"I am not stupid, just too lazy to show how smart I am”

I am a A Passionate Learner👨🏻‍💻 and a Sophophile📚 I will graduate with Master's in Computer Science from North Carolina State University, Raleigh in May 2023. Currently, I am working as a Research Assistant under Dr. Edward Gehringer assisting his research focused on improving Peer Assessment System - Expertiza (Open Source), while officially maintaining the system. Previously, I have worked as Software Engineering Intern at Zscaler in the R&D team of the ZPA tool. Find my resume here

1. Design and Analysis of Algorithms
2. Internet Protocols
3. Automated Data Learning Analysis
4. Internet of Things: Architectures, Applications, and Implementation
5. Object-Oriented Design and Development
6. Algorithms for Data Guided Business Intelligence.
7. Software Engineering
8. Database Management concepts and Systems
9. Human-Computer Interaction
10. Resource Dependent Neural Networks

Expertiza: Enhanced the application by implementing the Suggestion Detection Algorithm in the current codebase, which will help reviewers get live feedback for the review provided.

• Core member of the Research and Development Lab of Computer Science & Engineering Department. My areas of research include Application of Computer Vision and Deep Learning methods like Evolutionary Algorithms and Nature Inspired Algorithms in Healthcare.
• Coordinating juniors to work on innovative research projects by helping them in their endeavours. Presented a Research Paper in International Conference on Smart Sustainable Intelligent Computing and Application (ICITETM-2020).

• Assisting research focused on improving Peer Assessment System - Expertiza (Open Source), while officially maintaining the system.

• Implemented design patterns such as DTO, DAO, and Model View Controller in conjunction with Hibernate ORM to retrieve data from a Postgres database and reduce redundant database access statements, resulting in a 10% boost in tool speed.
• Collaborated with other developers in the team to eliminate the most current security issue by upgrading the Spring framework and enhancing tool performance by 35%.
• Participated in designing and developing the ZPA tool using MVC architecture utilizing the Spring framework while working in an agile environment, which sped up development by 30%.
• Contributed to the continual improvement and reliability of the ZPA tool by fixing ad hoc defects in the codebase as reported by customers and QA and tracked using JIRA.

• Structured and designed data models consisting of 100+ million records and 40+ tables by utilizing Big Data technologies like Spark, Hadoop, HDFS, and Hive, hence reducing the system complexities and increasing overall efficiency by 40%
• Prepared data warehouse on AWS and Azure by working on services like EC2, EMR, S3, Azure Data Lake Storage, Azure Data Factory, Azure Databricks. to shape the analytical pillar. Accelerated the process of extraction, transformation, and verification by almost 30%
• Conceptualized and conceived high complexity dashboards with over 80 screens and utilized 20 different visualizations for high level business analytics using Tableau exhibiting various KPI’s and key business metrics to major leading Biopharmaceutical client in the US Pharmaceutics market resulting in real time analysis, forecast track, and identify trends leading to a 15% increase in sales
• Devised process in Boomi to ingest & extract pharmaceutical data from RDBMS like Oracle DB, MySQL, Salesforce, IQVIA, further formalized Spark code in Python using Spark SQL & Data Frames for aggregation and programmed Hive queries to transform data for additional processing, consequently reducing company cost and enhancing performance by almost 20%
• Engaged and worked directly with business partners for major Biopharmaceuticals company in different geographies like the US, ACE countries, EU (European Union) and Latin America in gathering business requirements, discussing business plans, and providing data analysis
• Trained and guided Interns and fresh hires in Big Data and ETL, on the AWS cloud, and front-end tools such as Tableau, Microsoft Excel, increasing productivity and helping to exceed the goal by 120%
• Automated the testing process by developing a Python script that automatically executes testing queries and reports the results on the dashboard for further scrutiny and thereby saving approximately 300+ man-hours.

I am fortunate to work on multiple interesting projects in my graduate studies under amazing professors. Some of them are listed below:

• IoT Smart Dog Collar a system that allows users to keep an eye on their dog or pet and observe if they are accessing an area unaccompanied and interacting with the owner's belongings. Our solution would allow the user to observe the dog's state without constantly monitoring it.

• MyPack-Lite a ruby on rails full-stack web application for students' and instructors' classes and subject enrollment system. The app includes various components, i.e., Admin, Student, Instructor, Course, Enrolment, and a Waitlist System. The user can perform respective functionalities as per the role assigned.

• Door Movement Detection via IoT an inertial measurement unit (IMU) and a cloud-based machine learning system to detect door open and close events, mounted the IMU sensor to a door and used IMU readings to identify when it was closed and opened.

• Client Server File Transfer Application an FTP Server and Client architecture with ARQ schemes (Go Back N, Selective Repeat, and Stop and Wait) in Python utilizing Socket Programming. Maintained multi-threaded model to simultaneously buffer and manage the packet received and transferred, which sped up the process by 50%. Evaluated the performance of ARQ schemes by varying the Maximum Segment Size and the Window Size.

• LUNG TUBERCULOSIS DETECTION USING ANTIALIASED CONVOLUTION NEURAL NETWORKS published in INTERNATIONAL CONFERENCE ON SMART SUSTAINABLE INTELLIGENT COMPUTING AND APPLICATIONS | ICITETM-2020 ELSEVIER PROCEDIA – MARCH 2020

• PREDICTION OF CERVICAL CANCER USING CHICKEN SWARM OPTIMISATION published in INTERNATIONAL CONFERENCE OF INNOVATIVE COMPUTING AND COMMUNICATIONS SPRINGER SINGAPORE – FEBRUARY 2020

• APPLICATION OF CHICKEN SWARM OPTIMISATION IN DETECTION OF CANCER AND VIRTUAL REALITY published in ADVANCED COMPUTATIONAL INTELLIGENCE TECHNIQUE FOR VIRTUAL REALITY IN HEALTHCARE SPRINGER INTERNATIONAL PUBLISHING – JANUARY 2020

• BRAIN TUMOUR SEGMENTATION USING U-NET BASED FULLY CONVOLUTIONAL NETWORKS published in JOURNAL OF MULTI-DISCIPLINARY ENGINEERING TECHNOLOGIES GOOGLE SCHOLAR – AUGUST 2018