Dhruv Arora

I possess a strong work ethic and am driven to succeed. I take full ownership of any situation I encounter, and embrace difficult challenges with confidence and determination.

• Lead a team which got 9th position out of 400+ teams in Breached 2.0 a CTF event.
• Got AIR 24th, State rank 4th and Class rank 2nd in Silverzone International Informatics Olympiad 2021.

1. Depression among Students: A Data Analysis Study
Conducted a comprehensive study with 150+ students to detect and analyze depression using data-driven techniques. Data was collected through a survey of Psychologically certified Questions. Employed Tableau to create impactful visuals including scatterplots, pie charts, and donut charts, supporting the identification and understanding of depression patterns. Additionally, provided insightful recommendations to 50+ students on the verge of depression or already experiencing it, based on the patterns discovered through the analysis of their responses.

2. Enhanced Disease Detection: ML & Deep Learning Approach
Developed a predictive model utilizing deep learning and machine learning algorithms, such as deep learning reinforcement, decision tree, and random forest, to accurately predict 70+ diseases based on 250+ symptoms. Leveraged extensive data analysis and feature engineering techniques to train and optimize the models for improved accuracy and performance. Successfully implemented the model, enabling efficient disease identification. Additionally, provided personalized recommendations to users regarding potential treatment options and helpline contacts of nearby healthcare professionals.

3. Optimizing Inventory Management: Case Study on Order Trends Analysis for a Nearby Commercial Shop
Utilizing Microsoft Excel, SQL, and Tableau, I analyzed the order trends for a nearby commercial shop. By examining historical data, I identified patterns and insights to optimize inventory management. Dynamic visuals, including Gantt charts, bar charts, and line charts, were created using Tableau to present the findings. Overordering was reduced by 18%, improving operational efficiency, reducing inventory costs and ensuring optimal stock levels and maximizing profitability.

4. Dynamic Full Stack Website for Nearby Dining Establishment
The website offers robust functionality and a seamless user experience. Customers can easily browse the menu, place online reservations, and access essential details about the restaurant's offerings. This project involved the development of a dynamic full stack website for a nearby restaurant, utilizing HTML, CSS, and JavaScript for the frontend, and PHP, Apache, and MySQL for the backend.

5. Full stack E-Commerce Platform for Local Shops
Leveraging HTML, CSS, and JavaScript, I created a visually appealing and user-friendly frontend, ensuring an engaging and seamless experience for website visitors. By harnessing the capabilities of PHP and MySQL on the backend, I established a robust infrastructure that facilitated secure data management

Advanced ML and Deep learning for Disease Diagnosis: Predictive Symptom Analysis(Ongoing)

Focusing on evaluating current models used in disease diagnosis while also developing newer models to enhance accuracy and expand the range of features. By leveraging the latest techniques in ML and deep learning, I aim to improve the performance of disease diagnosis models to provide health professionals and clients with more accurate and comprehensive diagnostic tools, contributing to more efficient healthcare decision-making and better patient outcomes.

• Portfolio Website (https://dhruvarora.net):

Website created to showcase projects and skills (under construction).

• Backroads Tour Company (https://dhruvarora.net/back_roads/index.html):

Demo website created using CSS Flexbox and Grid.

Focuses on tour descriptions and visuals.

• Virtual Assistan t:

Windows-based virtual assistant created using Python libraries and APIs.

Includes various features like weather information and Wikipedia search.

• Enquiry Management System (TechMaster):

GUI-based project in Python for managing user enquiries.

Allows tracking of enquiry progress and generating reports.