Graphen's Financial Agent Fraud Detetion adapts artificial intelligence and graph database to detect potential fraud of financial agents and protect banks from the inside

The Graphen team has extensive experience in leading monitoring tasks in 26 of the largest social networks in the United States and understands how to reason behavior on a large scale, analyze motivation, predict influence and dissemination, determine whether a piece of information is true or false, judge intent, analyze geographic space and cultural influence, etc

Know Your Customer - Smart Due Diligence

An advanced due diligence (DD) system effectively reduces workload at banks for merchant due diligence and payment operations, while enhancing Know Your Customer (KYC) capabilities
Applying comprehensive knowledge and product graphs with Bayesian network probabilities helps to monitor and detect suspicious activities and merchants

Graphen's KYC can be applied to any industry that is looking to get more customer insights and analyis, i
e
online marketing, e-commerce, etc

Graphen deveveloped an AI empowered Personal Financial Advisor to assist wealth management and investment

Graphen provides advanced information security technology to scan the company information network, analyze and understands the behavior of each terminal
It uses machine learning, graph analysis, and machine understanding to detect internal abnormalities
When anomaly and motivation are clearly identified, the system can begin to predict what the next abnormal behavior might be

Such an AI anomaly detection system can be applied in a wide range of fields, including long-term threats (APT), internal threats (leakage, sabotage), IoT security, etc
of each enterprise

The Graphen business monitoring system of the central control center helps organizations to grasp the operation status in real time
E
g

• Status of online and mobile activities
• Abnormal conditions of computers and other equipment
  Graphen aims to build applications required for the energy sector based on the Ardi platform to support a sustainable future with green energy
  Our solutions include:
• Electric field and power system anomaly analysis
• Distributed energy source and load forecast
  Graphen has been helping one of the largest energy providers in Asia to make 24-hour predictions of solar power generation per hour in every station in Taiwan
  Graphen Genomics offers Personal Whole Genome Analytics System that analyzes your entire 6
  4B genome
  It provides one's risk likehood of 350+ diseases in 10 major categories with a single test and life long updates

Graphen Gene Dynamic Detection will help you keep tracking the genetic performance over time and help understand your genetic performance trends, allowing you to grasp the distance to the underlying disease, accurately take preventative actions in advance and have long term health risk management

Graphen Drugomics has developed a system based on AI technology to directly predict the three-dimensional structure of proteins from genes

• Nucleic Acid and Small Molecular Drug Design
• Vaccine Design and Optimization
  Graphen partnered with one of the largest enterprises in the automotive industry and developed an advanced Car Doctor

The system successfully achieved close to 99% accuracy of car diagnosis and fix suggestions and achieved 91% accuracy of car diagnosis and fix suggestions with only 1% of training data

Graphen combines its Full-Brain AI to make robots think, learn, and interact like human beings

Using Ardi Understanding to realize the environments via natural languages and computer vision, AI Robots can know what is going on
With Ardi Personality and Ardi Emotion, AI Robots can sense the feeling of the person he/she is interacting and respond accordingly

Dr
Ching-Yung Lin is the CEO of Graphen, Inc
, a startup focusing on developing next-generation Artificial Intelligence technologies, especially solutions for the Finance and Medical industries
Before June 2017, he was Chief Scientist for Graph Computing at IBM and an IBM Distinguished Researcher
He created and led the Network Science and Machine Intelligence department at IBM T
J
Watson Research Center
He is also an Adjunct Professor at Columbia University since 2005, an Affiliate Professor at the University of Washington from 2003 to 2009 and an Adjunct Professor at NYU in 2014

Dr
Lin was named an IEEE Fellow in Nov 2011, the first in the area of Network Science
He is an author of 170+ publications and 29 awarded patents
In 2010, IBM Exploratory Research Career Review selected Dr
Lin as one of the five researchers "mostly likely to have the greatest scientific impact for IBM and the world
” His “Big Data Analytics” course at Columbia University attracts over 300 graduate students every year, and is the top search result on Baidu for Big Data Analytics
He led a team of ~40 researchers from Columbia University, CMU, Northeastern University, Northwestern University, UC Berkeley, Stanford Research Institute, Rutgers University, University of Minnesota and NMU in the then largest US social media analysis project from 2012 to 2015
He also led a project focusing on predicting human behavior for cognitive security applications

In 2015, he was invited to be a panelist together with the White House Chief Data Scientist at the semi-annual conference of the American Medical Association
He was invited as a keynote or plenary speaker at 20+ conferences, including the International Conference on Cybersecurity hosted by the FBI in 2016 and the Expo 2
0 at the New York Javits Convention Center
His work has won seven best paper awards, been shown in 100+ press releases, and was featured four times by BusinessWeek magazine, including Top Story of the Week in May, 2009

Dr
Chen-Yong Cher is the CTO, Infrastructure at Graphen, focusing on the design and development of the production software back-end and infrastructure

Some of his past projects include thermal-aware scheduling in the Linux kernel to reduce power, machine learning of supercomputer event logging and failure event prediction (published in SC2014); hardware thread priority scheduling in a power5 SMT to improve latency (ISCA2008), enable memory garbage collection in Cell SPE accelerators (VEE2010), and he co-invented a pre-fetching technique for DFS traversal in Java Virtual Machine memory management (ASPLOS2004)
Most recently through collaborating with Stanford University and University of British Columbia, he also published techniques to protect systems and GPUs from cosmic rays