About Me

I am Udit Deo, a Computer Science researcher and technologist with a strong foundation in deep learning, computer vision, and fuzzy optimization. Currently pursuing a Ph.D. in Computer Science and Engineering at the Indian Institute of Technology Roorkee, I hold an M.Tech in Software Engineering from MANIT Bhopal (GPA: 9.53) and a B.Tech in Computer Science and Engineering. My research explores the intersection of machine learning, soft computing, and decision systems, with recent contributions published in IEEE and Springer-indexed international conferences. I am a UGC-NET JRF awardee and a dual GATE qualifier (CS & DA), demonstrating a sustained commitment to academic excellence. Professionally, I bring two years of industry experience at Amdocs, where I developed automation tools and optimized software systems across billing platforms. I have also held research roles at ZHCET, AMU and Stackfusion, fine-tuning deep learning models for real-world applications. I am the co-inventor of a granted design patent for a novel energy device, and I remain driven by interdisciplinary innovation, rigorous inquiry, and impactful technology development.

Education

  • PhD in Compurter Science and Engineering, IIT Roorkee (2025–Present)
  • M.Tech in Software Engineering, MANIT Bhopal (2023–2025) — CGPA: 9.53
  • B.Tech in Computer Science and Engineering, SMVDU[GFTI] (2017–2021) — CGPA: 8.21

Industry Experience

  • Associate Software Engineer — Amdocs, Gurugram (Jul 2021 – Jun 2023)
    • Developed tools in C/C++ and Python for billing modules (BFENV, ODI, Splitter, Archive) in Unix environments.
    • Built a Python-based backward compatibility checker — reduced manual QA effort by 90%.
    • Created a database comparator and merger utility; designed a Flask-based regression testing system.
    • Recognized for innovation, code quality, and process optimization.
  • Machine Learning Intern — Stackfusion, Gurugram (May 2020 – Jul 2020)
    • Fine-tuned deep learning models (YOLOv3, ResNet, MobileNetSSD) for vehicle axle/license plate detection.
    • Automated data preprocessing with Python — improved label quality and dataset diversity.

Research Interests

  • Fuzzy Optimization & Relation Inequalities
  • Multi-Criteria Decision Systems
  • Computer Vision & Deep Learning
  • Interpretable AI & Soft Computing

Exams Qualified

  • UGC-NET (CS) – JRF (99.95%ile, Dec 2024) and Assistant Professor (June 2024)
  • GATE (CS, 2022 & 2025) | GATE (DA, 2025)

MTech Thesis

Title: Bridging Fuzziness and Optimization: Frameworks for Relation Inequalities and Multi-Criteria Decision Systems
Status: Successfully defended on 30 June 2025
Advisors: Prof. MMS Beg (ZHCET, AMU) and Dr. JK Jain (MANIT Bhopal)