Sep 2018 – May 2020 · 1 yr 8 mos · Bangalore

May 2017 – Jul 2017 · 2 mos · State College, Pennsylvania, USA

• Research on "Speech deterioration in Alzheimer's Disease". I collected speeches and literary articles of politicians, author and other celebrities who had Alzheimer's. I applied Machine Learning Algorithms to these texts to help the machine learn about the statistical trends in the speeches of these celebrities over the years of their life. The deterioration can be in the form of loss in memory resulting in stammering speeches. or increased used of fillers, or increased used of pronouns or some trend in the use of the various parts of speeches etc. Several features were extracted from the texts collected. These features were fed to the machine to build the model. This helped us in classifying the celebrities into Alzheimer's group and Non- Alzheimer's group.
• Tool used- Weka.

May 2016 – Jul 2016 · 2 mos · Kolkata Area, India

• Extracted tweets on various Indian airlines from Twitter using R and mined the data so as to analyse the sentiment of the passengers which can be positive, negative or neutral. Also judged the profit or loss of a particular airline company during a given time span by plotting Histogram from the responses obtained from the extracted tweets. Then the analysis of sentiment of the passengers using entity level analysis was performed. Entities such as food, hospitality, timings, etc were analysed separately. Designed the entire tool for the above task using R.

May 2016 – Jun 2016 · 1 mo · Kharagpur Area, India

• Checked two Finite State Machine with Data Path(FSMD) for equivalence using two processes- Path extension and Value propagation. Value propagation was proved better than path extension. Certain algorithmic modifications were made in the value propagation method as it showed wrong results for some test cases. Studied Normalised Sums and implemented in Haskell Programming language.

Jan 2016 – May 2016 · 4 mos · Durgapur Area, India

• Scheduled the tasks uploaded by the ground control station to the satellite so as to maximise the profit and keeping in mind the constraints of energy, memory and duration available. There are several works that were done previously on off-board satellite scheduling tasks where the ground station would schedule the tasks and upload to the satellite without knowing the energy or memory constraints of the satellite. In this work the scheduling was done by the satellite itself keeping the constraints in mind using Particle Swarm Optimisation(PSO) algorithm and the code was written in python.