Amal Krishna R

Boston University
Boston,
United States

Education

Master of Science in Computer Science

Specialization: Data Analytics
Boston University ,
Boston, US

CGPA: 3.75/4

Subjects: Foundation of Analytics, Computer Language Theory, Web Analytics and Mining, Artifical Intelligence, Data Analysis and Visualization, Software Engineering, Data Mining, Cloud Computing.

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B-Tech in Avionics Engineering

Indian Institute of Space Science and Technology ,
Thiruvanathapuram, India

B-Tech Project : Software Defined MICRONet
Mentored by Prof. Manoj B.S., Ph.D.
Relevant Subjects: Wireless Mesh Networks, Computer Networks, Data Structures and DBMS, Computer Organization and Operating System, Virtual Reality, Information Theory and Coding.

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High School, AISSCE (CBSE)

St Thomas Central School ,
Thiruvanathapuram, India

Percentage : 91.2%
Subjects : English Core, Mathematics, Physics, Chemistry, Computer Science.
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Secondary School, AISSE (CBSE)

St Thomas Central School ,
Thiruvanathapuram, India

CGPA : 9.2/10
Subjects : English Comm., Mathematics, Science, Social Science, Introductory I.T, Malayalam.
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Relevant Experience

Data Analytics Intern

MetLife - Claims Advanced Analytics ,
Warwick, RI

Project - NPS Analytics deep dive
a. Prepare BI analysis of Net Promoter Score survey data-set.
b. Reformat the NPS analytics to create an ongoing data set for different types of surveys using Alterex workflow and macros.
c. Prepare an ordinal logit model to provide descriptive significance of different factors that impact NPS score.
d. Prepare a Random Forest model for predictive analytics.
e. Key-phrase extraction and sentiment analysis using Azure text analytics on customer feedback to identify key claims factors.

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Quality Assurance Intern

Boston University - BUworks ,
Boston, MA

BUworks is the Information Services & Technology (IS&T) wing of Boston University.
1. Works as a QA Intern on QA process for HR and Payroll functions and Programming team at BUworks.
2. Works with SAP & Python automation scripts for automating HR functions.

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Computer Science Tutor

Chegg Inc. ,
Remote

1. Tutor for UG students through Chegg Tutors with 95% positive rating.
2. Experience in teaching over 100+ students and 100+ lessons through the platform.
3. Teaching students Computer Science, Computer Networks, and Python/C/C++/Java Programming, and prepare them for tests and help them in solving projects and assignments.

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Software Engineering Intern

Ather Energy ,
Bengaluru, India

Ather Energy is an Indian startup headquartered in Bangalore, India. The company is a hardware startup, that is designing and manufacturing electric and connected vehicles. Ather has raised over US$45 million till date from Flipkart founders Sachin Bansal and Binny Bansal, Tiger Global and Hero MotoCorp.
1. Worked on JIRA (issue tracking software) API for Python and JavaScript to implement automation functionalities for Program management team.
2. Worked on JavaScript, NodeJS, and SailsJS to harness intelligence from JIRA data for program managers to improve the efficiency of teams.
3. Worked for the Data Intelligence team with SailsJS, REST API, ElasticSearch, Kibana, and Grafana for Data Aggregation and Visualization.
4. Experienced in the testing frameworks MochaJS in JavaScript and unittest in Python.

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Data Analytics Research Associate

Tech Mahindra ,
Hyderabad, India

1. Worked directly under UpX Academy [upxacademy.com] (an e-learning startup ventured by Tech Mahindra Growth Factories)

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Research Associate

UpX Academy ,
Hyderabad, India

Tech Mahindra Global Strategy & Growth Factories (TMGFL) is a subsidiary of the Mahindra Group which pushes newer technologies and engagement with startups. UpX Academy is an e-learning venture incubated under TMGFL for data science, big data & analytics.
1. Helped the company with capstone projects, data analytics of real-world data sets in sentiment analysis and predictive analytics using Python Anaconda distribution.
2. Developed white paper and e-books on Big data and Data analytics on emerging research areas.
3. Maintained the web admin role to ensure smooth UI experience with WordPress.

