
Timeline
About me
Software Engineer @MicroStrategy. Cloud | AWS | GCP| Kubernetes| Genomics
Education

Pune institute of computer technology
2015 - 2019Bachelor of engineering - be computer engineering cgpa: 9.51
Virginia tech
2019 - 2021Master's degree computer science
Fergusson college
2013 - 2015Hsc12th Science
Experience

Persistent systems
May 2017 - Jul 2017InternWorked on Web Development and Persistent Artificial Intelligence platform. Successfully Implemented POC right from SRS to Automated Testing and successfully coordinated in the software engineering process. Learnt and implemented REST API'sSkills learnt : Software Engineering, PHP, Drupal, Python, Selenium, MySQL, AIML, XML,REST

Prescient technologies
Jun 2018 - Jun 2019Project internOur solution aims at detecting suspended impurities and foreign objects in beverages. We are working specifically on buttermilk for quality detection and assurance with the help of computer vision and sensors, which will act as a contact-free technology for foreign object detection. The data (images of bottles on the assembly line and that gathered from the sensors) is collected and classified for further QA using Deep Learning.

Periwinkle technologies pvt. ltd.
Jun 2018 - Sept 2018InternI worked on the Machine Learning and Computer Vision aspects of a live project, ‘Smart Scope™’. It involved software development for the detection of cervical cancer at an early stage with the help of images taken by doctors. Abnormalities like cervicitis could also be detected at early stages. Specifically, I built the algorithm required for cervix segmentation and examined the applicability of transfer learning for solving the given problem. I also deployed the ML platform on Amazon Web Services. In a resource-constrained country like India, the application enables remote screening of cervical cancer and provides real time diagnosis for prompt action. The Government of India has also shown a keen interest in the application and provided sponsorship for the same. Show less

Virginia tech
Aug 2019 - May 20211. Worked on the development of a ML model DeepARG+ that predicts antibiotic resistance from large scale genomic data. Paper to be published in a high impact factor journal 2. Led a team on NSF funded project CI-WARS for creating a pipeline for end to end resistance analysis3. Developed a visualization tool in D3.js for anomaly detection for monitoring antibiotic resistance.Advisor: Dr. Liqing Zhang CS1114 Statistics for Social Sciences Course
Graduate Research Assistant
May 2020 - May 2021Graduate Teaching Assistant
Dec 2019 - May 2020Graduate Teaching Assistant
Aug 2019 - Dec 2019

Microstrategy
Jun 2021 - nowSoftware engineer
Licenses & Certifications
- View certificate

Nlp - natural language processing with python
UdemyJul 2019 - View certificate

Intro to python for data science course
DatacampAug 2017 - View certificate

Associate cloud engineer
Google cloudOct 2023 - View certificate

A gentle introduction to deep learning using keras
UdemyJan 2018 - View certificate

Kaggle python tutorial on machine learning course
DatacampSept 2017 - View certificate

Bootstrap 4 quick start: code modern responsive websites
UdemyDec 2016 - View certificate

Ckad: certified kubernetes application developer
The linux foundationJan 2022
Honors & Awards
- Awarded to Rutwik KulkarniWinner Smart India Hackathon 2019 - March 1, 2019
- Awarded to Rutwik KulkarniDepartment Topper (Third year engineering) PICT July 1, 2018 Rank 2 in the Computer Engineering Department of 320
- Awarded to Rutwik KulkarniTech Mahindra Iris Hackathon Tech Mahindra Jun 2018 Bad Debts are normally due to disbursement of loans to customer who look good on paper, or the loan evaluation officer misses out on certain flags and hence passes the loan. By using an Artificial Neural Network trained to determine these bad debts on past data with financial and non financial input vectors, we can reject potential bad customers or flag and monitor already provisioned high risk loans so that bad debts can be predicted in advance and hence do not get converted into Non… Show more Bad Debts are normally due to disbursement of loans to customer who look good on paper, or the loan evaluation officer misses out on certain flags and hence passes the loan. By using an Artificial Neural Network trained to determine these bad debts on past data with financial and non financial input vectors, we can reject potential bad customers or flag and monitor already provisioned high risk loans so that bad debts can be predicted in advance and hence do not get converted into Non Performing Assets. Show less
- Awarded to Rutwik KulkarniDepartment Topper (Second year engineering) PICT July 1, 2017 Rank 5 in the Computer Engineering Department of 320
Languages
- enEnglish
- hiHindi
- maMarathi
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