REKHA H K .

Research (Public Datasets)
KEY PROJECTS
1. A Study for Possible Interdependency between Cognition and Aesthetics of Human Brain - (Research work/project for
MTech Dissertation) A research on fMRI data ( Neuroimaging - Big data ) - a Public Dataset from sciencedirect.com,
(https://www.sciencedirect.com/science/article/pii/S2352340921009501) is conducted to analyze the underlying
patterns of cognition activity in brain, among various subjects, along with the help of behavioral data. Generalized
Linear Model (GLM) is used to record the observations. NiLearn Python Package has been used for neuroimaging data analysis, along with Pandas, NumPy, MatPlotLib libraries.

Tasks performed as part of research include :
- Data Pre-processing, to normalize the Brain Data Set.
- Time series data - timing correction done.
- Visualization for better insight in to data.
- Data analysis and Hypothesis formation .
- Building use cases to best achieve the hypothesis.
GLM (Generalized Linear Model) Exercised on Big data.

Semester Projects [ Jan 2021 - June 2022 ]
1. Data Science Principles Analysis using Supermarket Sales Data.
2. Movie Review Dataset Analysis and study/comparison of 3 different ML feasible Models.
3. To build a predictive model to address the change for primary care physician with the Insurance Provider
dataset.
4. Bank Loan Modeling applying Bayesian Belief Networks

Gained expertise on -

• Conduct thorough exploratory data analysis to identify patterns and trends, informing project direction.
• Presented findings through clear visualizations and reports, facilitating effective communication.
• Utilized visualization and analytics tools to analyze and process complex data sets.

KEY PROJECTS:
iDRAG Utility - DELL Servers Team
Test framework development using internal tools and Python.
DriverPack Weekly Release (AGILE TOOL)

• Enhanced software functionality by identifying and resolving complex technical issues.
• Created proofs of concept for innovative new solutions.
• Analyzed work to generate logic for new systems, procedures and tests.

Power Firmware Dept., India Software Labs (ISL)
Expertise on Server hardware/architecture, Simulation engines , System Bring-up, IO chips, Virtualization/ Hypervisors, Testing.

Skills -

C * Python * OOPS * Agile

KEY PROJECTS
1. DEVELOPMENT OF SIMULATION MODELS of IBM Power Series Server hardware ( IO Chips ) using SIMICS Simulator (Utilized for the firmware bring-up) , spanning P5, P6 and P7 power processor series .

Full system (model) configuration was done using python. TCP/IP networking standards have been followed keeping
Linux Operating system technology.

Following Hardware parts were designed as part of SIMICS engine, modeled using C, PHYTHON and DML -
Host Channel Adapter -HCA – a channel adapter which stands as an interface between an end-node and a link in an
InfiniBand subnet.
Host Ethernet Adapter -HEA model was done keeping HCA as backbone, to fit in to an IO chip (P5IOC2) .
PCI-X Host Bridge - PCI switch that connects multiple PCI devices to one slot in a system.
Memory Management Unit (MMU) of IBM server IO chip - MMU provides address translation capability for different units in IO chip.MMU simulated model supported 4K to 4G page sizes.
-Distributed Virtual Ethernet Bridge (P7 Power series), Layer 2 networking connectivity between IBM blade servers of data centre network and external networks.

2. HYPERVISOR-FIRMWARE VERIFICATION - IBM P series servers
Functional Test Case ( FTC Test Cycle )/ Integration Test Case ( ITC Test Cycle ) for IBM P series servers.
Responsibilities:
-Identification of test cases for functional flow of different features of Power Hypervisor.
-Ensuring 95% coverage of entire server system with FTC/ITC Cycles

Roles and Responsibilities :

• Understanding respective Hardware architecture and Bit/Pin functionalities .
• Collaborated with cross-functional teams to deliver high-quality products on schedule.
• Improved software performance by identifying and addressing bottlenecks in the codebase.
• Performed root cause analysis on reported issues, swiftly resolving bugs while minimizing disruptions to users'' experiences.

Managed source code repositories, enforcing version control policies and facilitating efficient collaboration among team members.