CV

Contact Information

Name Rathin Chandra Shit
Professional Title Founder & Principal Researcher, NavSense Lab
Email rathin@navsenselab.org
Location Bhubaneswar, Odisha, India

Professional Summary

Computer Scientist with a Ph.D. in CSE, specializing in Artificial Intelligence, Machine Learning, and IoT infrastructure. Experienced in developing scalable multi-agent systems, deep learning frameworks, and network localization solutions for next-generation applications.

Experience

  • 2020 - Present

    Remote

    AI/ML R&D Engineer
    R&D Consultant
    Translating deep academic research into scalable, industry-ready software applications and automated pipelines.
    • Architecting automated research workflow and tracking system.
    • Engineering multi-agent systems and experimenting with local LLMs (Ollama) to build autonomous, agentic workflows.
    • Managing and optimizing efficient machine learning model deployment across multiple hardware architectures.
  • 2016 - 2021

    Bhubaneswar, India

    IoT/AI Researcher
    PhD Research Scholar, IIIT Bhubaneswar
    Led extensive research initiatives focusing on the intersection of AI and network infrastructures.
    • Authored comprehensive survey papers mapping the taxonomy of sensor localization in IoT.
    • Collaborated with international researchers to design and architect protocols and infrastructure for applied AI in IoT infrastructure.
  • 2014 - 2016

    DRDO, India

    Senior Researcher / Engineer (SRF)
    Defence Research and Development Organisation (DRDO), Govt. of India
    Led advanced R&D initiatives in radar systems, focusing on data processing software development and RF hardware simulation.
    • Developed and optimized Data Processing System Software for Precision Coherent Mono-pulse C-Band (PCMC) Radar systems.
    • Designed, simulated, and analyzed the performance of Low Noise Amplifiers (LNA) and waveguides for high-survival radar receivers.
    • Conducted deep technical analysis of radar receiver front-end data to improve system accuracy and signal reliability.
  • 2012 - 2014

    DRDO, India

    Junior Researcher / Engineer (JRF)
    Defence Research and Development Organisation (DRDO), Govt. of India
    Contributed to the core software architecture and data analysis pipelines for critical defense tracking systems.
    • Engineered specialized software modules for the Angle Tracking Sub-System (ATSS) to enhance target tracking capabilities.
    • Analyzed and validated complex C-band PCMC Radar receiver data to ensure system performance and signal integrity.

Leadership & Peer Review

  • 2014 - Present

    Remote

    Technical Program Committee (TPC) & Expert Reviewer
    IEEE, Elsevier, Springer, ACM, IET
    Active leader and contributor to the global computer science research community, providing strategic direction for top-tier journals and conferences.
    • Served on Technical Program Committees (TPC) for international conferences, guiding technical agendas and curating high-impact research in AI, IoT, and network localization.
    • Conducted over 80 rigorous technical peer reviews in the current year alone, evaluating 40+ journal submissions and 40+ conference papers.
    • Engineered ‘ReviewerOS,’ a custom automated workflow application leveraging Google Apps Script, to efficiently track, synthesize, and manage this high-volume peer review pipeline.
  • 2024 - 2024

    Remote

    Expert Grant Evaluator (Engineering & Advanced Technology)
    Israel Ministry of Innovation, Science and Technology
    Invited by the national ministry to evaluate high-stakes R&D grant proposals within the Artificial Intelligence sector.
    • Assessed the technical viability, architectural soundness, and innovation potential of proposed AI applications for image localization.
    • Provided critical technical audits and funding recommendations to guide government investment in advanced technology research.

Education

  • 2016 - 2021

    Bhubaneswar, India

    Ph.D.
    IIIT Bhubaneswar
    Computer Science and Engineering
    • Artificial Intelligence, Internet of Things, Sensor/Object Localization
    • Published highly-cited research on IoT infrastructure, localization, and autonomous vehicle safety in top-tier IEEE journals.
    • Conducted advanced research utilizing machine learning and deep learning architectures.
  • 2014 - 2016

    Odisha, India

    M.Tech
    Veer Surendra Sai University of Technology (VSSUT), Odisha
    Information and Communication Technology
    • Effectiveness of Anchor Positioning in Localization of Wireless Sensor Network
  • 2006 - 2010

    Odisha, India

    B.Tech
    Biju Patnaik University of Technology (BPUT), Rourkela, India
    Electronics & Telecommunication Engineering
    • Wireless Missing Person Detection

Awards

  • 2014
    Senior Research Fellowship (SRF)
    Defence Research and Development Organisation (DRDO), Govt. of India

    Prestigious national fellowship awarded to fund advanced R&D initiatives in radar systems and data processing software.

  • 2012
    Junior Research Fellowship (JRF)
    Defence Research and Development Organisation (DRDO), Govt. of India

    Government-funded research fellowship awarded for the engineering and analysis of critical defense tracking systems.

  • 2013
    GATE Qualification: Electronics and Communication
    Graduate Aptitude Test in Engineering (GATE)

    Successfully qualified in both 2010 and 2013, demonstrating top-percentile proficiency in foundational engineering, advanced mathematics, and electronics.

Publications

Skills

AI & Machine Learning (Advanced): Deep Learning, LLMs (Local & Cloud), RAG, LangChain, Prompt Engineering, MLOps, Multi-Agent Systems, Computer Vision
Programming & Data (Advanced): Python, SQL, Bash/Shell, C++, Google Apps Script
Systems, CI/CD & Infrastructure (Advanced): Docker, FastAPI, Airflow, CI/CD pipelines, Redis, Git, Linux, IoT Architecture

Languages

English : Professional Working Proficiency
Hindi : Native / Bilingual
Odia : Native / Bilingual
Bengali : Native / Bilingual

Interests

Productivity & Workflow Optimization: System Automation, Custom OS Environments, Task Management
Autonomous Systems: Agentic Workflows, Edge AI, MLOps

Projects

  • Multi-Agent Edge LLM Workflows

    Developing and experimenting with local LLMs and multi-agent systems to build secure, offline AI capabilities.

    • Architected local containerized deployments using Docker, FastAPI, and Redis caching.
    • Designing agentic workflows to automate complex R&D tasks without relying on cloud dependencies.

References

  • Available upon request

    Professional references from industry and academic collaborations can be provided.