Assistant Software Developer

Rachith R Ramaswamy

Phone: 716-***-**** Email: ********@*******.*** LinkedIn: https://www.linkedin.com/in/rachith-ramaswamy/ Qualifications

Research Assistant and Graduate student in Data Science with 3.5 years of experience in mobile application development with proven communication and leadership skills at a major technology consumer company. Education

Master of Science, Data Science University at Buffalo, The State University of New York Aug.2019 - Dec. 2020

• Coursework: Statistical Data Mining, Machine Learning, Data Driven Analysis, Computer vision. Bachelor of Engineering Sri Jayachamarajendra College of Engineering June 2012 - May 2016

• Major: Electronics and Communications Engineering Industry Experience

Machine Learning Engineer Moto Experiences, Motorola Mobility LLC. Mar. 2018 - Aug. 2019

• Designed and built a Context Awareness Engine that employed on device machine learning to learn and adopt the phone settings based on the user location, time of the day, activity etc.

• Associated in developing a full stack Help and Feedback library which used clustering and anomaly detection to monitor device health and report user to send the diagnostics and feedback.

• Investigated various possible improvements by constantly performing Proof of Concept. Software Developer Carrier based Services, Motorola Mobility LLC Sept 2016 - Feb 2018

• Developed the AT&T Messaging Backup & Restore Service, a native messaging application with real time synchronization of SMS and MMS messages including read receipts and deletion across web and multiple devices.

• Implemented APIs as a part of Carrier Based Services to change the device settings and configurations based on the region, network provider, over the air updates with WAP messages for most of the network providers across North America and Europe.

• Mentored an intern and 3 fellow developers.

Internship Wearables (Moto 360), Motorola Mobility LLC. Jan 2016 – Aug 2016

• Designed and implemented an algorithm to learn user specific features like walk, run etc. to provide accurate results even when any of the sensor was unavailable/failed. Resulted in significant improvement in indoor distance results after few minutes of outdoor walking which was later used to conserve battery in intensive operations like marathon mode etc.

Research Experience

Research Assistant Department of Engineering Education, University at Buffalo Oct. 2019 – present

• Working as data analysis due to the impact of “Problem Typology in Communicating Engineering Experience” involving collection and analysis of data to obtain insights of the qualitative impact on the subjects after undergoing training on Problem typology and other professional competencies. Independent projects

PicSort, Face Detection, recognition and sorting (UG Course Project). Mar. 2016

• Performed research to compare/combine various methods to detect and recognize faces from a video stream.

• Added features to detect emotions like happy, grumpy, cry etc. RBOT, Smart Reply for Android Aug. 2017

• Developed an assistant to converse with the incoming messages on behalf of user by learning the user’s messaging pattern, activity and calendar schedules

Shopping Alert for Android. June 2016

• Designed and Implemented a mobile application and an AWS instance. A user could add items to shopping list and the application alerted the user when he travelled near the store where the items were available. Skills & Abilities

Programming Languages/Technologies

• Proficient in Python, NumPy, Pandas, R, SQL, Java, Kotlin and Android Application Development

• Prior experience in Android Frameworks, Image Processing, Amazon Web Services, Azure. Awards and Recognitions

Mobile Business Group Bravo Lenovo Group. Feb 2018

• Awarded the prestigious award after the on-time completion of the crucial project on the carrier-based services in a surprisingly short period of time.

Motorola International Hackathon Motorola Global. Dec 2017

• Received award for best out of the box project, by implementing a device assistant to automatically resolve device issues and respond to user quires.

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