Available for Opportunities

Divyanshu
Bhaik

Senior Engineer · MediaTek ·

Telecom protocol engineer with expertise in VoWiFi, 4G IMS, and IPSec. Building AI-powered tools and automation frameworks at the intersection of wireless networks and machine learning.

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Years at MediaTek

200+

Research Citations

90%

Issue Reduction

8.86/10

CGPA · NIT Hamirpur

// Technical Arsenal

Skills & Expertise

🐍

Programming

Python C++ Automation Scripts API Development

Expert

📡

Wireless Technologies

VoWiFi 4G LTE IMS NAS RRC SIP

Expert

🔐

Networking & Security

TCP/IP IPSec IKEv2 ISAKMP N3GPP

Advanced

🧠

AI / Machine Learning

Prompting RAG DNN CNN TensorFlow Keras RNN/LSTM

Advanced

🛠️

Tools & Platforms

Amarisoft Linux Git VS Code Wireshark

Advanced

🧪

Testing & QA

Protocol Testing Regression SQC Integration Functional

Expert

// Career Journey

Work Experience

MediaTek · NOIDA

Jun 2022 – Present

Senior Engineer Full-Time

Feature Owner for "Backup Calling" — increased coverage for feature testing in Lab and Live Network environments, resulting in ↓ 90% reported issues
Implemented Internal Lab Environment & Automation Setup for testing Emergency Calling requirements for Verizon, resulting in ↓ 30% CCP/DCP issues
Developed an AI Assistant (Prompting & RAG) that generates JSON format strings for dynamically setting Network Parameters for Amarisoft Call-Box

Python RAG Prompting Amarisoft IMS VoWiFi IKEv2

Protocol Testing Engineer Internship

Jan 2022 – Jun 2022

Developed Automation Test Scripts using Python for protocol validation
Implemented APIs to control Network & DUT behavior and validate modem logs from IMS (SIP), N3GPP (ISAKMP, IKEv2) and 3GPP (NAS, RRC)
Implemented VoWiFi Testing Environment in lab using Amarisoft Call-Box
Performed various testing: SQC, Integration, Regression, Functional

Python Amarisoft VoWiFi SIP NAS RRC ISAKMP

IIT Jodhpur · Dept. of CSE

May 2021 – Jul 2021

Research Intern Research

Worked on Earthquake Prediction using AI methods with the Stanford Earthquake Dataset (STEAD) from Kaggle
Performed data pre-processing and fine-tuning of AI models including RNN and LSTM
Evaluated models using Accuracy, Sensitivity (Recall), Specificity, Precision, F1 Score, and Confusion Matrix

Python RNN LSTM TensorFlow Keras

// Research Output

Publications & Research

ELSEVIER · Biomedical Signal Processing and Control

A Deep Learning Based Approach for Automatic Detection of COVID-19 Cases using Chest X-Ray

📅 Sep 23, 2021 👁️ 532 Reads 📖 200 Citations

Applied C-GAN for Image Segmentation and extracted image features using SIFT and BRISK algorithms
Combined acquired key points with CNN models including VGG-16 and DenseNet-169 for COVID-19 classification
Proposed method outperformed existing approaches with state-of-the-art metrics

96.60%

Accuracy

95.00%

Sensitivity

97.40%

Specificity

200+

Citations

View Paper →

// Open Source

Featured Projects

🫁

GitHub →

Lung Cancer Detection

Detection of lung cancer and malignant nodules from chest CT scans using watershed algorithm with Sobel filters and CNN architectures including VGG16 transfer learning on the LUNA16 dataset.

Python CNN VGG16 Image Processing

🦠

GitHub →

COVID-19 Detection

Deep learning pipeline for COVID-19 detection from chest X-rays using C-GAN segmentation, SIFT/BRISK feature extraction, and VGG-16 / DenseNet-169 transfer learning. Basis for the published Elsevier paper.

Python C-GAN VGG-16 DenseNet TensorFlow

📡

GitHub →

CSI Estimation in 5G

Channel State Information estimation for 5G wireless networks using deep learning techniques, combining telecom domain expertise with neural network modelling.

MATLAB Deep Learning 5G Wireless

🚗

GitHub →

Smart Road Assistant

AI-powered road safety system using computer vision to detect hazards and prevent accidents through real-time intelligent alerting and driver assistance.

Python Computer Vision AI Safety

👁️

GitHub →

YOLO Object Detection

Implementation of the YOLO (You Only Look Once) real-time object detection algorithm applied to both static images and live video streams using Python and OpenCV.

Python YOLO OpenCV Computer Vision

⠿

GitHub →

Text-to-Braille Converter

Assistive technology device that converts written text into Braille output using an Arduino UNO microcontroller, bridging digital text with tactile reading for the visually impaired.

Python Arduino IoT Assistive Tech

DivyanshuBhaik

Skills & Expertise

Work Experience

My Education

Publications & Research

Featured Projects

Get in Touch

Divyanshu
Bhaik