# Cyril Jacob

> Software Engineer · Distributed Systems, Cloud & AI/ML

- Location: New Delhi, India
- Status: Open to software engineering and research opportunities
- Email: itscyriljacob@gmail.com
- GitHub: https://github.com/cj445
- LinkedIn: https://www.linkedin.com/in/thecyriljacob/
- Medium: https://medium.com/@thecyriljacob
- Resume (PDF): https://cj445.github.io/Cyril_Jacob_Resume.pdf
- Site: https://cj445.github.io/

## Summary

I build AI systems that go beyond models, focusing on deployment, infrastructure and real-world impact. CSE (AI & ML) student at Karunya Institute of Technology & Sciences, graduating in 2027, with backend, cloud, DevOps and computer vision experience.

At Graceful Management Systems I automated server provisioning and built CI/CD and containerized deployments on Azure. At Karunya Innovation and Design Studio I optimized computer vision models for NVIDIA hardware with TensorRT.

Outside of work I compete in ISRO hackathons on satellite image super-resolution, and I am always keen to connect with people building scalable products or doing impactful AI research.

Beyond code, I teach and organize. I have run workshops on Python, data science and Jetson edge AI at Karunya Innovation and Design Studio, and I led GDSC Karunya as Lead for 2024 to 2025.

## Featured work

### Dual Image Super-Resolution for Satellite Imagery

*ISRO Bharatiya Antariksh Hackathon 2025 · 4th nationally*

Fuses two low-resolution captures of the same scene into one 512×512 high-resolution image, and scores the result with a blind image-quality model. Built as Team HumbleOps for Problem Statement 12, among 61,000+ students across 8,744 teams.

- **41.45 dB**: PSNR on the official ISRO test set
- **0.97**: SSIM, above the 0.96 HighRes-Net baseline
- **33**: epochs, against 84 for our HighRes-Net track

- Two tracks were compared: a HighRes-Net tuned with 50 Optuna trials (40.5 dB, 0.96 SSIM) and an enhanced dual SwinIR (41.45 dB, 0.97 SSIM) trained with a composite MSE, SSIM, edge-gradient and perceptual loss.
- The SwinIR track matched state-of-the-art PSNR in a third of the epochs, and the composite loss is what lifted SSIM.
- A ViT + ResNet-50 blind quality regressor was trained on 17,344 image pairs across 1,084 scenes, because PSNR and SSIM alone can reward soft, blurry output.

Tech: PyTorch, SwinIR, HighRes-Net, Optuna, ViT, ResNet-50, GeoTIFF
Case study: https://cj445.github.io/reports/satellite-sr/

### Optical-Guided Thermal Super-Resolution

*Smart India Hackathon 2025 · ISRO track · Grand Finale top 5*

A self-supervised framework that upscales thermal satellite imagery 2× to 4× without any high-resolution ground truth. A gated fusion network borrows sharp structure from the optical bands, while a Planck-law radiance constraint stops it from inventing detail.

- **48.61 dB**: PSNR
- **0.9945**: SSIM
- **0.26 K**: RMSE

Note: Metrics are for the single scene shown (2× upscale), not an average over the test set.

- Trained with MTF-based synthetic degradation and residual reconstruction, so no high-resolution thermal reference is needed.
- The Planck/radiance-domain constraint limits optical texture leaking into the thermal output. Evaluated on SSIM, PSNR and RMSE in kelvin.
- Quantized and deployed on an NVIDIA Jetson. The accompanying paper is accepted at IEEE ICECA 2026.

Tech: PyTorch, ResUNet, FiLM fusion, RasterIO, Landsat 8, NVIDIA Jetson

#### Benchmark: ISRO dual-image super-resolution

| Model | PSNR (dB) | SSIM | Note |
| --- | --- | --- | --- |
| CrossSensor SISR | 12.30 | 0.45 | Failed on domain mismatch |
| TR-MISR | 32.00 | 0.40 | Poor SSIM on this data |
| MAT-light ×2 | 33.50 | 0.91 | Accuracy limited |
| SPOT6 interpolated SISR | 35.39 | 0.88 | Single-image baseline |
| ESC-MISR | 39.00 | 0.84 | Strong multi-image model |
| HighRes-Net (original) | 41.50 | 0.96 | State-of-the-art baseline |
| **Enhanced dual SwinIR** | 41.45 | 0.97 | Our submission |

## Experience

### Software Engineering Intern, Graceful Management Systems

Jan 2025 – Dec 2025 · Remote

- Automated Ubuntu server provisioning with Netplan and shell scripting, cutting deployment time by 70%.
- Built delivery workflows in Azure DevOps: Azure Repos, self-hosted Ubuntu agents, automated testing, CI/CD pipelines, and containerized deployments through Azure Container Registry.
- Deployed containerized microservices to Azure and designed the database schemas and data preparation pipelines for a RAG application.
- Managed Ubuntu servers, VMs, permissions, secure SSH access, and dual-interface static IP routing across multi-server networks.

### Industrial Training Trainee, Intel Unnati Program, Intel Corporation

Feb 2025 – Apr 2025 · Team project: visual search with VLMs

- Built a visual search engine on vision-language models: images and text are embedded into one shared space, so a text query or a sample image retrieves the right pictures.
- Implemented scalable indexing and fast similarity search for large datasets, with multi-modal querying from text or image input.
- Evaluated retrieval quality with industry-standard metrics. Team of three, guided by faculty mentors.

### Computer Vision Engineer (Trainee), Karunya Innovation and Design Studio

Jul 2024 – Dec 2025 · Coimbatore, India

- Deployed real-time CCTV analytics with NVIDIA DeepStream SDK, raising streaming throughput 40% (15 to 21 FPS).
- Optimized YOLOv8 and Mask R-CNN with TensorRT INT8 quantization, reducing latency by 60%.
- Managed Git/GitHub collaboration across a multi-member team building practical computer vision systems.

