AI Intern@RTX |Masters Student in AI at Indiana University Bloomington| Ex-AI @Zenskar, SuperKalam(YC W23), AI Planet, The HelloWorld |NIT Warangal|LLM and RAGs|Generative AI|
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Masters Student in Intelligent Systems at Indiana University Bloomington. Looking for potential AI/ML or Software Engineering opportunities
Indiana University Bloomington
Master's degree, Artificial Intelligence(Intelligent Systems)
August 1, 2025 – March 1, 2027
National Institute of Technology Warangal
Bachelor of Technology - BTech, Computer Engineering
December 1, 2021 – April 1, 2025
Allen
Jee, science
January 1, 2019 – January 1, 2021
Zenskar
AI Engineer
January 1, 2025 – March 1, 2025
New York, New York, United States · Remote
SuperKalam (YC W23)
AI Researcher
May 1, 2024 – September 1, 2024
Bengaluru, Karnataka, India · Hybrid
AI Planet
AI Engineer
January 1, 2024 – April 1, 2024
Leuven, Flemish Region, Belgium · Remote
National Institute of Technology Warangal
Research Intern
October 1, 2023 – December 1, 2023
Hybrid
The HelloWorld
Data Science Intern
June 1, 2023 – August 1, 2023
Bengaluru, Karnataka, India · On-site
Social(Formerly Script Foundation)
Open Source Contributor
May 1, 2023 – July 1, 2023
Remote
Technozion, NIT Warangal
Content Writer
October 1, 2022 – December 1, 2022
Blog Generation using LLama
December 1, 2023 – Present
Used the open source Llama-2 model to generate Blogs based on inputs like number of words and category. Interface built using Streamlit
GPT from Scratch
December 1, 2023 – Present
Built a Generatively Pre-trained Transformer and trained it on Shakespearean text(Tiny Shakespeare) to generate the same
Protein Synthesis and Clustering using BioPython
May 1, 2023 – June 1, 2023
-Developed a robust Biopython-based pipeline for comprehensive COVID-19 genome analysis, encompassing transcription and translation processes. This facilitated a profound understanding of the viral genetic structure and functional elements, aiding in pandemic research. -Employed advanced count vectorization techniques for protein sequence classification, unveiling essential biomarkers and functional insights within the viral genome. This approach deepened our understanding of the virus's molecular composition. -Applied K-Means clustering to categorize protein sequences into distinct functional groups, offering insights into the diversity of viral functions. This facilitated the identification of potential therapeutic targets, contributing to COVID-19 research and treatment strategies.
Significant Wave Height Prediction in Oceanography using Machine Learning
March 1, 2023 – April 1, 2023
Developed a machine learning model using models like Catboost, XGboost , Lasso Regression and feature engineering techniques like panda manipulation and information gain to design an ML model with the highest attainable accuracy in order to predict significant wave height using the NDBC dataset. The NDBC dataset contains historical records of oceanographic and meteorological data collected from buoys worldwide. This dataset which includes various parameters such as wind speed, sea surface temperature, and wave period, among others, that can be used to predict significant wave height. Submitted this project as part of The ML for Oceanography hackathon hosted by Oceana: The Ocean Engineering association of IIT Madras and received a final rank of 36.
FieldForesight-Web Interface for a Crop Recommender Model
February 1, 2023 – Present
Developed an ML model to predict the optimal crop to grow in a particular location based on soil composition, rainfall, temperature, and return of investment Created a user-friendly interface for the public to interact with the model and get recommendations based on geolocation, season, and price. Participated in the TRI-NIT Hackathon to develop and showcase the project
Crack Detection in Bridges Using Deep Learning-IITM L&T EduTech Hackathon
January 1, 2023 – January 1, 2023
Used open source datasets to develop a deep learning framework for detecting cracks in bridges. The project leveraged transfer learning to achieve high accuracy in crack detection. The model was evaluated using precision, recall and F1 score as the judging metrics. The end goal was to contribute to the advancement of bridge engineering by facilitating better design, construction, and maintenance through accurate crack detection. Worked on project as part of IIT Madras' L&T EduTech Shaastra Hackathon, and was shortlist in the final 10 from around 600 teams in the 2nd round.
Data Multiclass Engineering and Modeling-Kaggle Knight Hackathon
January 1, 2023 – January 1, 2023
Used Feature engineering techniques such as Information Gain, Principal Component Analysis, Synthetic Minority Oversampling Technique and AI/Machine Learning models such as Gradient Boosting, Support Vector Machines, Artificial Neural Networks on unlabeled datasets of around 800 features as a submission for the Kaggle Knight(Pre-Event) Hackathon hosted by IIT Jodhpur. Ranked 21st amongst 400+ registrations.
