Mayank .

Software Engineer

New York City, New York, United States5 yrs 3 mos experience

Most Likely To SwitchHighly Stable

Key Highlights

Expert in Machine Learning and Deep Learning.
Developed advanced NLP pipelines for healthcare applications.
Proficient in deploying models using Docker and AWS.

Stackforce AI infers this person is a Machine Learning and Deep Learning specialist with a focus on Healthcare and Computer Vision.

Contact

mayank.mayank@stonybrook.edu LinkedIn

Skills

Core Skills

Machine LearningDeep LearningNatural Language ProcessingResearchData ScienceComputer Vision

Other Skills

AWSAlgorithmsAllenNLPBERTC++CNNCollaborative FilteringConvolutional Neural Networks (CNN)CycleGANData StructuresData VisualizationDockerEnsemble LearningFace RecognitionGit

Experience

5 yrs 3 mos

Total Experience

1 yr 1 mo

Average Tenure

3 yrs 7 mos

Current Experience

Paypal

2 roles

Software Engineer (Machine Learning)

Feb 2023 – Present · 3 yrs 4 mos · Hybrid

Machine LearningDeep Learning

Data Scientist

May 2022 – Aug 2022 · 3 mos · New York City Metropolitan Area

Devised machine learning (ML) based pipeline for enhancing data quality pertaining to issue management. This involved developing different ML models for imputing missing values and identifying mislabeled samples. Lastly, we leveraged ensemble learning to learn from multimodal data which improved the model’s performance from 76.2% to 80.3%.
Developed a ML-based semantic search engine by generating synthetic queries based on Sentence-Bert embedding.

Machine LearningEnsemble LearningSemantic SearchData Science

Stony brook university

2 roles

Research Assistant

Promoted

Mar 2022 – Dec 2022 · 9 mos · New York, United States

Curated a labeled medical dataset constituting ~16k samples using selenium and rule-based NLP techniques.
Developing an end-to-end Named Entity Recognition (NER) pipeline for Medical unstructured data using AllenNLP toolkit.

SeleniumNLPNamed Entity RecognitionAllenNLPNatural Language ProcessingResearch

Teaching Assistant

Jan 2022 – May 2022 · 4 mos · New York, United States

Teaching assistant for CSE 352 Artificial Intelligence course

Moodboard analytics

Deep Learning Engineer

Sep 2020 – Mar 2021 · 6 mos · Bengaluru, Karnataka, India

- Developed an end-to-end Sentiment Analysis and Named Entity Recognition (NER) models using BERT variants and deployed the trained models using Docker Container on AWS.

Sentiment AnalysisNamed Entity RecognitionBERTDockerAWSDeep Learning+1

Defence research and development organisation

Research Intern

Jan 2020 – Mar 2020 · 2 mos · Greater Delhi Area

- Curated a dataset of 2000+ images and implemented CycleGAN paper for synthetic image generation and experimented with various CNN architectures and the resulting model generated accurate results for most of the captured scenarios.

CycleGANCNNComputer Vision

Nanyang technological university

Research Intern

May 2019 – Aug 2019 · 3 mos · Singapore

Worked under Asst. Prof. Lam Siew Kei in Hardware and Embedded Systems Lab (HESL).
Implemented Pix2Pix and CycleGAN papers on NTU campus dataset to translate images from day to night and vice-versa and experimented with various CNN architectures such as U-Net, Resnet.
Model built using U-Net architecture as Generator and PatchGAN Discriminator generated appealing results.

Pix2PixCycleGANCNNComputer Vision

Csir-cdri

Research Intern

Jan 2019 – Mar 2019 · 2 mos

Worked under Dr. Sukant Khurana (Scientist at CSIR-CDRI).
Studied and summarized various research papers published in the field of Alzheimer’s disease prediction using Machine Learning.
Published a blog on Medium describing methods for the prediction of Alzheimer’s disease using Machine Learning. (Link - https://link.medium.com/P3KDBBIrtV ).

Olcademy

Machine Learning Intern

Jun 2018 – Sep 2018 · 3 mos

Implemented various Machine Learning algorithms to analyze user’s sentiment on text data of online course reviews.
Implemented Collaborative Filtering method using K Nearest Neighbor (KNN) to recommend relevant courses to the user.

Machine LearningCollaborative FilteringKNN