Education

Research Fellow      

MEMS, Microfluidics and Nanoelectronics Lab, BITS-Pilani, Hyderabad Campus       2025-Present

 M. Tech in Nanotechnology, Center for Nano Science and technology,                                                                                  2023-2025 

JNTUH, 

7.6 C.GPA

Bachelor of Technology in Electronics and Communication Engineering,                 2019-2022

CMR Technical Campus, Medchal, Hyderabad,

 6.30 C.GPA

Diploma in Electronics and Communication Engineering, Government Polytechnic, Nizamabad, 2016-2019

83.01%

SSC, Krishnaveni English medium High School, Manthani, Peddapalli, 2016

8.8 C.GPA

• TECHNICAL SKILLS:

•     Programming: Python, Arduino IDE, Embedded C

•     Microcontrollers: AVR board, Arduino boards, Mc 8051

•   Characterisation techniques: XRD, CV, FTIR, UV Spectroscopy, Spin Coating, and Particle size analyzer

•  Software: Origin, Xpert high score

•   MS Office: Word, PowerPoint, Excel.

•  Proficient in using AI Chatbots (ChatGPT, Gemini AI, Copilot).

• WORKSHOPS & CERTIFICATIONS:

• Certificate Of Participation, Rise of Lithium–Ion Batteries for Electric Vehicles, Department of Physics, School of Sciences and Humanities, SR University, Warangal, India, Apr 2024

• Certificate Of Participation, ICAN 1.0 workshop conducted for 2 days on IoT-enabled Cyber-physical systems with advanced Nano-electronic microfluidic Devices and sensors, BITS Pilani, Hyderabad Campus, Nov 2023

• AI for Everyone, Coursera, May 2020

• ·         Synthesis and Characterization of different nanomaterials and structures.

• ·         Proficient with Microcontrollers, Arduino boards, Analog / Digital circuits

Work Experience

• PROFESSIONAL EXPERIENCE

• Indotronix Avani, Hyderabad, India                             Sep 2022 – Aug 2025      

• Executive - Talent Acquisition

• Description: I was responsible for hiring the IT talent for my clients in USA, I act as liaison between clients and candidates

• Skills: Corporate Communication, Screening, Sourcing, Candidate engagement, MS Office.

• ACADEMIC PROJECT DETAILS:

• M. Tech Projects: 

1.       Project 1 (Minor)

Title: Synthesis of rGO@Ni@Co nanocomposite for Supercapacitor Application

Description: Developed a novel reduced Graphene Oxide (rGO)@Ni@Co nanocomposite for use as an electrode material in supercapacitors to enhance energy storage capacity, power density, and cycle stability. Key Activities:

     Synthesised rGO using a chemical reduction method and incorporated Nickel and Cobalt nanoparticles through a hydrothermal process.

     Characterized the nanocomposite using techniques like XRD, SEM, TEM, and electrochemical testing (CV).

Evaluated the performance metrics, including specific capacitance, energy density, and cycling stability.

2. Project 2 (Major)

Title: Electrochemical Analysis of Nano-composites with 2D-layered Materials

Description: Synthesized and analyzed nanocomposites with 2D layered materials (rGO@Ni–MgO, rGO@Ni– ZnO, rGO@Ni–V₂O₅, and rGO@Ni–MoO) to study their electrochemical performance in energy application.

Key Activities:

 Synthesized rGO@Ni–MgO, rGO@Ni–V₂O₅ and rGO@Ni–MoO₃ a n d rGO@Ni–ZnO nanocomposites via co-precipitation method, ensuring homogeneous dispersion and phase formation under ambient air conditions.

   Characterized the prepared nanocomposites using X-ray Diffraction (XRD), Scanning Electron Microscopy (SEM), Raman    Spectroscopy.

 Evaluated electrochemical performance through Cyclic Voltammetry (CV), Galvanostatic Charge– Discharge (GCD).

• B. Tech Projects:

1. Project 1

• Title: Home Automation using Webpage

Role: Team member

Description: This project implements a home automation system that allows users to control various home appliances via a webpage. By leveraging web technologies and embedded systems, the project enables remote management and automation of home devices from any internet-enabled device

Key Components and Technologies:

 Web Interface: A user-friendly webpage serves as the control interface. It provides an intuitive graphical layout for managing home appliances, including switches for on/off control, status displays, and real-time feedback.

