About
Highly accomplished B.Tech. Electrical Engineering student with a robust foundation in Artificial Intelligence and Machine Learning, seeking to leverage advanced research and development expertise in AI/ML engineering or data science roles. Proven ability to design, implement, and optimize complex ML pipelines, demonstrated through achieving 93-95% accuracy in fault diagnosis systems and 92% efficiency in RAG pipelines. Recognized with multiple awards for outstanding research and innovation, including a Best Research Paper Award from IEEE ICCCIT.
Work
Virtual Labs, IIT Roorkee
|Research Intern
Uttrakhand, Uttarakhand, India
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Summary
As a Research Intern, Tanmay spearheaded the development of an ML-driven transformer fault diagnosis system, achieving high accuracy and efficient data processing.
Highlights
Spearheaded development of an ML-driven transformer fault diagnosis system, achieving 93-95% accuracy and processing 100+ mat files with a customizable preprocessing pipeline.
Formulated a feature extraction framework, computing 5+ features (e.g., Kurtosis, median, impulse factor) on customized datasets, processing up to 1.2 million samples.
Orchestrated FFT and wavelet transform visualizations for 5 wavelet types, enabling real-time adjustments via Streamlit.
Devised a Supervised Contrastive Learning pipeline for feature extraction and SVM classifiers, supporting 5 activation functions across 1000+ epochs.
IIT (ISM) Dhanbad
|Research Intern
Jharkhand, Jharkhand, India
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Summary
As a Research Intern, Tanmay contributed to the creation of an Advanced Retrieval-Augmented Generation (RAG) pipeline, significantly boosting query efficiency and data extraction success rates.
Highlights
Contributed to an Advanced Retrieval-Augmented Generation (RAG) pipeline, attaining 92% efficiency across 500+ queries while enhancing document processing capabilities.
Executed over 500 alpha-phase test cases to validate robustness, preparing for beta testing of 1,500+ queries.
Integrated PaddleOCR, realizing an 85% success rate in data extraction for the RAG pipeline.
Co-authored a research paper detailing methodologies and performance enhancements of the RAG pipeline project.
SVNIT Surat
|Research Intern
Surat, Gujarat, India
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Summary
As a Research Intern, Tanmay evaluated machine learning models to detect Non-Performing Loans (NPLs), identifying the most effective classifier and publishing findings.
Highlights
Evaluated machine learning models to detect Non-Performing Loans (NPLs), identifying the Random Forest Classifier with the highest success rate on a dataset of over 250,000 users.
Benchmarked 7 classifiers to enhance credit risk assessment frameworks and improve predictive accuracy.
Authored and published a paper, "Comparative Performance Analysis of Machine Learning Algorithms for Non-Performing Loan Prediction," accepted at IEEE ICCCIT conference.
Awarded the Best Research Paper Award at IEEE ICCCIT conference for outstanding contributions.
Education
National Institute of Technology, Surat
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B.Tech.
Electrical Engineering
Grade: 7.9 CGPA
Courses
Data Structure
Algorithms
DBMS
Machine Learning
Artificial Intelligence
Operating System
CBSE Board
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High School Diploma
Secondary Education
Grade: 93.2%
ICSE Board
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High School Diploma
Secondary Education
Grade: 94.2%
Awards
Best Research Award
Awarded By
IEEE ICCCIT
Honored with the award for outstanding research contribution at IEEE ICCCIT.
Best Innovation Award
Awarded By
Research & Innovation Conclave (RIC)
Recognized for exemplary innovation at the Research & Innovation Conclave (RIC).
Finalist: NTIRE Shadow Removal Track
Awarded By
NTIRE Challenge
Secured a global rank of 14th in the Shadow Removal Track at the NTIRE Challenge.
Finalist: DOTSLASH 8.0
Awarded By
DOTSLASH
Earned a national rank of 4th at DOTSLASH 8.0.
Certificates
Internship Completion: Virtual Labs, IIT Roorkee
Issued By
Virtual Labs, IIT Roorkee
Internship Completion: IIT (ISM) Dhanbad
Issued By
IIT (ISM) Dhanbad
Internship Completion: SVNIT Surat
Issued By
SVNIT Surat
Skills
Programming Languages
Python, C, C++, SQL, PL.
Libraries & Tools
TensorFlow, Scikit-learn, Pandas, Transformers, Langchain, PaddleOCR, Pinecone, Streamlit.
Databases & Software
MySQL, Oracle, PostgreSQL, IBM SPSS, Tableau, Excel, Matlab.
AI/ML Concepts
Machine Learning, Artificial Intelligence, Deep Learning, Natural Language Processing (NLP), Computer Vision, Predictive Analytics, Feature Engineering, Model Evaluation, Supervised Contrastive Learning, Retrieval-Augmented Generation (RAG).
Technical Methodologies
Data Structures, Algorithms, DBMS, Operating System, FFT, Wavelet Transform, Hybrid ConvNext-U-Net.
Research & Development
Research, Problem Solving, Data Analysis, Scientific Writing, Experimentation, Prototyping.