top of page

Harish Rohan Kambhampaty

Autodidact | Philomath | Developer

profilePic_edited_edited.jpg


Work Experience

Realtime LiDAR Data Streaming Project:

A Study on High-Volume Low-Latency Data Streaming for Realtime LiDAR Applications
Role: Research Intern@TiHAN, Indian Institute of Technology - Hyderabad
Duration: 3 Months (Full-Time)
Nature of Work: 

  • Peer-to-Peer Architecture (using WebRTC)

  • Client-Server Architecture (using Firebase: Realtime Database)

  • Integration with Robot Operating System (ROS) in C++

  • Octree Compression for LiDAR data (also investigated Google's Draco Compression)

  • Proposed a Minimal Installation Setup that worked with WebAssembly in any Chromium browser

Status: Application Deployment Completed

​

Event Management Application (Cockcrow Events)
Role: Lead Backend Engineer@Rivach LLP
Duration: 6 Months (Part-Time)
Nature of Work: 

  • Designed and developed back-end for event-management solution (Cockcrow events) for placing orders with third-party vendors

  • Highly scalable, extensible and cross-platform  full stack application (MERN)

  • Implemented OAuth2.0 with Role-Based Access Control

  • Used AWS Services like Lambda, API Gateway, S3, CodeBuild, and SNS to deploy application

  • Setup CI/CD with GitHub repository to allow future development

Status: App is currently live in Google Play Store.
Approach:

  • Worked with key stakeholders to understand requirements of event management app

  • Determined alternative solutions

  • Identified potential challenges in implementation

  • Finalized on solution

  • Implemented back-end for solution

Contribution:

  • Identified a technology stack that meets current industry standards in web development and security. MERN stack was ideal for a highly scalable, extensible and cross-platform solution

  • Implemented OAuth 2.0 authentication framework

  • Used AWS services and successfully deployed all the components of the application on the Cloud

  • Played a vital role in architecting the data model and REST APIs for the backend; developing the code; integrating with the frontend; and finally developing a CI/CD deployment pipeline to update resources on AWS

  • Instrumental in identifying the most optimal use of the AWS services used like Lambda, API Gateway, S3, CodeBuild, and SNS

  • Linked existing GitHub repositories with the CI/CD pipeline has eased future development efforts for our team

  • Developed detailed documentation of the application

​


Training & Certifications

AWS Certified Developer – Associate
Issued By: Amazon Web Services Training and Certification
Date of Certification: Sep 24, 2022
Valid Till: Sep 24, 2025
Validation ID: JSPWE51CRNRQ1MWR​

aws-certified-developer-associate.png

Data Analytics with Python
Issued By: NPTEL Online Certification
Course Period: Jan-Apr 2022
Final Score: 90% (Elite+Gold Performance)
Validation Link​

NPTEL_elite_gold.png
NPTEL_topper_2%.png

Data Science for Engineers
Issued By: NPTEL Online Certification
Course Period: Jul-Sep 2021
Final Score: 84% (Elite+Silver Performance)
Validation Link

NPTEL_elite_silver.png
NPTEL_topper_5%.png


Extra-Curricular Activities

Advanced Academic Center
Role: Head of Training & Development & Core Committee Member
Nature of Work: Took up 3 activities as a core member of AAC​

​

Activity 1 - GitHub Initiative

  • Proposed and setup GitHub Organization for AAC

  • Provided detailed procedures for creating and maintaining the organization’s repositories

  • Conducted a training session for juniors to introduce the fundamentals of version control and Git

​

Activity 2 - Mentoring

  • Mentored two teams in the area of web development

  • Provided overview of topics

  • Recommended good sources to learn from

  • Supervised the teams’ work and made suggestions

  • Helped with general troubleshooting and bug fixing

​​

Activity 3 - Training and Development

  • Currently managing Training and Development of AAC students

  • Ensuring students were trained in domains of their choice by assigning mentors

  • Conducting tests on platforms like Hackerrank and CodeChef

  • Setting up teams and projects to cultivate teamwork


International Publications

A Novel Real-Time LiDAR Data Streaming Framework

Abstract– In this paper, a novel framework has been proposed which is capable of efficiently streaming LiDAR data over the internet. The proposed framework consists of various subsystems that handle data in multiple stages. The end-to-end framework runs over Robot Operating System (ROS) platform. The challenge of Clock Synchronization was addressed using a unique approach during the testing process. A detailed analysis to validate the quality of decompressed data has also been performed for which cloud distance was used as a metric. The implemented model was able to perform data transmission with an average latency of 160.62 ms for low-resolution compression mode.

​

Nature-Inspired Methods and Machine Learning Algorithms for Intelligent Prediction of Heart Diseases

Abstract– The prediction of the heart disease has been assessed by the combination of nature-inspired techniques and machine learning algorithms. This paper presents the outcome of the research conducted with four nature-inspired algorithms, namely Ant, Bat, Bee and Genetic algorithms and two machine learning classification models, Random Forest and SVM to predict the heart disease. Feature variables are extracted from heart data obtained from the UCI Machine Learning Repository. The output of the optimization techniques is used to train models based on the two classification algorithms.

​

A Novel Deep-learning based Classification of Alzheimer's Disease in Adults

Abstract– In this paper, Sequential Deep Convolutional Neural Network was used to perform a 5-way classification over degree of affectedness from Alzheimer's Disease. Data from two varied sources was combined. The data was oversampled using Synthetic Minority Over-Sampling technique from imblearn. The Deep CNN model was able to achieve a maximum of 93.57% accuracy while being tested on data from both data sources. Thus, Deep CNNs are able to classify brain MRI images from varied data sources with sufficient accuracy.

​

Reference Architecture for Intelligent Enterprise Solutions

Abstract– This paper progressively elaborates a reference model for enterprise solutions, builds an integrated view of data, information and intelligence components and presents a reference architecture for intelligent enterprise solutions. Finally, it applies the reference architecture to an insurance organization. The reference architecture is the outcome of experience and insights gathered from developing intelligent solutions for several organizations.

​

bottom of page