Data Con LA 2020
Description
Coming from a grand belief of data democratization, I believe that in order for any team to be successful collaborators, it has to be data centric and data should be accessible to all.
*To ensure that your non software or software engineering centric team has maximum efficiency, data should be visible, data lake should be accessible.
*Form a database for analytics summaries, talk about the different technologies(SQL, NoSQL) cost of deployment, need, team driven structure. Build an API for this database for external/inter team crosstalk.
*Build analytics and visual layer on top of it. Flask/Django/Node, etc.., to enable the team to have high visibility in their analysis, and to ensure a higher turnaround of data.
*Talk about an easy way of enabling the team to run code, could be local/cloud, JupyterHub is a great way of doing so, talk about the tremendous value added in that and the potential it enables
*Talk about the common tools user for version control/CICD/Coding technologies, etc..
*Finally summarize the value of the mixture of all these tools and technologies in order to ensure the maximum efficiency.
Speaker
Nawar Khabbaz, Rivian, Data Engineer
Experienced Software Engineer with a demonstrated history of working in the computer software industry. Skilled in Java, Python, Javascript(ES6), Flask, React and Databases. Strong engineering professional with B.Tech in Computer Engineering from Thapar University, Patiala.
Graphs are common in a variety of situation, from social networks to financial transactions. These graphs are gold mines of information, and being able to process them is key to the success of many businesses. Real graph, however, are growing larger and larger, and traditional software and algorithms cannot satisfy the performance needs of the most demanding users.
Gospel, a research line at NECSTLab, aims at making graph processing faster and
readily available to researchers and industry, by leveraging high-performance heterogeneous and novel computer architectures. From accelerating algorithms such as PageRank by making use of modern GPUs, to extending existing frameworks for graph analysis, Gospel offers a broad array of techniques to bring graph processing to the world of high-performance computing.
Currently, seeking full-time Software Development positions
M.Sc Computer Science graduate from the University of Oregon
Experienced in Web/Mobile development, Machine Learning techniques, Data Science, Internet of Things and Distributed systems
Data Con LA 2020
Description
Coming from a grand belief of data democratization, I believe that in order for any team to be successful collaborators, it has to be data centric and data should be accessible to all.
*To ensure that your non software or software engineering centric team has maximum efficiency, data should be visible, data lake should be accessible.
*Form a database for analytics summaries, talk about the different technologies(SQL, NoSQL) cost of deployment, need, team driven structure. Build an API for this database for external/inter team crosstalk.
*Build analytics and visual layer on top of it. Flask/Django/Node, etc.., to enable the team to have high visibility in their analysis, and to ensure a higher turnaround of data.
*Talk about an easy way of enabling the team to run code, could be local/cloud, JupyterHub is a great way of doing so, talk about the tremendous value added in that and the potential it enables
*Talk about the common tools user for version control/CICD/Coding technologies, etc..
*Finally summarize the value of the mixture of all these tools and technologies in order to ensure the maximum efficiency.
Speaker
Nawar Khabbaz, Rivian, Data Engineer
Experienced Software Engineer with a demonstrated history of working in the computer software industry. Skilled in Java, Python, Javascript(ES6), Flask, React and Databases. Strong engineering professional with B.Tech in Computer Engineering from Thapar University, Patiala.
Graphs are common in a variety of situation, from social networks to financial transactions. These graphs are gold mines of information, and being able to process them is key to the success of many businesses. Real graph, however, are growing larger and larger, and traditional software and algorithms cannot satisfy the performance needs of the most demanding users.
Gospel, a research line at NECSTLab, aims at making graph processing faster and
readily available to researchers and industry, by leveraging high-performance heterogeneous and novel computer architectures. From accelerating algorithms such as PageRank by making use of modern GPUs, to extending existing frameworks for graph analysis, Gospel offers a broad array of techniques to bring graph processing to the world of high-performance computing.
Currently, seeking full-time Software Development positions
M.Sc Computer Science graduate from the University of Oregon
Experienced in Web/Mobile development, Machine Learning techniques, Data Science, Internet of Things and Distributed systems
MANAGEMENT SKILLS DEVELOPMENT AND ASSESSMENT PROJECTAfifah Nabilah
This is a project paper for group assignment for course MGT 4110 (Organizational Behavior). We interview managers and evaluate our own management skills and what is our action plan to improve that skills.