Summer Intern

Indian Institute of Space Science and Technology ,
Thiruvanathapuram, India

Project : Software Defined Delay Tolerant Network (SDDTN)
Analyzed the challenges of Software Defined Network (SDN) in a high delay environment. An Software Defined Delay Tolerant Network (SDDTN) module is deployed onto every switch using OpenFlow protocol which gets activated when there is an absence of main controller connection. The module act as a light-weight controller which generates the flow for the switch and compute the plausible locations to store the packets in the isolated network.

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Technical Skills

Strongest Areas

Cognitive Networks, Data Science/Analytics, Software Engineering (Automation)

Programming Languages

Python, R, JavaScript, Java, C++, PHP, HTML5, GNU Octave, Shell Script, VHDL & ARM

Competitive Programming

HackerRank [O(logN), Medals : 1 Gold 11 Silver 4 Bronze, Contest Score: 2096, Percentile Score : 97.6%] ,
HackerEarth [1585]

Tools/Frameworks

Anaconda(Python), NodeJS, SailsJS, SAP, HPE LoadRunner, JIRA, ElasticSearch, Kibana, GitLab, POSTMAN, Semantic-UI, Wireshark, LaTeX, MySQL, OpenGL, WordPress, RYU, Open vSwitch & OLSR daemon

Platforms

Linux, Debian & Windows

IDE

Visual Studio Code, Jupyter, Spyder, Eclipse & Netbeans

Text Editor

Geany, Gedit, Vim & Nano

Relevant Courses

Boston University:

Foundation of Analytics, Computer Language Therory, Web Analytics and Mining, Artificial Intelligence.

Indian Institute of Space Science and Technology:

Computer Networks, Wireless Mesh Networks, Data Structures and Algorithms, Virtual Reality, Computer Organization and Operating System, Information Theory and Coding.

MOOCs:

Algorithms: Design and Analysis, Part 1 (Stanford) , Machine Learning (Stanford), Cryptography I (Stanford) , Hadoop Platform and Application Framework (UC SanDiego), Python for Data Science (Microsoft)

Standardised Tests

ISAT 2012 AIR 577

among 1,50,000 candidates

KEAM 2012 Rank 686

among 1,10,000 candidates

Secured 91.2%

AISSCE 2012

CGPA 9.2

AISSE 2010

Initiatives

IEEE Student Member

Institute of Electrical and Electronics Engineers

ACM Student Member

Association for Computing Machinery

IEEE Student Volunteer

IEEE International Conference on RAICS

Finance and Creativity Head

Dhanak 2014 , Annual Cultural Festival, Indian Institute of Space Science and Technology

Creativity Head

Conscientia 2015 , Annual Astronomy and Technical Festival, Indian Institute of Space Science and Technology

Publicity Co-Head

Dhanak 2013 , Annual Cultural Festival, Indian Institute of Space Science and Technology

Web and Creativity Co-Head

Conscientia 2013 , Annual Astronomy and Technical Festival, Indian Institute of Space Science and Technology

Online Tutoring

Chegg Inc, Taught over 100+ students and took 100+ lessons through the platform in Computer Science, Computer Networks, and Python/C/C++/Java Programming.

