Engineer Intern Software

SAKSHAM GARG

240-***-**** # adwath@r.postjobfree.com ï linkedin.com/in/saksham-garg § github.com/sakshamgarg EDUCATION

New York University Sep. 2021 – May 2023

Master of Science in Computer Science, GPA:3.5/4 New York City, NY, USA Coursework: ML in Finance, Computer Vision, NLP, Big Data App Dev, Fundamental Algorithms, Database, Reinforcement Learning Manipal Institute of Technology Aug. 2014 – May 2018 Bachelor of Technology in Computer Science Manipal, KA, India Coursework: Neural Network & Fuzzy Logic, Natural Computing, Human Computer Interaction, AI, Operating System, Data Mining EXPERIENCE

Altair Engineering Jan 2018 – July 2021

Software Engineer Bangalore, India

• Led and implemented spark-pbspro-connector (GitHub), the integration of PBS Professional as a pluggable scheduler in Apache Spark, increasing efficient use of resources

• Automating 4500+ tests for Windows OS by ideating and productionizing backend framework for QA in PBSPro

• Developed authentication mechanism between Windows & Linux services which increased interoperability between 2 OS P.K. Online Ventures, Inc June 2017 – July 2017

Software Engineer Intern Gurgaon, India

• Leveraged content based filtering & collaborative filtering ML algorithms to devise a News Recommendation System

• Integrated with the company’s android application and saw a significant increase in the user-engagement by 47% PROJECTS

Personalized Product Search Engine Apache Spark, Scala, Elastic Search, GitHub Sep 2022 – Dec 2022

• Cleaned 89GB of Amazon Review Dataset using PySpark & used ALS algorithm with Spark ML to generate the matrix

• Stored 4 million item details with item factors in the GCP Elastic Search and generated personalized search tailored as per the preferences of the users determined from their previous purchases Credit Risk Modeling using ML Python, Scikit-learn, Pandas, GitHub Sep 2022 – Nov 2022

• Predicting the probability of default that a potential borrower will default on a prospective loan over the next 12 months

• Data mining financial statement data containing more than 1 million firm years by augmenting macroeconomic variables Augmented DPNs for uncertainty estimation & out of distribution detection GitHub Sep 2022 – Nov 2022

• Deviced a method to augment a classifier network into a Dirichlet prior network, using a novel loss for DPNs, considering the resulting classifier as an energy-based model and the factorization characteristics of data in view of the likelihood ratio test for out-of-distribution and misclassification detection Diet Vision Python, Flutter, Android, IOS, Tensorflow, GitHub May 2022 - Aug 2022

• Developed a Mask-RCNN model for 3D image reconstruction of a meal thereby giving users its nutritional value

• Led end-to-end development for the IOS and Android application using flutter. REMO: Robust mean absolute error styled bias mitigation objective Python Jan 2022 - May 2022

• A novel approach to de-bias a new & pre-trained language model like GPT using modified training objectives Emotion Detection Analysis Python, Jupyter Notebook, GitHub Feb 2022 - May 2022

• Content based classification using RNN and transformer based models to detect emotions of Republicans and Democrats Assigning sentiment score for twitter tweets R, Sentiment Analysis, IEEE ICACCI December 2018

• Enhanced algorithms by 35% for better classification of sentiments to increase accuracy of the insights about a user’s preference

Air Pollution Analysis Python, Azure Web Services, Arduino, Alphagas sensors Sep 2017 - Dec 2017

• An interactive air quality detection system that analyses data for providing atmospheric quality to the user in real time

• Achieved 50% quicker response time to increasing pollution of a city by notifying users through web/mobile apps TECHNICAL SKILLS

Programming: Python, C, C++, Java, MySQL, R Programming, Shell Scripting, Bash, Scala, CUDA, HTML, CSS, Javascript Tools/Frameworks: Spark, Android, Flask, Docker, Git, Azure, AWS, REST, PyTorch, Kubernetes, Jira, Jenkins, Flutter, Linux, MATLAB

LEADERSHIP / EXTRACURRICULAR

Graduate Teaching Assistant: Assisted various professors for courses like Cybersecurity and Privacy Management (NYU Stern School of Business), Big Data (NYU Center for Data Science) and Regression & Categorical Analysis (NYU GPH) Category Head: Led social media category of college technical and Cultural fests, supervising team of 30. Special Mentions: in Economics Symposium & inter school Model United Nations (MUN)

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