“Worked with Reetika at ADF and she has been an amazing teammate. She grasps things fast and is a quick learner. It was very easy to explain anything to her and get it done. Besides clear understanding of predictive models and the associated algorithms, her coding skills and database expertise were exceptional and she could easily come up with quick analysis and insights from huge chunks of data. Uber committed and determined and an exceptional team player, always ready to offer help and suggestions. All the best Reetika for your MS. Keep up the good work and your passion.”
About
Activity
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Just finished the learning path “Career Essentials in Generative AI by Microsoft and LinkedIn”! #computerethics
Just finished the learning path “Career Essentials in Generative AI by Microsoft and LinkedIn”! #computerethics
Liked by Reetika Roy
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I have recently received my Australian Citizenship in the City of Melbourne. I have arrived in Australia in 2019 as an International Student to study…
I have recently received my Australian Citizenship in the City of Melbourne. I have arrived in Australia in 2019 as an International Student to study…
Liked by Reetika Roy
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Happy 4th of July! 🇺🇸 At Sumo Logic, we're celebrating freedom and innovation. As we honor this day, let's continue to create strong partnerships…
Happy 4th of July! 🇺🇸 At Sumo Logic, we're celebrating freedom and innovation. As we honor this day, let's continue to create strong partnerships…
Liked by Reetika Roy
Experience & Education
Publications
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Estimating Heating Load in Buildings using Multivariate Adaptive Regression Splines, Extreme Learning Machine, a Hybrid Model of MARS and ELM
Renewable & Sustainable Energy, Elsevier
Heating load and cooling forecasting are essential for estimating energy consumption, and consequently, helping engineers in improving the energy performance right from the design phase of buildings. The capacity of heating ventilation and air-conditioning system of the building contributes to the operation cost. Moreover, building being one of the sectors with heavy energy use, it is required to develop an accurate model for energy forecasting of building and constructing energy-efficient…
Heating load and cooling forecasting are essential for estimating energy consumption, and consequently, helping engineers in improving the energy performance right from the design phase of buildings. The capacity of heating ventilation and air-conditioning system of the building contributes to the operation cost. Moreover, building being one of the sectors with heavy energy use, it is required to develop an accurate model for energy forecasting of building and constructing energy-efficient buildings. This paper explores different machine learning techniques for predicting the heating load and cooling load of residential buildings. Among these methods, we focus on advanced techniques like Multivariate Adaptive Regression Splines (MARS), Extreme Learning Machine (ELM) and a hybrid model of MARS and ELM along with a comparison of the results with those of more conventional methods like linear regression, neural network, Gaussian processes and Radial Basis Function Network. The MARS model is a non-parametric regression model that splits the data and fits each interval into a basis function and ELM is similar to a Single Layer Feed-forward Neural Network except that in ELM randomly assigned input weights are not updated. As an improvement, we have tried a hybrid model that uses MARS to evaluate the importance of every parameter in the prediction and these important parameters have been fed to the ELM to build hybrid model and it can be seen that this boosts the ELM performance to match up to the accuracy of MARS with lesser computation time. Finally, a comparative study examines the performances of the different techniques by measuring different performance metrics.
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Prediction of Customer Satisfaction using Naive Bayes, MultiClass Classifier, K-Star and IBK
Soft Computing Applications. SOFA 2016. Advances in Intelligent Systems and Computing, vol 634. Springer
Customer satisfaction is an important term in business as well as marketing as it surely indicates how well the customer expectations have been met with by the product or the service. Thus a good prediction model for customer satisfaction can help any organization make better decisions with respect to its services and work in a more informed matter to improvise on the same. The problem considered in this study is optimization of customer satisfaction for the customers of San Francisco…
Customer satisfaction is an important term in business as well as marketing as it surely indicates how well the customer expectations have been met with by the product or the service. Thus a good prediction model for customer satisfaction can help any organization make better decisions with respect to its services and work in a more informed matter to improvise on the same. The problem considered in this study is optimization of customer satisfaction for the customers of San Francisco International Airport. This paper adopts three classification models Naive Bayes, MultiClass Classifier, K-Star and IBK as potential classifiers for prediction of customer satisfaction. The customer satisfaction depends on various factors. The factors which we consider are the user ratings for artwork and exhibitions, restaurants, variety stores, concessions, signage, directions inside SFO, information booths near baggage claim and departure, Wi-Fi, parking facilities, walkways, air train and an overall rating for the airport services. The ratings are obtained from a detailed customer survey conducted by the mentioned airport in 2015. The original survey focused on questions including airlines, destination airport, delays of flights, conveyance to and from the airport, security/immigration etc. but our study focuses on the previously mentioned questions. Graphs are plotted for actual and predicted values and compared to find the least amount of deviation from the actual values. The model which shows least deviation from actual values is considered optimal for the above mentioned problem.
