I conducted a self defence workshop for women. I managed a crowd of more than 50 women and assisted them in learning self defence moves for extreme emergency situations. It was a highly successful unprecedented event in my college, geared towards helping women combat real world violence issues.
I was a part of a student chapter of the department of Computer Engineering named DJACM which was associated to ACM (Association for Computing Machinery). I was incharge of coordinating and monitoring the storage and supply of goods, also ensuring premises, assets and communication is used effectively to optimize the working of the organization.
I am currently pursuing my Masters in Science with majors in Computer Science. My concentration is Data Science. My current GPA is 4.0. My coursework includes Algorithms and Data Structures, Database Systems, Machine Learning, Cloud Computing, Computer Graphics and Computer Networks.
I am a Bachelor of Engineering from Mumbai University with majors in Computer Engineering. During my four years I have made projects in the fields of Data Manipulation, Computer Networks, Database Systems, Machine Learning, Operating Systems etc. My GPA in this course was 7.57/10.0.
See my Projects under the field of Machine Learning, Software Development and many more.
Well, I'm more than just academics.
I'm a professional Karateka,
Black Belt since 2009.
Besides, I have basic level skills in
Krav Maga and
Brazilian Jiu Jitsu.
I like to watch
and play sports like
Cricket, Soccer, Tennis, Badminton, Swimming, Table tennis.
Indian Cricket Team,
Manchester United
for life 💗.
Coding has been my past
time in the last few years.
I also have interest in learning new languages for programming and work on them. But, yes, Python is the best
language hands down.
I am a regular blood donor.
Been a member of Indian Development Foundation,
a national NGO committed to
health, education and development,
in 2015.
Want to know something more about me? Feel free to contact me.
Field: Machine Learning.
Time Span: February 2019 - May 2019.
- In this project, the data is collected from Twitter and News. This data is then pre-processed, after which Semantic Analysis is done on it and a positive, negative, neutral and compound score is calculated. Then this data, with the information of stocks is passed to our training model. The model consists of LSTM (Long-Short Term Memory) and ANN(Artificial Neural Network). After training the model it is tested of the initially split test data and the results are then evaluated.
- Performed web crawling using a python script and ‘BeautifulSoup’ library to collect news from ‘businesstimes.com’ and ‘tweepy’ library to collect Twitter data. Sentiment Intensity Analyzer was used to get the negative, positive, neutral, compound scores of the content.
- The hyperparameters of the network such as weight, bias, learning rate, etc, play an important role in the prediction of the target variable, a Genetic Algorithm is induced in to the LSTM model to optimize the model and select best hyper-parameters for the given model and training dataset. Genetic Algorithm computes the fitness score of the initial random population(weights and bias) to select the hyperparameters over which crossover and mutation are performed till the population converges and we get the fittest hyperparameters.
Field: Data Extraction
Time Span: July 2017 - March 2018.
- The project investigates the real-time interaction of events such as earthquakes, in Twitter, and proposes an algorithm to monitor tweets and to detect a target event. K-means classifier is used based on features such as the keywords in a tweet, the number of words, and their context. Each Twitter user is considered as a sensor and then Kalman filtering and Particle filtering is used, which are widely used for location estimation
- By using distributing computation and data aggregation technique on the discrete signals as a new representation of the original data, we extract and track real social events on Social Data Stream. After detecting the events we notify the users using an app on the mobile which will help the nearby people to save themselves from any damage.
- To detect the authenticity of the tweets we have planned to consider the frequency of tweets. Additionally, we also take into consideration the number of tweets coming from a particular area, typically from the area affected from event or the areas in the vicinity.
- Firebase Cloud Messaging (FCM) is used to notify users in real-time via a text message. FCM offers a broad range of messaging options and capabilities.
Field: Computer Graphics
Time Span: October 2018 - December 2018.
- A college building is used to demonstrate the navigation. There are two floors with 4 classrooms on each floor. To navigate through the corridors there are doors at the start of each corridor. To go the next floor (or previous floor) lifts have been installed at two positions one each to go up and go down respectively.
- A hierarchical rendering strategy was employed in a simplistic manner to tag every quad polygon to belong to certain categories. Each quad can belong to one of 4 corridor categories. One color texture panel was created to encapsulate all the necessary texture images.
- The whole project was made by using WebGL tool with core coding in Javascript.
Field: Computer Networks.
Time Span: March 2019.
- A client sends an HTTP request to a server in the form of a request message, with a header and a message body containing the payload. Then, a server responds to a client's request by sending one or more HTTP response messages
- The server is able to handle multiple simultaneous service requests in parallel. This means that the Web server is multi-threaded. A threaded web server is one that handles each request with a new thread, as opposed to handling each request with a new process. Multi-threading is more complex than concurrency with processes, so there's an increased risk of the web server crashing if one of its modules isn't working correctly.
- The project was implemented on Python and initiated by using Command Line arguments.
Field: Web Development
Time Span: March 2018.
- This website was built for the Martial Arts club of my college. It was a part of my course in Human Computer Interaction.
- This website demonstrates the details which every human pays attention to while browsing through the internet, for example, what shapes and colors draws attention. Also, what designs are more visually appealing.
- This website was made by using the following languages: HTML5, CSS, Bootstrap, Javascript