STATISTICAL MODELLING AND CIVIL ENGINEERING CONSULTANT @STRUCTURAL FORENSIC EXPERTS

Sept 2024 – Present

DATA SCIENCE CONTRACTOR @CLIMATEAI

Sept 2024 – April 2025

AL ENGINEER @MOTHERSHP

Feb 2024 – Oct 2024

• Innovated in-house fine-tuned LLMs based on Mistral 7B, Llama-2 to solve behavioral issues foster children face efficiently.

• Engineered and integrated design based on RAG to suggest interventions to parents of children suffering from complex trauma.

• Enhanced the advanced feedback system using RLHF, with MongoDB database further to ease the vector search indexes of the embeddings.

• Developed an AI-based CRM system with a Streamlit chat interface to enhance communication between caseworkers and parents, using Semantic Router to manage and integrate scheduling into existing calendars of caseworkers.

• Established backend data extraction pipelines that assimilate a child's previous history and compliance requirements set by behavior analysts, employing causal inferences, machine learning, and generative AI technologies.

data science intern @climateai

Mentor: Dr. David Farnham                                                                                                               

May 2023 – Aug 2023

• Developed a Python-based modular framework to model supply chain delays from climate threats at 40+ major ports using statistical techniques.

• Assessed Value at Risk (VaR) and Conditional Value at Risk (CVaR) for ports under various carbon emission scenarios, the framework extends over 20 decades and aids stakeholders from non-tech backgrounds in risk mitigation and portfolio management.

• Created a flexible architecture to estimate the financial impacts on assets from climate hazards, such as flooding, thus assisting clients in evaluating the potential range of costs happening due to physical, disruptive and operational impacts.

• Identified asset-specific climate sensitivities and impact thresholds, enhancing risk assessments by 20% for multi-million dollar assets.

RESEARCH ASSISTANT @DEPARTMENT OF COMPUTER SCIENCE, PURDUE SCHOOL OF SCIENCE,IUPUI

Mentor: Prof. Fengguang Song                                                                                                        

Jan 2023 – Present

• Developed a data exchange server using FastAPI to couple distinct computational clients to enable the efficient transfer of large binary data arrays with metadata using HTTP protocol's binary octet stream.

• Implemented communication libraries in Fortran, C, and Python to provide REST API endpoints for our clients E3SM (Energy Exascale Earth System Model) CPL7 located at Perlmutter, DOE, PNNL, and CyberWater at Pittsburg and Indiana University to interact with data exchange server.

• Devised an efficient Flag Management System which can handle multiple variable data transmissions simultaneously, avoiding chances of memory leaks and optimizing performance so that the server performs seamlessly.

• Utlized HPC environments, utilizing slurm job scripting, remote access, and Linux/Unix operations to efficiently provide modular and flexible solutions to easily include new open data models into existing couplers or systems.

• [Github Repository]

• Skills Working on: Linux, Unix, Remote Server Handling(SSH), High Performance Computing, Client Management Server, FastAPI, HTTPs, Network Protocol

SUMMER RESEARCH INTERN @UNIVERSITY OF MIAMI

Mentor: Prof. Cheng Bang Chen                                                                                                        

May 2021-Aug 2021

• Conceptualized a novel recurrence analysis methodology for cardiac arrhythmia detection using multi-channel ECG signals.

• Integrated physics-based and machine-learning methodologies to extract the subtle dynamic recurrences from the ECG signals.

• Formulated quantification metrics to describe recurrence patterns in ECG signals, enhancing anomaly detection and classification.

• Achieved 97% sensitivity in evaluating the framework against the MIT BIH database, exceeding current benchmarks.

• Skills Gained: Anomaly Detection, Machine Learning, Statistical Modeling and Data Analysis, Python, R, SQL

• [Presentation | Certificate]

DATA SCIENCE INTERN @HOTEL CLOUD, LONDON TOWN GROUP

Mentor: Mr. Amit Popat                                                                                                                   

May 2020-Jun 2020

• Developed algorithms for predicting the number of booked rooms and dynamic pricing of seven hotels based in London, UK.

• Created a new dynamic pricing model and developed a Flask API, which is currently being used in the backend program for hotel revenue operations.

• Implemented various probabilistic methods proposed by research articles published by Airbnb and worked on the price sensitivity model.

• Skills Gained: Dynamic Pricing Strategy, Probabilistic and Forecasting Models, Price Sensitivity Analysis, API Building, Flask, Python

• [Certificate | Poster]