Abubakarr Jaye

scikit-learn

NumPy

pandas

React

Google Cloud Platform

Microsoft Azure

Amazon Web Services

Data Science

Natural Language Processing

GPT-3

Remote Software

Backend Development

C++

Object-oriented programming

Computer Vision

Machine Learning

Computer Science

Product Development

Javascript

Java

Python

Data Analysis

Tensorflow

Software Development

PyTorch

Available for hire fromNegotiable

Contracts

Full-Time Roles

AI Pioneer with Proven Cost-Saving Innovations: Bridging Deep Learning Expertise with Business Strategy for the Robotics and Finance Industry.

I am a multifaceted professional with a robust background in robotics, artificial intelligence, and software engineering. As a Robotics Fellow at Amazon Fulfillment Technologies & Robotics, I played a pivotal role in devising strategies that saved $360 MM and was instrumental in AI strategy proposals. I founded Lumnis Factors, where I developed the LUMNIS API for asset data, and previously interned at JP Morgan Chase & Co, working on automated trading strategies and software engineering projects. I hold a Bachelor's in Computer Science and Economics from the University of Illinois Urbana Champaign and I am currently pursuing a Masters of Engineering in Computer Science at Brown University.

Projects

Research Project: The Office Character Dialogue Generation Using Images

Developed an advanced dialogue generator to create context-aware character dialogues based on a still frame from the TV show, "The Office".See More

TS2VecV2 - Enhancing Time Series Representation Learning

Developed TS2VecV2, a novel framework for time series data, incorporating meta features and addressing non-stationarity. Demonstrated improved performance in long-term horizon predictions and effectively learned the underlying data structure, emphasizing better generalizability and efficient learning of multiple in-domain probability distributions.See More

Research Project: Enhancing Time Series Forecasting Through Transfer Learning

Pioneered a task-agnostic pre-training method using contrastive learning to address challenges of non-stationarity and large input domain space in Time Series forecasting. Utilized a dataset from the Binance exchange with ~450,000 data points, demonstrating potential for improving predictive accuracy and model efficiency in the domain.See More

Undergraduate Capstone Projects

1) Worked with a group of two to create a graph using the Reddit Hyperlink Network dataset to perform various traversals. We also implemented dijkstra's algorithm to compute a shortest path tree from any given subreddit. 2) Implemented Logistic regression, Perceptron, neural net and SVM algorithms using numpy 3) Implemented multi-label classifier using both a self-designed model and pre-defined model (Alex Net) from pytorch 4) Implemented multi-label classifier using both a self-designed model and pre-defined model (Alex Net) from pytorch 5) Built YOLO-like object detector on PASCAL VOC 6) Implemented both a DQN and DDQN on the game of breakout using the OpenAI gym. 7) Trained a RNN on text data for language classification and text generation. 8) Implemented one nearest neighbor from scratch using pytorch 9) Trained a generative adversarial network (GAN) on the CelebA Dataset to learn to generate face images See More

Work History

Applied Scientist

Amazon Fulfillment Technologies & RoboticsJun 2023 - Aug 2023 • 3 mosFormulated a strategy that resulted in cost savings of $360 MM. My analysis was instrumental in the AI strategy proposal presented to Andy Jassy. Proactively identified novel applications of Foundation Models in untapped domains. Collaborated with business stakeholders and engineering units to ensure the seamless transition of research findings into the operational workflow. Presented data-driven insights and research outcomes across all company tiers, effectively communicating complex topics up to the executive level. Wrote an in-depth evaluation of a startup for the Industrial Innovation Fund; Wrote a technical test for evaluating startups, and assisted in evaluating startups by joining pitch meetings; Wrote a research paper exploring different effective ways Generative AI/Foundation Models can be used to identify damage detection.

Founder

LumnisMay 2022 - May 2023 • 1 yr 1 moDeveloped and deployed the LUMNIS API, a comprehensive factor dataset for assets, accessible at docs.lumnis.io. Conducted in-depth research on several microstructure factors, including VPIN (Volume Synchronised Probability of Informed Trading), Kyles Lambda, order imbalance, and more. Utilized SageMaker, AWS API Gateway, EC2, S3, ArcticDB, and MongoDB in API development. Deployed the API on AWS API Gateway and created a SDK for enhanced user accessibility. Engineered a data pipeline to process terabytes of crypto order book and trade data efficiently.

AI & Data Science Summer Analyst

JP Morgan Chase & CoMay 2022 - Aug 2022 • 4 mosWorked with Automated Trading Strategies (ATS) Commodities team . Conducted advanced analysis on order book data, enhancing understanding of market microstructure. Led research initiatives focused on mid-price analysis, optimizing strategies for precise trade executions. Developed machine learning models to predict mid-price movements more accurately using order book data insights.

Software Engineer Intern

JPMorgan Chase & CoJun 2021 - Aug 2021 • 3 mosDeveloped client onboarding notification settings UI using React and JavaScript for the JP Morgan EWallet team. Engineered backend functionalities to edit and view client notification configurations, leveraging React and Spring Boot.

Education

Brown University

Masters Degree, Computer ScienceSep 2022 - Present

University of Illinois at Urbana-Champaign

Bachelors, Computer Science and EconomicsSep 2019 - May 2022

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