K HARSHAVARDHAN RAJU

Seeking Entry-Level Role in Software engineer | Team Player with Strong Problem-Solving Skills | Eager to Make an Impact

• Member in National Service Scheme (NSS)
• Member of ROTRACT club NITPY
• LEAP | Content Creator
• Event Coordinator for Technical Fest in NITPY
• Certification wing head for Technical Fest in NITPY

• Won 1st place in Relay Coding Event conducted in Gyanith 2023 in NITPY

• Travelling
• Watching movies

Final year project:The project enhances SDN DDoS resilience through adaptive policies and real-time traffic analysis. Methodology employs dynamic rerouting and resource allocation, responding to evolving threats.

 YHills edutech: 

Machine Learning :

 Using python and Machine Learning Algorithm, developed predictive models for both labelled and unlabeled data. Also improved the accuracy of the models by using different feature engineering. 

Predicted taxi fare in NYC: Developed a predictive model that could accurately predict taxi fares in NYC based on distance and number of persons. 

Deep learning: 

Image classification of X-Rays: Develop an image classification model using deep learning to identify COVID -19 or Pneumonia in X-ray images. Preprocess the dataset, split it into training and testing sets, and use Inception V3 Model (CNN) for training. Evaluate the model's performance on the test set, measuring accuracy, precision, recall, and F1 score. Present the results and discuss potential improvements in the detection weather body is infected with COVID-19 or Viral-pneumonia. 

Machine learning: 

Project on deep fake detection, Implement a deep learning-based image classification system to detect deep fake images. Curate a diverse dataset of authentic and manipulated images, preprocess them, and split into training and testing sets. Train a Basic convolutional neural network (CNN) using transfer learning techniques such as using a pre-trained mode like ResNet or VGG. Evaluate the model's accuracy and confusion matrix on the test set, emphasizing precision and recall.

Participated in Workshop is conducted by Amazon web Services tells about:

• App serverless features, including authentication, image storage, NoSQL data storage, and serverless functions
• Building, operating, and scaling end-to-end streaming architectures
• Building in-demand AWS Cloud skills

• Publication Title: 2024 International Conference on Signal Processing, Computation, Electronics, Power and Telecommunication (IConSCEPT)
  
• Article Title: Enhancing Software-Defined Networks (SDN) Environment to detect DDoS Attack using KNN Classifier Algorithm.
• The project enhances SDN DDoS resilience through adaptive policies and real-time traffic analysis. Methodology employs dynamic rerouting and resource allocation, responding to evolving threats.