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M.Tech Completed • CGPA 8.14 [cite: 1]

Debendra Kumar Pal

CS24M016 | Indian Institute of Technology Madras [cite: 1]

debendrakumar12345@gmail.com [cite: 1] | 9875492593 [cite: 1]

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Senior Software Engineer @ SSIR

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Experience & Education

Senior Software Engineer

Samsung Semiconductor India Research (SSIR) | Upcoming

M.Tech, Computer Science and Engineering [cite: 1]

Indian Institute of Technology Madras | 2026 [cite: 1]

Completed successfully with 8.14 CGPA. [cite: 1]

Advance S/W Engineer Intern [cite: 1]

Accenture | May-July 2025 [cite: 1]

  • In 2 weeks of training I learned GenAI, Al, Prompt engineering, Cyber Security, Robertic Process Automation (RPA), and AgenticAl. [cite: 1]
  • Developed Agentic Al model with four agents: Intent analysis, Sentiment Analysis, Content Generation and customer support for Marketing based company during a 8-week internship. [cite: 1]
  • Designed and implemented the Intent Analysis module with orchestration of models using LangGraph that demonstrated an understanding of design specifications and client requirements. [cite: 1]
  • Integrated with LangChain, OpenAI API, RAG pipeline, and Hugging Face models, chromaDB for robust NLP workflows, StrewamLitUI. [cite: 1]

'Quantum Hybrid Cloud' Researcher [cite: 1]

IISc (DREAM Lab) | June-Dec 2024 [cite: 1]

  • Worked in DREAM Lab under Prof. Yogesh Simmhan, on project "Quantum Hybrid Cloud" inaugurated with IBM Research. [cite: 1]
  • I learned Qiskit for quantum workloads. [cite: 1]

B.Tech, Computer Science and Engineering [cite: 1]

DIATM, W.B. | 8.85 CGPA | 2023 [cite: 1]

Machine Learning Internship [cite: 1]

Acmegrade | Feb-Mar 2023 [cite: 1]

  • Designed and developed a Sentiment Analysis on social media during a 5-week internship. [cite: 1]
  • Used Naïve Bayes, KNN as the basic ML model. [cite: 1]

Schooling [cite: 1]

Class XII (ISC): Shatavisha Public School (75%, 2019) [cite: 1]

Class X (ICSE): Xavier's English School (84.6%, 2017) [cite: 1]

Finder - Portfolio_Data

Research & Major Projects


MTech Project - 'Brain Atlas Analysis using Artificial Intelligence' [cite: 1]

Prof: Manikandan Narayan | Jul 25-Present [cite: 1]

  • Developing an Al model using Sudha Gopalakrishnan Brain Centre (IIT Madras) dataset to analyze age-wise brain evolution through imaging data. [cite: 1]
  • Phase 1 of this project is to make an Model that can annotate the brain atlas, specially hippocampus formation. [cite: 1]
  • Designing a deep learning pipeline to predict structural/functional brain changes between input age x and output age y. [cite: 1]
  • Extract and track key neuroanatomical and functional parameters driving age-related variations. [cite: 1]
  • Investigate causal factors behind observed parameter changes using statistical and ML-based interpretation methods. [cite: 1]
  • Contribute towards mapping unexplored regions and structural patterns in brain atlas for advancing computational neuroscience research. [cite: 1]

BTech Project- 'A Deep Learning Approach: A Facial Recognition System on Real-Time Dataset' [cite: 1]

Jan-Aug 2023 [cite: 1]

  • Built a real-time facial recognition system using deep learning on a dataset collected from DIATM college students. [cite: 1]
  • Implemented and compared KNN and CNN models for facial identification tasks. [cite: 1]
  • Trained and optimized CNN model, saved as .h5 file for deployment. [cite: 1]
  • Integrated model with live video stream to perform face recognition in real-time [cite: 1]

Course Projects


GPU Programming (CS6023) [cite: 1]

Professor: Rupesh Nasre [cite: 1]

  • Developed parallel convolution algorithms for matrices, by leveraging memory coalescing and shared memory in CUDA. [cite: 1]
  • Designed and implemented a cost-effective network pathway using a parallel version of Boruvka's algorithm in C++ and CUDA. [cite: 1]
  • Created an evacuation simulation for a group of cities, utilizing concepts like synchronization and thrusts. [cite: 1]