SU GUÍA PARA:
♥♥ Conceptos básicos sobre la
presión arterial
♥♥ El peligro de la presión arterial alta
♥♥ Medidas para evitar o disminuir la
presión arterial alta
Neupart Bright Talk - How Does the New ISO 27001 Impact Your IT Risk Manageme...KMD
Slides from Lars Neuparts Bright Talk webinar concerning the new ISO 27001 changes and how they would affect a company's IT Risk Management Processes.
It is possible to watch the webinar here:
http://www.neupart.com/events/webcasts.aspx
Phase two of OpenAthens SP evolution including OpenID connect optionEduserv
David Orrell, System Architect and Phil Leahy, Service Relationship Manager, talk about Phase II of the OpenAthens Cloud Service Provider project, and also about how OpenAthens is being used as an identity provider service in the corporate sector.
1. KAI KANG
(732) 519-2251 Full-time Software Engineer kk769@scarletmail.rutgers.edu
2801 S. King Dr., Chicago, IL, 60616 github.com/cctv2206
Available to Relocate Nationwide linkedin.com/in/kk2206
EDUCATION
Rutgers, The State University of New Jersey Sep 2014 ~ May 2016
• Master of Science in Computer Engineering. GPA: 3.8
• Relevant Courses: Cloud Computing, Operating System, Software Engineering, Algorithms, Web Application
University of Science and Technology Beijing (USTB) Sep 2010 ~ May 2014
• Bachelor of Engineering in Mechanical Engineering. GPA: 3.5
INTERNSHIP
Software Developer Intern | WINLAB, Rutgers, State University of New Jersey May ~ Aug 2015
• Developed an iOS application (in Swift) establishing local wireless communication between vehicles using
combination of Bluetooth and WiFi.
• Achieved providing guidance messages to divers about vehicles approaching at high speed, tailgating etc. over up to
100 ft. range. (github.com/cctv2206/Project-V2V-iOS)
PROJECTS
AR 3D Tetris Game St. Louis, MO | July ~ Sep 2016
• Design and built an 3D augmented reality Tetris game using Unity and Vuforia SDK in C#.
• The game allows users to play 3D Tetris right on their table through handheld displays (iPhone or iPad).
(github.com/BitTigerInst/AR-3D-Tetris)
Driver Identification Using in-vehicle Data Rutgers, NJ | Feb ~ May 2016
• Applied Support Vector Machine and Neural Network algorithms to the pre-trip driver actions data such as door
closing, starting ignition, shifting gear, etc. which are extracted from in-vehicle data of 10 drivers.
• Achieved 10% accuracy improvement of driver identification by adding 2 more indicators.
• Implemented an Android App (in Java) for transferring data, extracting features and classifying drivers.
(github.com/cctv2206/pre-trip-driver-identification)
Pintos Operation System Project Rutgers, NJ | Feb ~ May 2016
• Modified and strengthened the simple implementation of Pintos Operation System framework.
• Implemented and modified kernel functions (in C) to achieve better synchronization performance, user program and
virtual memory management. (github.com/cctv2206/Pintos-project-3)
Feature-Based Tweets Sentiment Analysis on Movies Rutgers, NJ | Oct ~ Dec 2015
• Designed and built a feature-based movie rating system (in Python) applying sentiment analysis on public tweets
about movies using Natural Language Toolkit (NLTK) and cloud computing technique.
• Generated radar charts for visualizing feature based moving ratings.
• Conducted performance evaluation experiments on single-threaded implementation and MapReduce implementation
on Spark over up to 2 million tweets dataset. (github.com/cctv2206/cloud-computing-project)
Context Awareness Application Rutgers, NJ | Oct ~ Dec 2015
• Designed and built an iOS App (in Swift) detecting user’s activities including standby, walking, running, driving
uphill and downhill using accelerometer, barometer and GPS data.
• Achieved over 95% detection accuracy in general and 10s faster than Google Map navigation when driving uphill and
downhill. (github.com/cctv2206/context-awareness-system)
Classroom Search Platform Beijing, China | Oct 2013
• Designed and built an add-on application of WeChat offering information about available classrooms providing
service to over 18,000 students across campus.
• Implemented room searching, user signup / login and checking in functions (in PHP & MySQL) on SinaAppEngine
(SAE) server.
TECHNICAL SKILLS
• Java, C, Python, PHP, MySQL, HTML and Spark.