Sukumar Bisetty Research Profile

About

Sukumar Bisetty is a highly experienced IT professional with 18 years in design, development, maintenance, and production support of applications, specializing in AS400 development, SAP MM functional analysis, SAP Ariba consulting, and Celonis analysis. His expertise spans various industry domains including Retail, Healthcare, Manufacturing, Finance, Logistics, and Wholesale. Bisetty has a proven track record of successfully implementing and supporting SAP systems, particularly in the MM (Materials Management) module, and has also worked extensively with AS400 legacy systems. He possesses deep knowledge of the full software development lifecycle (SDLC), from requirements gathering and gap analysis to configuration, testing, implementation, and post-implementation support. His SAP skills include configuring purchasing documents (RFQs, contracts, purchase orders), setting up release procedures, managing master data (material and vendor), configuring pricing and output determination, and integrating MM with SD and FI modules. He is proficient in using SAP Solution Manager for configuration management and transport request tracking. Bisetty has experience in preparing blueprint documents for SAP implementations in validated environments (FDA regulated), utilizing RICEF methodology to create user requirement specifications (URS) and functional specifications (FS). He is adept at resolving functional issues using tools like JIRA/QC and maintaining documentation in Confluence. He has also led end-to-end testing efforts, including functional, technical, and performance testing, and has experience in training end-users on procurement processes. His AS400 expertise encompasses programming in RPG II, RPG III, RPG IV (ILE), COBOL 400, CL, and DB2/400, using tools like QUERY, stored procedures, and SQL/400. He has experience in robot scripting for scheduling AS400 and SAP jobs, and has provided production support for over 9 years. Bisetty's retail experience includes functional knowledge of retail architecture, item processing, promotions, price changes, BOL, inventory, and logistics. In healthcare, he has experience with adjudication and 837/835 claims testing. He has demonstrated leadership skills in managing teams, both onshore and offshore, and has experience in business process management, requirements gathering, and project planning. He is a strong communicator and problem-solver, with experience in troubleshooting, debugging, and providing technical specifications to ABAP programmers. His career progression includes roles as SAP Functional Analyst at Mohawk Industries, where he performed feasibility studies, gap analysis, master data conversion, and configuration; Project Lead at Cigna, where he managed multiple applications and oversaw batch processing and issue resolution; Project Lead and Analyst at CareCentrix, where he focused on functional testing and team leadership; and various roles at Pfizer, Delphi, and Mattel-Europe, where he gained experience in AS400 development, application support, and client interaction. He holds a Master's in Computer Application and a Bachelor of Computer Science.

Skills

Experience

SAP Functional Consultant

Mohawk Industries Inc

Aug-2017 to Present

Project Lead and Analyst

CareCentrix

Aug-2010 to Mar-2013

Project Manager

Cognizant, USA

Jan-2011 to Aug-2017

Project Lead

Cigna HealthCare, Raleigh

Mar-2013 to Aug-2017

Team Lead and Analyst

Pfizer Inc, Chennai

May-2008 to Apr-2010

Education

University of Madras

MCA in Computer Application

Passout Year: 2004

Andhra University (AU)

B.Sc. in Electronics and Computers

Passout Year: 2000

Peer-Reviewed Articles

Internal and External Re-keying and the way forward

Side Channel Analysis are the security attacks due to the issues in the implementations. This attack bypasses the mathematical security provided by the cryptographic algorithms. These attacks are broadly categorized into the issues related to architectural of the chip manufacturing, attack due to unwanted leakages like power leakage, acoustic leakage, thermal leakage or electromagnetic leakages, and the issues due to programming vulnerabilities for example the heartbleed bug etc. The architectural related issues are fixed when the newer version of hardware is designed once the vulnerability is found in the earlier version. The programming related attacks are solved by patching the software and updating the code that caused the vulnerability to be exploited. The leakage issues are the ongoing issues since it was first discovered in 1997. Among the various leakage issues, the acoustic and thermal leakages aids in the attack related to power analysis. The Electromagnetic attack boils down to the power analysis issue and hence, it all comes down to the power analysis attack. Since it was discovered, the researchers have suggested the solutions for them but on the other side, they would also be vulnerable again. The Power analysis attacks are mainly classified into Simple Power Analysis (SPA), Differential Power Analysis (DPA), Correlation Power Analysis (CPA), and profiled attacks. Their countermeasures are mainly masking and rekeying apart from architectural changes. The masking has been researched extensively and have been widely implemented countermeasure. However, it comes with a very big overhead. Therefore, the researchers started exploring the rekeying to counter them. Rekeying has been classified mainly into the internal and external rekeying both having its advantages and disadvantages. There is currently no literature available that discusses both in detail. This work surveys the work on both the approaches and suggest the way forward for the researchers of the re-keying.

DEVELOPING A DATA-DRIVEN ARCHITECTURE FOR IMPLEMENTING AI-ENABLED DYNAMIC PRICING STRATEGIES IN THE AUTOMOTIVE INDUSTRY

In the Automotive Industry, dynamic pricing is used a lot to make the most money and hold off the competition. The Automotive industry is using AI to build a data-centric framework that will allow dynamic pricing. This research will look at how they are doing it. Automakers can find out about how customers act, how the market is changing, and how competitors plan to beat them by using complicated formulas and strict data collection methods. The aim of this research is to analyze how dynamic pricing protects prices in various industries, with a particular focus on its application in the automotive industry. In addition, the research will discuss about data-driven design approaches incorporating with artificial intelligence (AI), mainly how these technologies could be used to improve pricing strategies by automating choices and letting prices adjust based on the market. Important things like how to use market trends to our advantage, gather and analyze data, and understand how customers behave, and merchandise sales are the focus areas of the paper. As part of the project, AI could also be used to improve pricing methods. Some of these are prediction analytics, machine learning, and reinforcement learning. We can figure out how to make the most money and guess what prices will be in the future by using algorithms that look at past price data. Finally, the study shows that price strategies that are driven by AI and design that is driven by data can have a big impact on the automotive industry. Businesses in the Automotive industry might be able to boost competition, new ideas, and customer trust by using dynamic pricing systems and staying honest all the way through.

Scholar9 Profile ID

S9-112024-1206393

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Mr. Sukumar Bisetty