プロフィール詳細

プロジェクトを作成

★★★★★

☆☆☆☆☆

★★★★★

☆☆☆☆☆

Kalai R.に依頼

United States

AI Scientist with extensive subject matter expertise in climate and energy including research to market experience

プロフィール概要

Multifaceted AI scientist at Xerox PARC, focusing on application of AI to climate, healthcare and infrastructure. Led and executed ~$2M projects, funded by government agencies such as DARPA and NASA. Summary: Leadership: 2+ years experience in technical leadership, people management (~10 research scientists), strategy setting, hiring talent. Deep learning: 5+ years experience. Computer vision (image and video analysis), NLP. Tools: Keras, Tensorflow, Pytorch, Spacy, NLTK, OpenCV. Machine learning, Operations Research and Statistics: 8+ years experience. Linear and Non-linear Optimization, Classification and Regression analysis, Clustering, Analysis of Variance. Tools: R (caret), Python (scikit-learn, pandas, numpy, scipy). Programming: 8+ years experience (R, Python) Spatial Analysis: 6+ years experience. ArcGIS, ArcPy, QGIS, GRASS, PostGIS, PostgreSQL, Leaflet. Visualization: 7+ years experience. R (ggplot2, lattice, Shiny), Python (matplotlib), Keynote/Powerpoint, HTML, LaTeX. Consulting: 4+ years experience in the Intelligent Transportation Systems industry. Calibrated and installed various ITS hardware devices, ranging from sensors, cameras to ramp meters, and worked with cross-functional teams and various stakeholders to deliver projects on time. Selected projects: – Led and executed $1M DARPA-funded climate AI project to develop novel physics-informed AI models for climate science (Tools: xarray, dask, pytorch, AWS) – Led a research project to develop deep learning based approach to determine methane using column CO2 satellite measurements (Tools: xarray, pytorch) – Project lead for a conversational AI chatbot to help unemployed people affected by COVID-19 find information on pandemic related benefits – Developed an object detection algorithm to be used in augmented and virtual reality assistance applications (Tools: Python, Tensorflow, OpenCV, Unity) – Lead developer of AI generated art project–developed and deployed the model to production (Tools: Tensorflow, Docker, AWS). – Developed a novel mathematical modeling approach through a combination of multi-level logistic regression algorithm and least-cost optimization models to introduce vehicle purchase behavior in energy systems models (Tools: GAMS, R, Python)

専門分野

• ☆ Data Analysis
• ☆ Image Processing
• ☆ Social Network Analysis
• ☆ Computer Simulation/Computational Modeling
• ☆ Algorithm Design
• ☆ Predictive Modeling & Analytics
• ☆ Data Processing
• ☆ Data Exploration
• ☆ Cluster Analysis
• ☆ Data Visualization
• ☆ Big Data Analytics
• ☆ Data Management
• ☆ Data Manipulation
• ☆ Machine Learning
• ☆ Text Mining & Analytics
• ☆ Data Mining
• ☆ Data Cleaning
• ☆ Natural Language Processing
• ☆ Data Architecture
• ☆ Neural Networks
• ☆ Pattern Recognition
• ☆ Artificial Intelligence
• ☆ Deep Learning
• ☆ Computer Vision
• ☆ Data Security
• ☆ Business Analytics
• ☆ Statistics
• ☆ Regression Analysis
• ☆ Multivariate Analysis
• ☆ Mathematical Statistics
• ☆ Earth & Atmospheric Science
• ☆ Geographic Information Systems (GIS)
• ☆ Climate Science
• ☆ Applied Mathematics
• ☆ Mathematical Models
• ☆ Mathematical Optimization
• ☆ Python
• ☆ Tensorflow
• ☆ LaTex
• ☆ R
• ☆ Scikit-learn
• ☆ Markup Languages

サービス

• Writing
• Research
• Consulting
• Data & AI

Writing Technical Writing

Research Scientific and Technical Research

Consulting Scientific and Technical Consulting

Data & AI Predictive Modeling, Statistical Analysis, Image Processing, Image Analysis, Algorithm Design-Non ML, Algorithm Design-ML, Data Visualization, Big Data Analytics, Text Mining & Analytics, Data Mining, Data Cleaning, Data Processing, Data Insights

職務経験

Research Scientist and Team Manager

PARC

8月 2017 - 現在

学歴

PhD Applied Mathematics

University of California, Office of the President - United States

9月 2010 - 7月 2016

認定資格

• Artificial Intelligence Nanodegree

  Udacity

  5月 2017 - 現在

• Introduction to Agent-based Modeling

  Santa Fe Institute

  11月 2016 - 現在

出版物

JOURNAL ARTICLE

Kalai Ramea(2019). An integrated quantitative-qualitative study to monitor the utilization and assess the perception of hydrogen fueling stations . International Journal of Hydrogen Energy. 44. (33). Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 18225--18239. Elsevier {BV}

Eamonn Mulholland, Jacopo Tattini, Kalai Ramea, Christopher Yang, Brian P. Ó Gallachóir(2018). The cost of electrifying private transport – Evidence from an empirical consumer choice model of Ireland and Denmark . Transportation Research Part D: Transport and Environment. 62. Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 584--603. Elsevier {BV}