payload to develop a side mask
• I applied the numerical method of curve tracing to astronomical data
• Developed a database for data sent by ASTROSAT
• Data extraction, transformation, and cleaning
• Monitoring functions, commanding CZTI (ASTROSAT's payload), and automating data processing tasks using Linux shell scripting
• Presenting and educating about the data pipeline of "ASTROSAT" to post-doc fellows and space agencies, visiting scientists, astronomers, and PhDs.