As Naturally, I chose to specialize in electronics

As a young kid, I was fascinated by electronic gadgets and dreamt of building an electronic gadget by myself someday. Naturally, I chose to specialize in electronics during my high school. The coursework included an intricate study on utility and functioning of hardware parts such as switches, transistors, amplifiers etc. However, it did not focus much on the programming aspect and thus felt very sectional. So, I chose to pursue Information Science in UVCE, which has the reputation of being the first engineering college in Karnataka.

During my study at UVCE, I got a chance to expand my horizons in the field of computing. Operating systems was one of my favorite subjects and it was intriguing to know how a simple swap function, when made atomic, could solve the race condition, one of the most complex problems in Operating Systems. In my sophomore year, I had an opportunity to intern at National Aeronautics Limited where I learned about prognostics and diagnostics in aircraft systems. I also became aware of neural nets and algorithms such as wavelets and petrinets. During this period, I also implemented a color changing, flying dragon as a part of a mini-project in computer graphics. I was also introduced to Web Development and I got my feet wet by implementing my first Web-based Application “Gas Agency Management System” using the Model-View-Controller approach using Html, CSS, PHP and MySQL database. Following which, I implemented yet another project, ‘Online Mail Order’ based on the same approach.

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In my senior year, I and a few of my cohorts executed a project where we implemented an algorithm to seamlessly share photos on the cloud. We first encrypted each photo to be shared using a unique key and then aggregated these different keys into one single aggregate key shareable over the cloud. Using the decryption algorithm and the shared aggregate key, we managed to extract the original keys with which these photos were encrypted. The entire project was developed using Java and third-party cloud platform.

Outside of academics, I am an avid badminton player. I successfully represented my college in badminton game during the Bangalore University tournaments and won the badminton championships in the two annual fests conducted by our college. I have always had a thirst for travel and I have traveled to thirteen countries including the United States of America. I also have a penchant for going on motorcycle rides. I am a runner and I frequently participate in marathons conducted in my city.

In my final year, I was placed in Nokia Networks Pvt Ltd, as an R&D Engineer. My first project here was ‘Nokia Wi-Fi’ which comprised of a Cloud Wireless Controller and Nokia Access Points. The project aimed at offloading traffic from the Base Station in densely populated areas such as Times Square or an Olympics event where the number of users per unit area is often very high. During the project, I extensively worked on the High Availability feature of the Cloud Wireless Controller and I was exposed to the power of cloud computing through the OpenStack framework. I was amazed at the flexibility, computing capability and robustness provided by cloud coupled with a lower cost per byte.

 

 

 

The High availability was a feature which targeted at solving virtual machine failures and enabled almost zero downtime of the system during these failures. During this project, I worked mostly on C++ and wrote shell scripts to support the High Availability configuration on our nodes. My efforts on the project were tremendously appreciated and I was awarded ‘Achievement: Excellent contribution to WIFI16 release’.

Recognizing my drive to implement new things, my manager provided me an opportunity to develop an SCT framework which removed the hardware dependency in the core network for 2G. This was one of the best teams I have worked with, being a novice at TTCN-3, the entire team was able to adapt very quickly and delivered more than what was needed for the project. This work drew the attention of our Product Management Team in Finland, who recognized our team with ‘Business Excellence MN Quality First award’ in the category of ‘Breakthrough’.

Following this, I was recommended to join the 5G Team in Bangalore. Here, I was asked to work for the L2NRT (Layer2 Non-Real-Time) team for implementing “256 QAM support for Nokia’s Non-Stand-Alone deployment of 5G” in the L2 layer. This feature was developed purely in C++ and after completing this task, I was assigned to another team which was responsible for developing “50 MHz bandwidth support for mm Waves” feature. During the implementation of this feature, I was required to study more about the L2 layer scheduling. During this study, I understood that spectrum is a very precious resource and use of the allocated spectrum efficiently is the key differentiator for networking companies.

To use the spectrum efficiently, the base station (GNB) must allocate spectral resources efficiently. This allocation is based on a myriad of parameters such as timing advance, channel condition, number of users supported in a cell, bandwidth, Quality of Service requirement, handovers, profitability etc. With the advent of IOT (Internet of Things), we expect at least a billion devices to be connected to the internet by 2020. With such large number of devices getting connected, the base station must not only be able to handle huge data but take data-driven decisions with minimal latency. This is a challenge which I believe can be addressed using data mining and machine learning tools and thus creating the need to develop specialization on the same.

The MS in Computer Science:  Data mining and machine learning at Arizona State University is a program that matches my academic goals and career aspirations. All the course requirements and electives are focused on data, making it a comprehensive learning experience in data mining and machine learning. Browsing through ASU’s website, I was excited to find out that these areas incidentally happen to be the major research areas in the university. I am confident that the excellent faculty coupled with the state-of-the-art research facilities would help me grow better in all aspects. I thank you for considering my application and hope that with my strong academic records and industry experience, ASU finds me a competent candidate for the M.S program.

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