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Portrait of Sethu Iyer - Data Scientist and AI Researcher

I'm an interdisciplinary AI professional with years of experience building production-grade LLM architectures, search, retrieval systems and end to end product development . Mathematics and Computer Science is my foundation. Conversational AI, Search, and exploring seemingly unrelated yet connected concepts are my playgrounds.

About Me

Education & Background

I have a strong background in mathematics and computer science with a dual degree from BITS Pilani. My interdisciplinary approach allows me to tackle problems from multiple angles, drawing insights from graph theory, topology, functional analysis, and computational methods.

Research Focus

My research focuses on developing novel interpretability metrics for LLMs to enhance transparency in decision-making.

Current Focus

Active Research Areas

All research areas align towards building scalable, interpretable, and production-grade LLM systems.

Work Experience

Senior AI Research Engineer -

Workato (Bengaluru, India)

Deep Learning Researcher & Data Scientist -

Jio Platforms Ltd (Hyderabad, India)

Research and Development Engineer -

Amelia / IPSoft (Bengaluru, India)

Research Intern -

Video Analytics Lab, IISc Bengaluru

Student Researcher -

BITS Pilani Goa Campus

Game Theory in Machine Learning (Jul 2017 - Dec 2017)

Research under Dr. Jajati Keshari Sahoo exploring novel applications of game theory in ensemble learning:

  • Developed Banzhaf Power Index-based feature selection for ensemble methods
  • Implemented Borda count voting mechanism for classifier aggregation
  • Created Banzhaf Random Forests with strategic classifier selection
  • Published research on game theoretic approaches in ensemble learning
View Game Theory Research on GitHub

Image-to-Image Search Engine (Jan 2018 - Jul 2018)

Research under Dr. Tirtharaj Dash developing a novel reverse image search system:

  • Built a visual image search system using image captioning, ElasticSearch, and TensorFlow
  • Implemented LSTM-based caption generation for semantic image understanding
  • Published research paper in SocPros 2017 on captioning-based search engine
  • Created RESTful APIs for image caption generation and search functionality
View Image Search Project on GitHub

Education

Birla Institute of Technology and Science, Pilani -

Dual Degree: M.Sc Mathematics & B.E Computer Science

GPA: 7.47/10 (Equivalent to 3.7/4.0 US Scale)

Relevant Courses: Functional Analysis, Data Structures and Algorithms, Advanced Probability and Statistics, Graph Theory, Topology, Operations Research, Machine Learning, Quantum Computing

Certifications

Publications

Image captioning-based image search engine: An alternative to retrieval by metadata

S. Iyer, S. Chaturvedi, T. Dash - Soft Computing for Problem Solving: SocProS 2017, Volume 2, 181-191

View on Google Scholar

Featured Projects

DeydooGPT

AI Assistant built on fine-tuned Mistral 7B with 8000-token context handling for enhanced understanding of complex conversations.

LLM Fine-tuning Python
View DeydooGPT on GitHub

Clinical Diagnosis Engine

Medical diagnosis system using Graph RAG techniques, achieving 85.83% production accuracy for clinical applications.

Graph RAG Healthcare AI Python
Proprietary Project

Scalable BERT Inference Pipeline

High-performance inference system that reduced latency by 50% using ZeroMQ & NGINX for efficient handling of NLP requests.

Optimization NLP Python
View on GitHub

EazyML

Core technical member for this explainable AutoML platform for tabular data that automates model selection, hyperparameter tuning, and provides interpretable results.

AutoML Explainable AI Python
Proprietary Project

Keyflix

Educational platform with video content and intelligent recommendation system to personalize learning experiences.

Education Recommendations JavaScript
View on GitHub

Newsboat Recommender

RSS feed recommender using hybrid approach combining lexical and BERT-based content analysis for personalized news delivery.

NLP Recommendations Python
View on GitHub

FDE-Solver

MATLAB solver for Fractional Differential Equations with applications in mathematical modeling and simulations.

Mathematics Numerical Methods MATLAB
View on GitHub

YouTube Video Assistant

A production-ready Python tool that enables natural conversations with YouTube videos using ASR, NLP, and LLMs. Features include automatic transcription, context-aware responses, and efficient caching.

