CV
Contact Information
| Name | Rathin Chandra Shit |
| Professional Title | Founder & Principal Researcher, NavSense Lab |
| 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
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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.
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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.
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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.
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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
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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.
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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
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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.
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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
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2006 - 2010 Odisha, India
B.Tech
Biju Patnaik University of Technology (BPUT), Rourkela, India
Electronics & Telecommunication Engineering
- Wireless Missing Person Detection
Awards
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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.
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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.
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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
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2021 AI-Enabled Fingerprinting and Crowdsource-Based Vehicle Localization for Resilient and Safe Transportation Systems
IEEE Transactions on Intelligent Transportation Systems
Proposed a novel AI-driven fingerprinting and crowdsourcing architecture to improve the accuracy and resilience of vehicle localization in intelligent transportation systems.
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2019 Ubiquitous Localization (UbiLoc): A Survey and Taxonomy on Device Free Localization for Smart World
IEEE Communications Surveys & Tutorials
Authored a comprehensive taxonomy on device-free localization technologies, establishing foundational frameworks for smart city and ubiquitous computing environments.
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2018 Location of Things (LoT): A Review and Taxonomy of Sensors Localization in IoT Infrastructure
IEEE Communications Surveys & Tutorials
Conducted an extensive architectural review of sensor localization techniques, mapping the technological landscape and requirements for scalable IoT deployments.
Skills
Languages
Interests
Projects
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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.