Diksha Devi

Highly motivated professional with a keen eye for detail and a creative mindset. Passionate about continuous self-improvement to enhance analytical skills. Eager to apply my knowledge to achieve organizational goals and meet requirements.

• HINDI, 100/100
• ENGLISH, 80/100

Public Education Foundation Non Profit, Coordinated with volunteers and managed event logistics., Organized fundraising events, raising over $5,000 for community programs., Promoted events through social media and local advertising.

Will be provided upon request.

• Volunteering
• Traveling
• Chess
• Cooking/Baking

Secure Network Design, 02/2018 - 04/2018

RESPONSIBILITIES

To undertake the project, an in-depth investigation into the network infrastructure of commercial banks for inherent security challenges information.

 To guarantee the network's effectiveness, the choice of network elements and devices was executed.

 To create a secure and well-organized network, an architectural layout segregating departments into distinct VLANs using Cisco Packet Tracer was established.

 To enhance departmental connectivity in specific subnets, ensuring efficient address allocations were configured. 

Comparative Study of Wireless Networks Using Different Protocols, 09/2017 - 11/2017

RESPONSIBILITIES

 To comprehend the implications of network architectures and routing protocols.

 To ensure the effective modeling of network scenarios with crucial components identification.

 To further analyze network models with a detailed comparison between infrastructure networks (WLANs) and MANETs.

 To interpret the outcomes, average delays in wireless and MANET networks were scrutinized. Neural Network Approaches to Forecast Disease Trends from High-dimensional Human Health Datasets., 02/2017 - 04/2017,

RESPONSIBILITIES

 To gain insights into the current landscape of predicting human disease patterns, extensive research across scientific journals, databases, and research papers was conducted.

 To design the architecture for ECNN-HDPT by integrating various methodologies to predict diverse human disease patterns.

To commence the algorithmic process by collecting genome sequence training data from a comprehensive database.

 To compare the proposed ECNN-HDPT model with earlier models, specifically G-HRF and IHDGAP, in terms of processing time.

 To acquaint oneself with the significance of sensitivity, specificity, and F-score in evaluating performance to develop proficiency in model assessment.