Distant Supervision for classifying the sentiment of Twitter messages using MLlib
Published:
Spark MLib with Akka, Play and ReactJS
Posts by Collection
portfolio
StackOverFlow K-Means Analysis
Published:
Implemented a distributed k-means algorithm which clusters posts on the popular question-answer platform StackOverflow according to their score. Moreover, this clustering was executed in parallel for different programming languages, and the results were compared.
RNN Joke Generation with TensorFlow, ML5.js and deeplearn.js
Published:
Elementary example of using ML5.js for prototyping language models
Elo Merchant Category Recommendation for Kaggle
Published:
My solution involved using a combination of boosting classifiers
Quora Insincere Questions Classification Challenge
Published:
Developed a GRU capsule network for Kaggle competition
Tracking COVID - 19 Reproduction Rates
Published:
Measuring effective reproduction rates across international locales
publications
Multi-angled Statistical Approach to Human Trafficking Detection and Profiling
Published in Laboratory for Analytical Sciences Conference, 2017
This conference presentation highlights the use of deep learning applied to human trafficking.
Recommended citation: Saanchi, Y, Wang, M., Ahluwalia, S., Laber, E. & Caltagirone, S. (2017, December). Multi-angled Statistical Approach to Human Trafficking Detection and Profiling. Laboratory for Analytical Sciences, Raleigh, NC. http://ahlusar1989.github.io/files/las_2017_trafficking_detection_v2.pdf
Repucall: Towards Describing the Reputability of Phonenumbers
Published in North Carolina State University OUR Symposium, 2018
This paper was prepared after exploratory work in telephony studies of open-sourced feedback and complaints from victims of robocalls and of predatory phishing scams.
Recommended citation: Ahluwalia, S. & Reaves, B. (2018, April). Repucall. Paper submission at the North Carolina State University OUR Symposium, Raleigh, NC. http://ahlusar1989.github.io/files/repucall.pdf
Deep Learning within the Context of Doom
Published in North Carolina State University Symposium, 2019
There are two main approaches to reinforcement learning: value based methods that aim to find an optimal Q-function, and policy based ones that directly look for the optimal policy. However most of reinforcement learning problems (such as learning to play games) have large or even continuous states spaces, which makes constructing Q-values table impossible. Thus, there is a need for approximate reinforcement learning. In this paper the Deep reinforcement learning methods we’ve used to train an agent to play in a Doom environment.
Recommended citation: Ahluwalia, Saran and Laber, Eric. (2019, May). " Deep Learning within the Context of Doom" Unpublished Manucript http://ahlusar1989.github.io/files/st_498_independent_study_05_04_2019.pdf
Review of Joint Clustering with Correlated Variables
Published in Fundamentals of Statistical Inference II with Dr. Ana-Marie Staicu, 2020
This paper was a part of my graduate coursework in non-parametric statistics and Bayesian estimation
Recommended citation: Ahluwalia, Saran, Kim, Minjee and Park, Hannah. (2020, May). " Review of Joint Clustering with Correlated Variables" Unpublished Manucript http://ahlusar1989.github.io/files/joint_clustering_paper.pdf
Estimating Single-Family Returns and Home Price Appreciation
Published in Acre Labs, 2022
Recommended citation: Ahluwalia, Saran. " SFR Returns and HPA - A cross-section study across the United States" Working Paper http://ahlusar1989.github.io/files/SFR_returns_and_HPA_sample.pdf
talks
Predicting Gentrification in District of Columbia Wards
Published:
I was part of a interdisciplinary group - aptly named Gentrifuge - tasked with creating a solution during a three month sprint with the Department of Commerce and Small Business Administration. The problem was framed as such:
Multi-Angled Statistical Approach to Human Trafficking Detection & Profiling
Published:
Human trafficking is a form of modern-day slavery that affects millions of people. Escort websites are a primary vehicle for selling the services of trafficking victims.
Enabling Search Using bi-LSTMs
Published:
Within large enterprises, disparate unstructured data sources contain valuable information that needs to be unified with other instrumentation in order to fulfill business objectives. In this talk, we present a deep learning implementation, using bidirectional - LSTMs that enabled Cisco S&TO to enable search for forensic evidence evaluation and unification. Our solution enabled Cisco to streamline processes for service request triaging - reducing time to address customer requests.
teaching
Capital Teaching Resident
Secondary Education, E.L Haynes Public Charter High School, 2012
Member of Selective (Acceptance Rate: 8%) Capital Teaching Residency Program (Partnership between The New Teacher Project (TNTP) and the KIPP Foundation’ KIPP DC Network)
AP Biology Teacher
High School, E.L Haynes Public Charter High School, 2013
Independently created science department for 11th grade in novel high school (at the time, its third year of existence), providing service to 250 students spanning grades 10 and 11. Utilizing CRM - based software, Google Analytics and Excel collaborated with and informed administration, utilizing quantitative and qualitative data, in order to streamline school graduation pathways and drive data-driven interventions for at-risk students (students who possessed greatest achievement gaps in literacy and numeracy)
Upper School Educational Technologist
High School, Stone Ridge School of the Sacred Heart, 2013
Under the guidance of the Director of Technology spearheading entrepreneurial Robotics and Web - Development program in the Upper School, leveraging 3-D printing technologies and in-house professional development curriculum for Upper School Faculty that utilizes Google Applications, Web 2.0 applications and peripheral hardware