Majored in Computer Science. During the course of study, I was activley involved with startups incubated at Manipal, participated in hackthons and volunteer work.

CGPA: 3.61/4.00
Activites

• Representative of Google Students Team, Manipal.
• Web Development Team Head at Tech-Tatva ‘15.
• System Administrator at Tech-Tatva ‘14, official Tech Fest of Manipal.
• Core committee member IEEE, Manipal.

Courses
Artificial Intelligence, Intro to Machine Learning, Digital Image Processing, Operating Systems, Networks and Distributed Systems, Formal Language and Automata Theory, Principles of Software Engineering etc.

Conference:
IEEE International Conference on Trends in Automation, Communication and Computing Technologies
Date:
Dec 21, 2015
Abstract:
The paper focuses on comparing the performances of two machine learning algorithms - Decision Trees and Random Forests. Through the course of the paper, a comparison is made of classification results of these two algorithms, for classifying data sets obtained from Kaggle's Bike Sharing System and Titanic problem. The paper concludes that for all classification problems Decision Trees is handy with small data sets i.e. less number of instances and Random Forests gives better results for the same number of attributes and large data sets i.e. with greater number of instances.

Conference:
IEEE International Conference on Electrical,Computer and Communication Technologies 2015
Date:
Mar 7, 2015
Abstract:
Efficiency and thrust output of an Aero Engine have a huge bearing and vary drastically based on the ambient conditions at airports. The amount of these variations greatly affects thrust, fuel consumption, surge margins, temperature management across the cross section of the gas turbine fluid flow path. Data mining techniques have been used in the aeronautical industry for many years and have been known to be effective. In order to solve problems such as, this study concentrates on building a hybrid methodology, combining data mining techniques such as association rules and classification trees for creating patterns to aid in better performance management of aero engines. The methodology is applied to real-world parameters data collected from Forecast Systems Laboratory Radiosonde Database and the results are evaluated by comparing them with other techniques. The performance of the aero engine and in turn the airplane is accounted by analyzing various parameters like Pressure, Temperature, Wind direction and Wind Speed at different altitudes of the aircraft as it takes off and lands at the airports. This methodology is expected to help Aeronautical Engineers to make a faster and more accurate prediction of the aero engines and aero planes performance.

Journal:
International Journal of Engineering Research and Technology
Date:
May 17, 2014
Abstract:
In today’s world of ever increasing amounts of information, hospitals and medical groups must continually find ways to manage the myriad information that is gathered on patients. MED+YOU not only helps to manage this myriad patient information, but it also educates patients about health information technologies so that they are in a better position to monitor their health, attain desired health goals and manage their health services. MED+YOU also possesses several facets which include self-management of health, patient doctor communication, improvement of health awareness and outcomes, patient satisfaction with their healthcare provider and assessment of accessibility and usability factors of the personal health records. Subsequently, the MED+YOU improve sustainability and efficiency of patient-centered care to be provided among healthcare networks and clinic partners throughout the globe. MED+YOU would function as a universal portal where a person would have his or her own profile with a login ID and a password. It will also contain a home page where information about health and related issues keep getting updated. We also get to form groups and follow health related pages and people with similar problems.