 Microcontroller/Embedded System: An embedded system, such as an Arduino acts as the central controller for the home automation system. It processes commands received from the web interface and controls the appliances accordingly.

  Wi-Fi Module: A Wi-Fi module (e.g., ESP8266 or ESP32) connects the microcontroller to the internet, enabling communication between the webpage and the embedded system.

  Relay Modules: Relay modules are used to switch home appliances on or off based on commands from the microcontroller. They interface with the physical devices and execute the control commands.

 Webpage Development: The webpage is designed using Arduino programing. It includes interactive elements such as buttons and sliders for controlling appliances and displays the current status of each device.

 Microcontroller Integration: The microcontroller is programmed to interpret commands from the web server. It then sends appropriate signals to the relay modules to control the appliances. Both webpage and controller are connected using Wi-Fi Module

  Real-Time Updates: The system supports real-time updates, allowing users to see the current status of their appliances and receive immediate feedback when changes are made.

2. Project 2

Title: Detecting Web Attacks with End-To-End Deep learning Role: Team member

Description: This project addresses the increasing prevalence of web attacks in the digital era by employing an unsupervised end-to-end deep learning approach for real-time detection and prevention. Developed by a team of four members, this system aims to enhance web application security through advanced machine learning techniques.

Key Components and Technologies:

Unsupervised Deep Learning: Utilizes an unsupervised deep learning model to automatically detect anomalies and potential attacks on web applications without the need for pre-labeled attack data.

 Robust Software Modeling Tool (RSMT): Implements a robust software modeling tool that continuously monitors and characterizes the runtime behavior of web applications. This tool helps in identifying deviations from normal behavior indicative of potential threats.

Test Applications and Datasets: Evaluates the performance of the unsupervised learning approach using various test applications and intrusion datasets created specifically for this project. These datasets help in assessing the model's effectiveness in detecting different types of web attacks.

Integration and Deployment: The developed software can be directly installed on web applications or used as needed via command-line interface. This flexibility allows for easy integration into existing systems and on-demand security monitoring.

 Model Development: The team designed and trained the unsupervised deep learning model to analyze web traffic and identify anomalous patterns associated with various web attacks.

  Performance Evaluation: Conducted thorough testing and evaluation of the system’s performance against custom- created datasets and test applications. This evaluation focused on the accuracy of attack detection and the system's ability to minimize false positives.

 Deployment: The final software is equipped for straightforward installation and usage, providing web administrators with an effective tool for real-time threat detection and response.

• Diploma Projects:

1. Project 1

Title: Home Automation using DTMF Role: Team Lead

This project demonstrates the implementation of a home automation system utilizing Dual-Tone Multi- Frequency (DTMF) signals and an AVR microcontroller. The system allows users to control various home appliances remotely through their telephone keypad.

Key Components and Technologies:

 DTMF Signal Processing: The system decodes DTMF signals received from a standard telephone keypad. Each keypress generates a unique tone pair, which is interpreted by the system to perform specific actions.

 AVR Microcontroller: An AVR microcontroller is used as the central control unit of the system. It processes the decoded DTMF signals and sends commands to the appropriate relays to control home appliances.

Relay Modules: Relay modules are integrated into the system to switch the home appliances on or off based on the commands received from the AVR microcontroller

Signal Decoding: The project utilizes a DTMF decoder IC to convert the tones from the telephone keypad into digital signals that the AVR microcontroller can interpret.

 Microcontroller Programming: The AVR microcontroller is programmed to handle the decoded signals, execute corresponding commands, and control the relay modules.

Appliance Control: Users can control various appliances (such as lights, fans, and other electronic devices) by pressing specific keys on the telephone keypad. The system responds to these inp 

Publication

Contact

Awards/Achievement/Certifications

• TRAINING EXPERIENCE:

• ·         Embedded System and Solar Installation, Resolute Electronics India, Private Limited, Medchal, Nov 2018 –Apr 2019

• ACHIEVEMENTS:

• ·           Participated in Srujana Tech fest at the district and state level, and earned certifications

•  Indias Next Gen Leaders Program (Online). Do Well Do Good