### Junior Software Developer (Internship), EthicCoders

Jul 2021 – Dec 2021 · Remote

- Trained in Dart and Flutter to build Android and iOS apps, from a weather app on a public API to a range of UI challenges, then moved into teams working on real apps.
- With teammates, built 'Joyful Lips', a digital version of the book that proved useful during the COVID period.
- Merged work through Git, Bitbucket and Sourcetree, and made app promo images and videos for YouTube and the Play Store, plus Canva content for the BeInspired and Nearby Churches apps.
- Supported customers of new and released apps, and tested the eMissal and Radio Veritas apps, submitting detailed bug reports.

## Projects

### Inference Autopilot

Oct 2026

An autonomous SRE for LLM inference. It monitors an inference stack, identifies what went wrong with real GPU telemetry and deterministic root-cause analysis, suggests a policy-gated remediation, then checks that the fix actually worked. Open source.

Tech: Logs, Metrics, Traces, Health checks, RCA, Remediation
Source: https://github.com/CJ445/inference-autopilot

### IoT Fleet Management Platform

Oct – Nov 2025

Distributed edge orchestration for 100+ Raspberry Pi nodes using containerized microservices, PostgreSQL, MongoDB and Redis. OTA updates with rollback, real-time telemetry, and remote commands over MQTT and REST.

Tech: Docker, PostgreSQL, MongoDB, Redis, MQTT
Source: https://github.com/cj445/IoT-Fleet-Management

### Visual Search with Vision-Language Models

Feb – Apr 2025

Retrieves images from a text query or a sample image by embedding both into a shared space, with indexed similarity search over large datasets. Built for the Intel Unnati Industrial Training Program.

Tech: VLMs, Embeddings, Similarity search, Python
Source: https://github.com/CJ445/Intel-Unnati-VLM

### Real-Time Occupancy Analytics

Sep – Dec 2024

Live campus CCTV streams processed through Kafka into PostgreSQL, with Grafana dashboards for floor-wise occupancy insights.

Tech: Kafka, PostgreSQL, Docker, Grafana

## Live demo

Inference Monitor: YOLOv8n object detection running FP32 vs INT8 on ONNX Runtime Web, entirely in the visitor's browser. Camera frames are never uploaded.
Open it on the main page: https://cj445.github.io/#demo

## Skills

- **Programming**: Python, SQL, Shell Scripting
- **Backend & software engineering**: REST APIs, Microservices, CI/CD, Git, GitHub, RAG schema design
- **Databases & distributed systems**: PostgreSQL, MongoDB, MySQL, Redis, Apache Kafka, MQTT, ChromaDB, HNSW indexing
- **Cloud & infrastructure**: Azure, Azure DevOps, Azure Container Registry, Docker, Kubernetes, Linux, Ubuntu, Netplan, Networking, SSH, Grafana
- **AI/ML & computer vision**: PyTorch, TensorFlow, Keras, scikit-learn, OpenCV, ONNX, TensorRT, NVIDIA DeepStream, YOLOv8, Mask R-CNN, CLIP, RasterIO

## Education

B.Tech, Computer Science Engineering (AI & ML), Karunya Institute of Technology & Sciences (2023 – 2027)

CGPA 7.75 / 10. Focus: distributed systems, cloud & infrastructure, AI/ML.

## Publications

- Physics-Guided Residual Super-Resolution for Thermal Infrared Satellite Imagery. IEEE ICECA 2026 (Accepted)
- Smart Security Management using IoT and HC-05 Bluetooth Module. 2024 8th International Conference on Inventive Systems and Control (ICISC), IEEE (Presented 29–30 Jul 2024, on IEEE Xplore 19 Sep 2024)

## Certifications

- Microsoft Certified: Azure Fundamentals
- Intel Unnati Industrial Training Program
- MongoDB certification (12 units)
- SnowPro Associate: Platform Certification
- NVIDIA Deep Learning and AI on Jetson Nano
- Duke University: RAG
- University of London: Machine Learning for All
- Scaler: PyTorch
- OpenCV Bootcamp

## Recognition

- **Bharatiya Antariksh Hackathon 2025 (ISRO)**, 4th place nationally (2025). Team Lead. Satellite image super-resolution among 61,000+ students across 8,744 teams.
- **Smart India Hackathon 2025 (ISRO track)**, Grand Finale, top 5 (2025). Quantized and deployed the thermal super-resolution model on NVIDIA Jetson.
- **Google Developer Groups On Campus, Karunya**, Campus Lead (2024 – 2025). Led a 25-member student engineering community and organized workshops, developer events, and a state-level hackathon.
- **Institution's Innovation Council, Karunya**, Student Coordinator (Nov 2024 – Nov 2025). Coordinated student work for the Ministry of Education's Innovation Cell, set up in 2018 to build a culture of innovation across higher education institutions.
- **Competition wins**, Three #1 finishes. First place in a Technical Quiz, in IoT Odyssey MK24, and the Academic Incentive Award.
- **Workshops taught, Karunya Innovation and Design Studio**, Teaching beyond the classroom (2024 – 2025). Python for IGCSE students from Hebron School, data science and machine learning for Kathir College, and an Arduino programme for school children.

## Writing

- [How to Run RT-DETR in DeepStream](https://medium.com/@thecyriljacob/how-to-run-rt-detr-in-deepstream-c3e32940e71d): Deploying RT-DETR object detection inside NVIDIA's DeepStream SDK for real-time inference pipelines.
- [What Is Buildspace, Anyway?](https://medium.com/@thecyriljacob/what-is-buildspace-anyway-78c825742cf4): What it means to build projects in public alongside a community of makers.