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aghosh80@gatech.edu I am an MBA Candidate at the University of Chicago Booth School of Business, where I am the Co-Chair of the Retail and Luxury (RAL) Group and recipient of the Forte Foundation Fellowship. Previously, I was a software engineer at Tableau CRM, Salesforce, where I worked as a member of the Query Engine Team. I graduated from Georgia Tech, with a specialization in Machine Learning and Systems. At Tech, I was a part of the Georgia Tech Database Group, where I worked extensively on the SQLCheck project, advised by Joy Arulraj. Our anti-pattern detection tool is now available as an extension on VSCode. In what seems like a previous life, I used to play basketball for the West Bengal State Team, India and Steel Authority of India Ltd., India. More recently, I have started writing the Kultivating Nostalgia series. Do check it out! |
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Arthita Ghosh, Deven Bansod, Arpit Narechania, Prashanth Dintyala, Su Timurturkan, Joy Arulraj. 47th International Conference on Very Large Data Bases, 2021 |
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Arthita Ghosh, Ankita Sinha, Nancy, Arindam Chatterjee. Keywords: NoC,Simple network,Garnet Network, Cache coherence, Snoopy protocol, Directory based protocol, GEM5 16th International Conference on Information Technology, 2017 |
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Arthita Ghosh, Joel Ye, Sashank Gondala. Keywords: CNN, Spiking Neural Networks, STDP. Computation and Brain, Spring 2021. Georgia Tech The objective of this project is to propose a biologically plausible algorithm for modelling a visual invariant. Target class of visual stimuli is the frontal-view faces. We start with a basic CNN as motivated by demonstrations that their hierarchical feature extraction is effective and at least correlated with the brain’s visual stream. Nonetheless, we aim to improve biological plausibility, and evaluate the effects of both regularization using a spiking neural network. Experiments and Results |
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Arthita Ghosh, Neha Pande, Rohan Goel, Rohit Mujumdar, Sai Shravani Sistla. Keywords: BERT, TF-IDF, PCA, Support Vector Machines, Latent Dirichlet Allocation, Clustering. Machine Learning, Spring 2020. Georgia Tech Prediction of chances of a paper being accepted to a conference by using unsupervised methods to find patterns in the data and exploring its underlying structure, through tasks like topic-modelling and clustering. website |
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Neda Tavakoli, Lane Dalan, Richa Tibrewal, Arthita Ghosh, Harish Kupo KPS. Keywords: Genome, Bidirectional LSTMs, supervised learning, deep learning. Big Data Systems and Analytics, Fall 2019. Georgia Tech Used Bidirectional and forward-backward LSTMs to create embedding vectors for genomic sequences. These embedding vectors were then run through various clustering algorithms to group genomic sequences to provide insight into what sequences play similar roles or can be found in similar contexts. website | code |
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Arthita Ghosh, Beno Jeya Savarimuthu, Harrison Banh, Richa Tibrewal, Vaibhav Bhosale. Keywords: VPN, Proxy Server, IPSec, OpenSwan. Computer Networks, Fall 2019. Georgia Tech Created Custom VPN using IPSec and OpenSwan hosted on an AWS Cloud Environment. report | slides |
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Design inspired from here |