Timeline

Institution/Company	Time	Brief
Arizona State University	2023 - 2025	Masters Degree in Computer Science 📖
Digital.ai	2022 - 2023	Grew significantly as a Software Engineer 🖥️
FlexiEle Consulting Services Gurgaon, India	2021	Briefly worked on people management software. 👮
Standard Chartered GBS	2020	Summer Intern ☀️
OSPF, NIAS, IISc., Bangalore	2019	Machine Learning on Medical Datasets 💊
National Institute of Technology, Karnataka	2017 - 2021	Bachelors Degree in Computer Science Engineering 💻

Education

• Master of Science, Computer Science, Arizona State University, 2023-2025
  • Courses: Frontiers in Generative AI, Knowledge Representation and Reasoning, Data Mining, Data Visualization, Distributed Database Systems, Multimedia and Web Databases, Engineering Blockchain Applications, Information Assurance and Security, Software Requirements and Specifications
• Bachelors in Technology, Computer Science Engineering, National Institute of Technology Karnataka, Surathkal, 2017-2021
  • Activities and societies: Executive Member at IEEE NITK (Taught Freshmen Linux Terminal Commands and Linux Installation Guide) and Media and Publicity Head at Web Enthusiasts’ Club NITK (Conducted Several Tech and Programming Events).

Work experience

Digital.ai Bangalore, India, Software Development Engineer, Jul 2022 - Jul 2023

• Technologies: Apache Kafka, Spark, Airflow, Kubernetes, Docker, Snowflake, Redshift, Lambda, EKS, Amazon Web Services, Spring Boot, Java, Python
• Jenkins to Kubernetes: Engineered and deployed Kubernetes Workloads for ’Clean Tenant’ and ’Replicate Data’ operations, achieved deployment efficiency, better resource utilization, reduction in response time during peak demand, contributed to a decrease in cloud infrastructure costs of 12,000 dollars annually.
• Data Pipeline Engineering and Source Integration: Successfully engineered and deployed comprehensive data pipelines, integrating dynamic sources such as GitHub, Snowflake, and New Relic, to significantly amplify business functionalities. Utilized the Adapter Framework (an internal data pipeline tool) to enhance data extraction and loading processes (ETL), achieving an improvement in processing efficiency. This strategic initiative played a key role in increasing the customer onboarding rate by significant percentage, leading to the addition of new key clients within a single quarter.
• Streamlined AWS Lambda Build and Deployment Automation: Orchestrated the automated build and deployment of AWS Lambda functions Conducted a meticulous evaluation of strategies for developing and deploying Lambda functions, pivotal in enabling email alerts and event logging from Apache Airflow . Devised a robust protocol, employing Docker and AWS S3, to facilitate the build and deployment of these Lambda functions. Subsequently, established an automated mechanism utilizing Jenkins for the seamless deployment of AWS Lambda functions.
• Application Control Plane Enhancement and Database Automation: Wrote a database automation script as a part of the ACP. Streamlined and automated diverse database functions within the customer Single Sign-On ecosystem. Completely revamped the front end of the Application Control Plane by rebranding it from scratch and optimizing it by adding several forms and other features tailored to distinct customer categories and accounts, expanding their access to a variety of applications.

FlexiEle Consulting Services Gurgaon, India, Software Developer Engineer, May 2021 - June 2022

• Technologies: MySQL, Angular, NodeJS, APIs, RsJS, JavaScript**
• Human Resources Management System: Enhanced the onboarding front end by adding several functionalities to the screen, Implementation of RxJS, REGEX addon on Angular, RESTful API’s Implementation from Front to Back, Nodejs development for Services and API’s, Implementation of UI components using ngx-bootstrap, Implementation of UI/UX components using prime-ng.

Standard Chartered GBS Chennai, India, Summer 2020: Summer Research Intern, May 2020 - July 2020

• Technologies: NLTK library, Python, PyTorch, Pandas, Matplotlib, Numpy.
• Worked on a Natural Language Processing Project to Organize Banking data provided: Worked with multiple teams to gather real time banking data and helped organize them to analyze business transactions needed for the analysis. Used plotting software to visualize data in a convenient manner.

Summer 2019: Summer Research Intern, May 2019 - August 2019

• OSPF Drug Discovery Lab, NIAS, Indian Institute of Science Bangalore, India
• Mentor: Dr Jaleel UC (Principal Scientist), OSPF Drug Discovery Lab, NIAS, IISc. Deep Learning Project at OSPF Lab in collaboration with TDU, Bangalore.
• Unsupervised Deep Learning Analysis with Kohonen Self-Organizing Maps: Exploration of Kohonen Self-Organizing Maps for Medical Data Insights Engaged in the application of Unsupervised Deep Learning methods to decipher intricate relationships among diagnostic parameters within a medical dataset. Specialized in Kohonen self-organizing maps, a neural network architecture renowned for competitive learning, enabling the unsupervised clustering of data. Acquired proficiency in Vector Quantization and other competitive learning techniques, pertinent to the realm of unsupervised learning. Employed R as the principal tool to actualize self-organizing Kohonen maps, subsequently visualizing multifaceted components of the derived map.
• Academic Conference Volunteering: Was part of the organising committee of the United Kingdom-India Meet on Emerging Innovations in AMR (Anti-Microbial Research) held on 7th June 2019 at National Institue of Advanced Studies, IISc.

Fall 2018: Research Associate, August 2018 - July 2019

• Computer Science Department, National Institute of Technology, Karnataka Surathkal, India
• Cloud Computing, Concurrent Programming Parallel programming Lab.: Advised by Christina Joseph and John M, PhD Scholars CSE Dept. NITK.
• Concurrency Analysis between Golang and Java: Successfully presented paper at 2020 5th International Conference on Computing, Communication and Security (ICCCS): Click Here . Within this study, we undertake an in-depth evaluation of the concurrency attributes inherent in Go and Java programming languages. This comprehensive analysis encompasses compile time, run time, binary sizes, as well as the distinctive concurrency capabilities of each language. Our investigation involves the empirical exploration of matrix multiplication and PageRank algorithms, serving as experimental grounds for rigorous comparison. By building upon the foundation laid by N Togashi and V Klyuev in their 2014 paper, we propose an enriched methodology, introducing advanced algorithms such as PageRank to augment the scope and depth of testing and analysis.

Skills

• Programming Languages: C, C++, Java, Python, Go, JavaScript, R
• Frameworks/Tools:
  • Programming Frameworks: Spring Boot
  • DevOps: Docker, Kubernetes, Linux
  • Data Engineering: Apache Kafka, Spark, Airflow
  • Machine Learning: PyTorch, Tensorflow, Numpy, Pandas, Matplotlib
  • Web Developement: Express, Node.js, Angular, React.js
  • Cloud: AWS

Talks

Teaching

Instructional Assistant for CSE 548: Advanced Computer Networks (Summer 2024)