ASR NLP LLM Python
View on Codeberg

YACR - Ultimate IT Roadmap

A comprehensive 9-10 month roadmap transforming beginners into job-ready IT professionals. Features structured learning paths, hands-on projects, and industry-aligned curriculum covering CS fundamentals to advanced AI.

Education Roadmap Career Development Open Source
View on Codeberg

DeydooRAG

A production-grade RAG pipeline using txtai for semantic search and LLM orchestration. Features include dynamic index management, query classification, and lightning-fast retrievals (3s search, <2s retrieval). Includes real-world examples with multilingual support.

RAG Semantic Search LLM Python
View on Codeberg

Simple Chatbot

A chatbot application built using Python and AIML (Artificial Intelligence Markup Language) for natural language processing and pattern matching.

Python AIML NLP
View Simple Chatbot on GitHub

Game of Thrones Visualization

Interactive visualization of the Game of Thrones dataset using t-SNE dimensionality reduction, featured in a YouTube video for its innovative approach to data visualization.

Python t-SNE Data Visualization Kaggle
View Game of Thrones Visualization on GitHub

DAPS (Dynamic Adaptive Prime Sampling)

A novel optimization algorithm that uses prime number-based grid sampling to avoid aliasing problems common in regular grid search methods. Features dynamic resolution adaptation and domain shrinking around promising regions, with primes serving as resolution knobs for accuracy control.

Mathematics Optimization Python Grid Search
View on GitHub

QuHabiton

A creative experimental habit tracker leveraging quantum physics, topology, and data analysis principles. Features include probabilistic habit representation, quantum machine learning for pattern analysis, behavioral topography visualization, and adaptive learning based on habit topology.

Quantum Computing Habit Tracking Topology Python
View on GitHub

List Coloring via Grover's Algorithm

Implementation of list coloring problem using Grover's algorithm through SAT formulation, developed during IIT Delhi's Quantum Machine Learning course. Demonstrates quantum computing applications in graph theory and constraint satisfaction problems.

Quantum Computing Graph Theory SAT Python
View on GitHub

LLM Episodic Memory System (Experimental)

A cognitive architecture for LLMs featuring surprise-driven memory formation, Legendre polynomial-based orthogonal paragraph embeddings, and dynamic memory refinement. Implements temporal decay, access boosts, and contradiction detection for biologically-inspired memory management.

LLM Memory Systems Cognitive Architecture Python
View on GitHub

Skills & Expertise

AI/ML & LLMs

  • Hugging Face Transformers
  • PEFT (LoRA, QLoRA)
  • Retrieval-Augmented Generation (RAG)
  • Prompt Engineering
  • Fine-tuning LLMs
  • Computer Vision

Programming & Development

  • Python (Advanced)
  • C/C++, Go, Scala
  • SQL, CUDA, MATLAB
  • Flask, Docker
  • Svelte, Quasar Framework
  • CI/CD, Linux

ML Frameworks & Tools

  • TensorFlow, PyTorch
  • Scikit-learn, SpaCy
  • OpenCV, XGBoost, CatBoost
  • ONNX Runtime
  • Mixed Precision Training
  • TPU Utilization

Big Data & Databases

  • Apache Spark
  • Elasticsearch
  • Redis
  • MongoDB
  • PostgreSQL

Publications & Research

Image captioning-based image search engine: An alternative to retrieval by metadata

A research paper introducing an innovative approach to image search using captioning techniques instead of traditional metadata, published in SocProS 2017.

Authors: S. Iyer, S. Chaturvedi, T. Dash

Publication: Soft Computing for Problem Solving: SocProS 2017, Volume 2, 181-191

View on Google Scholar

LLM Interpretability Metrics

Ongoing research in developing novel interpretability metrics for large language models to enhance transparency in decision-making and improve model trustworthiness.

Status: In progress

Episodic Memory Mechanisms in LLMs

Research exploring innovative approaches to enhance long-text coherence in large language models through the integration of episodic memory mechanisms.

Status: In progress

Get in Touch

Email: sethuiyer95@gmail.com