Introduction to Deep Learning (DA6401) [cite: 1]

Professor: Mitesh Khapra [cite: 1]

  • Modeled Feed Forward Neural Network from scratch and reached 97% test accuracy on the MNIST dataset. [cite: 1]
  • Designed a Convolutional Neural Network(CNN) model and trained it to get 42% accuracy on the iNaturalist dataset. [cite: 1]
  • Implemented a Se2Se architecture using Recurrent Neural Networks (RNNs), LSTM, GRU, to perform English to Hindi transliteration. [cite: 1]

Natural Language Processing (CS6370) [cite: 1]

Professor: Sutanu Chakraborti [cite: 1]

  • Built an Information Retrieval system using the Vector Space Model, and applied it to the Cranfield dataset. [cite: 1]
  • Implemented text processing techniques like sentence segmentation, tokenization, stemming/lemmatization, and stopword removal. [cite: 1]
  • Engineered a spell-checking component and integrated features of WordNet to enhance text analysis. [cite: 1]

Pattern Recognition and Machine Learning (CS5691) [cite: 1]

Professor: C. Chandra Sekhar [cite: 1]

  • Implemented a regularized linear regression model with polynomial basis functions, analyzing its performance. [cite: 1]
  • Developed and evaluated various classification models, including K-nearest neighbors, Bayes, and Naive-Bayes classifiers. [cite: 1]
  • Engineered Multi-Layer Feedforward Neural Networks (MLFFNNs) for function approximation and classification. [cite: 1]
  • Implemented Support Vector Machines (SVMs) with different kernels, along with a GMM-based classifier. [cite: 1]
  • Applied Principal Component Analysis (PCA) to reduce data dimensionality for enhanced model performance. [cite: 1]

Principles of Distributed Software (E0209) [cite: 1]

Professor: K.V. Raghavan (IISC) [cite: 1]

  • Designed and developed a microservice-based Movie Booking System using Spring Boot. [cite: 1]
  • Containerized services with Docker and deployed on Kubernetes for scalability and fault tolerance. [cite: 1]
  • Implemented actor-based concurrency and distributed coordination using Akka. [cite: 1]
  • Applied distributed systems principles (service discovery, load balancing, fault recovery) for high availability. [cite: 1]

Interactive Course Directory

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M.Tech Courses [cite: 1]
B.Tech Courses [cite: 1]
Online & Electives [cite: 1]

Technical Skills Stack


Languages [cite: 1]

C C++ Python CUDA Qiskit Html CSS JavaScript SQL Java [cite: 1]

Tools & Libraries [cite: 1]

Python Flask Pandas Numpy Keras LATEX WandB AI GitHub Matplotlib OpenCV Docker Jupyter Notebooks Google Colab LangChain LangGraph Chromadb RAG Blue Prism (RPA) Prompt Engineering StreamLitUI Hugging face Canva [cite: 1]

Scholastic Achievements & Positions


Scholastic Achievement [cite: 1]

  • Secured AIR 23938 (TFW-AIR 6362) in WBJEE 2019 [cite: 1]
  • Secured AIR 1306 in IMU CET June 2019 [cite: 1]
  • Secured AIR 938 in GATE CSE 2023 [cite: 1]
  • Secured AIR 119 in JEE AME 2023 [cite: 1]

Teaching Assistant (June 2024- Present) [cite: 1]

  • Introduction to Programming course (CS1100) under Prof. B.V. Raghavendra Rao (Aug 2024 - Nov 2024). [cite: 1]
  • Object Oriented Algorithm Implementation and Analysis course (CS2810) under Prof. Rupesh Nasre (Jan 2025 - May 2025). [cite: 1]
  • Pattern Recognition and Machine Learning for CS- PG course (CS5691) under Prof. Manikandan Narayan (Aug 2025-Nov 2025) [cite: 1]

Organiser [cite: 1]

  • Volunteered Vivitsu Lab (Prof. Gugan Thoppe, IISc) Reinforcement Learning on IISc Open Day 2024. [cite: 1]
  • Digital Team Organiser in 2025 Symposium on Artificial Intelligence and Pharmaceutical Medicine (AIPM-India) 10-11 Sept'25. [cite: 1]