Tejashree Nagesh Reddy

Seasoned collaborator experienced in meeting needs, improving processes, and exceeding requirements in team environments. Diligent worker with strong communication and task prioritization skills.

• Survey on Surveillance Robots, 6th National Conference held at AMC Engineering College on 'VLSI, Communication & Computer Networks VCCN6', Bangalore, Karnataka, 2019.

• Actively participated in the MET ABA@BU Hackathon in October 2023, developing innovative solutions to real-world problems. Collaborated with a diverse team to design and present a functional prototype, gaining experience in project management, coding, and teamwork.

• The Best Project Award was given by Advanced Technologies for Smarter and Secured Life (ATSSL) in 2018.
• The Best Student Award was given by the Indian Society for Technical Education (ISTE) in 2019.
• Represented Karnataka in 37th Junior National Archery Championship in 2014 and the 4th Mini National Archery Championship in 2011 at Hyderabad.
• Attended Combined Annual Training Camp conducted by 7 Karnataka Battalion NCC in 2012-13.
• Secured 2nd place for a project titled IOT FOR BLIND PEOPLE conducted by ACS College of Engineering in 2018.

• Participated in Statewide Engineering IT quiz 2019 organized by Board of IT Education Standards (BITES) and Tata Consultancy Services.
• Participated in Jr/Sr First Aid Quiz competition organized by St. John Ambulance (INDIA) in 2013.
• Volunteered to serve the people with National Social Service (NSS) organized by AMC Engineering College at Maladu District, Hassan in 2019.

• Mobile Phone Detector, 2017: This project was designed for mobile applications. Whenever the user uses the mobile in restricted areas, the signal will be sent to the alarm, and it starts beeping. This was mainly mapped out for the college students to stop using mobiles in classes during the lecture. It had raspberry pi as the main component and mobile was integrated with it.

• Smart Blind Stick Navigator, 2018: This prototype creates a better environment for blind people. It is built with abundant sensors which are used in IoT. The main aim of the project is to design a voice-based alerting system for blind people. It consists of a Water detector, Fire Detector, Motion detector, Light detector, Buzzer, Ultrasonic sonic sensor, and many more. An inbuilt GPS and GSM are attached to the Arduino to track the person in case of emergencies.

• IoT for Blind People, 2018: This is an enhancement of Blind Stick Navigator with a Hands-free application at home added to it. With the navigator project, Google Assistant is also activated to let the person command using voice. New features are controlling the fan, switching off lights (on and off), finding the Stick if misplaced, and controlling the appliance. This not only helps Blind people to travel outside but also helps them stay independently at home.

• Multi-Functional Border Security Robot, 2020: This model was created to help soldiers during the war and to make the machine multitask so that not only it can check for several parameters for monitoring but also carry out other significant tasks on its own. It can perform Landmine detection, Face recognition, Missile and Motion detection, and Surveillance. Python is used to give instructions to the prototype.

• Analysis on Stock Market and Unemployment in USA, 2024: This analyzes the relationship between stock market performance and unemployment rates to identify economic trends and impacts on employment. It utilizes SQL for creating and populating dimension and fact tables and performing ETL processes, Tableau for data visualization and generating insightful dashboards, and Python for data manipulation, cleaning, and preprocessing. The objective is to provide a comprehensive understanding of how stock market dynamics influence employment rates.

• COVID-19 Impact on India's Unemployment: A K-Means Analysis, 2023: The project focuses on assessing the impact of the COVID-19 pandemic on the labor market in India. It aims to examine how unemployment rates have varied across different states, determining which regions have been more severely affected. The study utilizes K-Means clustering, an unsupervised machine learning method, to classify states based on the level of impact on their labor markets. This method helps in visually representing temporal and geographic trends, making it easier to identify patterns in employment changes.

• [AWS Certified Solutions Architect - Associate], [Amazon Web Services]

Associate certification validates expertise in designing and deploying scalable systems on AWS. It covers best practices for architectural design, cost management, and implementation, making it essential for professionals aiming to build robust cloud-based solutions.