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Spam Email Detection Using Deep Support Vector Machine, Support Vector Machine And Artificial Neural Network
Soft Computing Applications. SOFA 2016. Advances in Intelligent Systems and Computing, vol 634. Springer
Emails are a very important part of our life today for information sharing. It is used for both personal communication as well as business purposes. But the internet also opens up the prospect of an enormous amount of junk and useless information which overwhelms and irritates us. These unnecessary and unsolicited emails are what comprise of spam. This study presents the application of a classification model to classify spam emails from using a model- Deep Support Vector Machine (Deep SVM)…
Emails are a very important part of our life today for information sharing. It is used for both personal communication as well as business purposes. But the internet also opens up the prospect of an enormous amount of junk and useless information which overwhelms and irritates us. These unnecessary and unsolicited emails are what comprise of spam. This study presents the application of a classification model to classify spam emails from using a model- Deep Support Vector Machine (Deep SVM). Moreover, other classifier models like Support Vector Machine (SVM), Artificial Neural Network models have also been implemented to compare the performance of proposed Deep SVM model. Furthermore analysis has been done to compare all the performances using available numerical statistics obtained from these models to find the best model for the purpose. Spam filtering is a very essential feature in most email services and thus effective spam classification models are pertinent to the current digital communication scenario and various work has been done in this area.
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A Modified Brainstorm Optimization for Clustering Using Hard c-Means
Research in Computational Intelligence and Communication Networks (ICRCICN), 2015 IEEE International Conference
The preeminent intention of the proposed study is exploring the performance of the Brainstorm Optimization algorithm in Hard c-means clustering of data. The rationale behind this analysis is to generate a random solution set of centroids and then modify the centroids so as to refine the clusters. As we are using Brainstorm Optimization which is a form of evolutionary algorithm this refinement of centroid happens through competition and cooperation with existing centroid values. This algorithm…
The preeminent intention of the proposed study is exploring the performance of the Brainstorm Optimization algorithm in Hard c-means clustering of data. The rationale behind this analysis is to generate a random solution set of centroids and then modify the centroids so as to refine the clusters. As we are using Brainstorm Optimization which is a form of evolutionary algorithm this refinement of centroid happens through competition and cooperation with existing centroid values. This algorithm incorporates both exploitation and exploration of the search space to generate the new centroids. The algorithm has been implemented with the Iris data set and its validity and effectiveness is tested with the help of commonly used internal evaluation measures for clustering like Davies Boudlin Index and Dunn Index.
Patents
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Clustering Of Structured Log Data By Key Schema
Issued US11321158
Clustering of structured log data (key-value paired) by keys and their frequency for easier analysis and visual comparison.
Courses
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Advanced Natural Language Processing
COMPSCI690N
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Algorithms for Data Science
COMPSCI590D
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Database Design and Implementation
COMPSCI645
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Information Retrieval
CMPSCI646
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Machine Learning
COMPSCI589
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Neural Networks: A Modern Introduction
COMPSCI682
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Probabilistic Graphical Models
COMPSCI688
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Reinforcement Learning
CMPSCI687
Projects
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SnapnShop
Built a chrome extension that lets you select some clothing you like while browsing the internet, like while watching a video and opens up sites that sell similar things on the browser.
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Coordinate Detection of People entering Room
Developed a system using Python that detections when people enter a room and plot the
coordinates of the person in a top view representation of the room with respect to a marker
using OpenCV and Haar Cascade. -
Image Skew Detection Correction
Used OpenCV for skew detection in images and correcting them.
Honors & Awards
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Most Creative Algorithm @ Hack UMass
Kensho
Built a chrome extension to capture any clothing you like while scrolling through webpages and get suggestions of websites that sell similar things.
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Joint Winners Of GE Healthcare Challenge- Camtech Jugaadathon, Bangalore
GE
Tried to demonstrate a cost effective way of production of Nitrous Oxide as an anesthetic in a way to ensure its continuous availability in rural areas!
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Top Teams for FICCI Heal Awards
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Were shortlisted for the FICCI Heal Awards as a follow up after CamTech Jugaadathon, 2014.
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Best Innovator for Novartis Foundation of Sustainable Development RMNCH Challenge- Camtech Jugaadathon, Bangalore
Novartis Foundation of Sustainable Development
We worked on a app for the mobile that can be used to predict leprosy based on skin lesion and numbness of skin. We aimed at using image processing and neural networks for the same.
http://www.thehindubusinessline.com/companies/a-jugaadathon-for-innovative-healthcare-solution/article6231054.ece -
Makeathon, VIT University (Top Teams)
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Worked on prototyping a smart cart to reduce queuing in supermarket cash counters. Were among the top teams to qualify for Honeywell Hackathon(VIT).
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Spell Bee
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Won All India Spell Bee in the literary fest of the college.
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Mozilla App Days- top 8 developers
Mozilla
My team was one of the top 8 developers in Firefox App Days in Bangalore.
Languages
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English
Full professional proficiency
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Hindi
Limited working proficiency
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Bengali
Native or bilingual proficiency
Organizations
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Computer Society Of India - VITU Chapter
Technical Core Committee
- Present -
HackHer413
Co Head External Outreach
-Headed the external outreach initiative at the first all-women and non-binary student hackathon in Western Massachusetts, taking place early February of 2019 and hosted at UMass.
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Join now to viewMore activity by Reetika
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🌟 Excited & honored to have had the opportunity to give a couple of guest lectures at the Rutgers Business School on the Power of Storytelling!…
🌟 Excited & honored to have had the opportunity to give a couple of guest lectures at the Rutgers Business School on the Power of Storytelling!…
Liked by Reetika Roy
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Today marks the end of my 6+ years journey at Sumo. I'm not one to post on here but I wanted to thank all of the talented people past and present…
Today marks the end of my 6+ years journey at Sumo. I'm not one to post on here but I wanted to thank all of the talented people past and present…
Liked by Reetika Roy
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