Conferences/Workshops Attended

IEEE International Conference on RAICS

Thiruvanathapuram

Raspberry Pi Workshop

Indian Institute of Space Science and Technology, Thiruvanathrapuram

An Insight Into THz Antenna Technology

Indian Institute of Space Science and Technology, Thiruvanathrapuram

Selected Academic Projects

Boston Property Assessment (2018)

Boston property assessment dataset from Boston.gov classifies properties in greaterboston area into it’s present overall condition (Poor to Excellent). 4 classification algorithms (Naives Bayes, RandomForest, IBk and Decision Table) were modeled using 5 different selection attributes using Weka. Performance measures such as TP Rate, FP Rates, ROC Area etc were used to determine the overall performance of each classifier model.
Project page : View here

MBTA Data Visualization and Real time app (2017)

1. The project analyses the MBTA real-time data of 1 week data between Dec 1- Dec 8.
2. Advanced Data visualization of Travel times and Head way times are implemented with R and Plotly in-order to determine the problems that exist in the Boston subway lines. The Intend of doing this was to develop a weekly reporting app that can be used to determine weekly estimates of the issues that needs to be looked upon by the MBTA.
3. A real-time MBTA app is developed using R and shiny. This app also shows real-time clustering of the trains based on parameters such as subway line length, number of active trains in a direction, and the distance to the next nearest train etc.
4. The shiny app provides a simple general population facing app where anyone can keep track of the train locations with the simplest of UI.
5. The shiny app from the MBTA facing side, predicting/visualizing train clusters and giving a birds eye dashboard in each train so that the driver would be able to adjust the train speed in-order to avoid clustering. This should at-least reduce the frequency of trains going in express mode and make the waiting time for trains at stations much more uniform. Usually, the cluster keeps building up until someone from the control room calls up the driver of the specific train (as the driver is unaware that a train is following till he is contacted from the control room) to move express to certain stop.
Project page : View here

On Switch-based Controller Hand-offs in Software Defined Wireless Mesh Networks (2016)

We use Expected Transmission Time (ETT) as the metric for controller hand-off inOpenFlow WMNs. ETT reflects various physical-layer characteristics, such as link traffic and end-to-end bandwidth. The experimental results showed that ETT is a better metric compared to RTT and ETX in a dynamic network with variable load across the links. ETT-based hand-off is able to respond to the excessive load in the link and make suitable hand-off decisons, whereas RTT and ETX fails in accomplishing the same with lower hand-off delay and packet dropouts.
Paper : View here

Software Defined MICRONet (2016)

Software Defined MICRONet architecture provides intelligent communication among physical boat clusters in the sea. This will solve the technology challenges faced by the fishermen community in India today, specifically by providing software defined Intelligent and adaptable communication and connectivity while they are out at sea. A scaled down model of Software Defined MICRONet environment was emulated in a testbed.
Final Report : View here
Repository : Software Defined MICRONet (2016)

Navigation in a Virtual Environment using IMU MPU-6050 (2015)

Head Mounted Display(HMD) is one of the revolutionary Virtual Reality(VR) inventions of all times. But how do you move around in a Virtual Environment?. For a true VR experience you need to move around freely and naturally. Imagine a game where the user can freely roam around their backyard or walk on a frictionless surface and navigate in a virtual environment rather than sitting idle in a chair. Developing a low-cost system for such a VR experience which can be implemented onto a HMD, is always a challenge. In this project we have done a hardware implementation to navigate in a virtual environment using a low-cost Inertial Measurement Unit(IMU).
Repository : Navigation in a Virtual Environment using IMU MPU-6050 (2015)

32 bit RISC Microprocessor in VHDL language and implemented on Altera FPGA (2014)

Developed a 32 bit RISC Microprocessor in VHDL language and implemented on Altera FPGA. The Test bench module is executed in the model-sim software and the LCD module is implemented on the FPGA to display the Register value, Memory value and the Program counter.
Repository : 32 bit RISC Microprocessor in VHDL language and implemented on Altera FPGA (2014)

2D convolution using Xlinix of a 128*128 window and by using a 3*3 convolution matrix (2014)

For each input pixel window, the values in that window are multiplied by the convolution mask. Next, those results are added together and divided by the number of pixels in the window. This value is the output for the origin pixel of the output image for that position. The input pixel window is always the same size as the convolution mask. The output pixel is rounded to the nearest integer. The results for this algorithm carried over an entire input image will result in an output image with reduced salt-and-pepper noise. This flexibility allows for many powerful uses.

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