Synthesizing Compressional and Shear Travel-Time Logs in Wells using Machine Learning Techniques: Improving Subsurface Characterization
January 1, 2023 – January 1, 2023
Data-Driven Sonic Log Synthesis: Improved Subsurface Characterization through Machine Learning Techniques. Used conventional logs (Caliper, Neutron, Gamma Ray, Deep Resistivity, Medium Resistivity, Photo-electric factor and density) to generate synthetic compressional and shear travel-time logs (DTC and DTS) in under-sampled wells. Obtained low prediction error quantified in terms of Root Mean Squared Error (RMSE). Enhanced geomechanical properties prediction for a complete well-seismic workflow. Worked on this for the Oily MLGO Hackathon hosted by IIT(ISM) Dhanbad.
Certificate of Participation in Havoc | Marketing Case Study of Eximius 2022, IIM Bangalore's Entrepreneurship Summit
Unstop
June 25, 2026 – Present
Anomaly Detection
AIM Research
June 25, 2026 – Present
Autoencoders
AIM Research
June 25, 2026 – Present
Binary Image Classification
AIM Research
June 25, 2026 – Present
Noise Filtering Techniques
AIM Research
June 25, 2026 – Present
Image Processing
AIM Research
June 25, 2026 – Present
Feature Selection Techniques
AIM Research
June 25, 2026 – Present
Principal Component Analysis
AIM Research
June 25, 2026 – Present
Intro to Deep Learning
Kaggle
June 25, 2026 – Present
Data Visualization
Kaggle
June 25, 2026 – Present
Basic Image Classification with TensorFlow
Coursera
June 25, 2026 – Present
Intro to Programming
Kaggle
June 25, 2026 – Present
Linear Algebra for Machine Learning and Data Science
Coursera
June 25, 2026 – Present
Outlier Treatment
AIM Research
June 25, 2026 – Present
2nd Place, "Fair of Proposal" Case Study
SCIT - Symbiosis Centre For Information Technology
June 25, 2026 – Present
Machine Learning Explainability
Kaggle
June 25, 2026 – Present
Multi-Class Text Classification
AIM Research
June 25, 2026 – Present
Multiclass Image Classification
AIM Research
June 25, 2026 – Present
Lasso, Ridge and Elastic Net Regression - The Regularization Techniques
AIM Research
June 25, 2026 – Present
Computer Vision
Kaggle
June 25, 2026 – Present
SVM for Classification
AIM Research
June 25, 2026 – Present
Machine Learning Specialization
Coursera
June 25, 2026 – Present
Unsupervised Learning, Recommenders, Reinforcement Learning
Coursera
June 25, 2026 – Present
Intro to Machine Learning
Kaggle
June 25, 2026 – Present
Supervised Machine Learning: Regression and Classification
Coursera
June 25, 2026 – Present
Binary Text Classification
AIM Research
June 25, 2026 – Present
Time Series
Kaggle
June 25, 2026 – Present
Transfer Learning
AIM Research
June 25, 2026 – Present
Convolutional Neural Network
AIM Research
June 25, 2026 – Present
CatBoost
AIM Research
June 25, 2026 – Present
Machine Learning for Kyphosis Disease Classification
Coursera
June 25, 2026 – Present
Support Vector Machine for Regression
AIM Research
June 25, 2026 – Present
Intermediate Machine Learning
Kaggle
June 25, 2026 – Present
Neural Networks and Deep Learning
Coursera
June 25, 2026 – Present
Intro to AI Ethics
Kaggle
June 25, 2026 – Present
Pandas
Kaggle
June 25, 2026 – Present
Certificate of Participation in The Tri-NIT Hackathon
Unstop
June 25, 2026 – Present
Postman Student Expert
Postman
June 25, 2026 – Present
Text Preprocessing and Analytics
AIM Research
June 25, 2026 – Present
Image Reconstruction
AIM Research
June 25, 2026 – Present
K-NN for Regression
AIM Research
June 25, 2026 – Present
Intro to SQL
Kaggle
June 25, 2026 – Present
Feature Engineering
Kaggle
June 25, 2026 – Present
Data Cleaning
Kaggle
June 25, 2026 – Present
AI-Powered Chest Disease Detection and Classification
Coursera
June 25, 2026 – Present
Python
Kaggle
June 25, 2026 – Present
Advanced Learning Algorithms
Coursera
June 25, 2026 – Present
SSOC Season 2
Social(Formerly Script Foundation)
June 25, 2026 – Present
Certificate of Participation in Startupbia | Analytics Case Competition of Eximius 2022, IIM Bangalore's Entrepreneurship Summit
Unstop
June 25, 2026 – Present
Cultural Fit Analysis
The candidate shows a strong inclination towards continuous learning and practical application, evidenced by numerous certifications and hackathon participations. Their diverse project portfolio, ranging from bio-informatics to oceanography and finance, indicates adaptability and a broad interest in applying AI across different domains. The open-source contributions also suggest a collaborative mindset. However, the focus is heavily on individual projects and internships, with less emphasis on team-based achievements outside of hackathons, which might require further probing for cultural fit in a highly collaborative environment.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a proactive and problem-solving approach, often participating in hackathons and open-source contributions. Their experience in prompt engineering and RAG suggests an ability to adapt to new technologies and contribute to cutting-edge AI development. The detailed project descriptions also imply good communication skills in conveying technical work.