Brian H. Xu, Ph.D., Data Scientist Lead, Silicon Valley, CA, email@example.com
Proven skills and experiences in solving complex real-world problems, creating innovative AI, ML technologies for new products and services by developing AI, ML, Cyber (Cloud, IoT, data) Security, Data Analytics. As PI & PM, won 8 federal AI-based contracts based on best innovations. Having built and led teams (5~10 scientists) to complete over 15 national contracts (> $10M, 2005~08). Extensive experience in software with over 48 products (AI, ML, data analytics, etc.) and intelligent solutions as a leader of teams since 2005. Having done 20 programs ($5M~$50M/Y) for big customers (Boeing, DARPA, DHS, etc.), developed 25 commercial products (Honeywell, Intel, Oracle, etc.). Had over 38 technical papers and USA patents, and 76 technical presentations.
AREAS OF EXPERTISE
· AI, Machine Learning, Big Data Analytics, etc. · Deep Learning, Advanced AI/ML Algorithms
· Data Science, Cloud Security, Data & IoT Security · Prediction, Anomaly & Malware Detection
· Predictive Analytics, Prescriptive & RT Analytics · SQL, NoSQL, NLP, Text Analytics, Rules
· Intelligent Systems & Agents, Recommendations · AWS, Spark, Cassandra, ML Models & Tools
· Reasoners, data-to-intelligence, Prognostics, CBM+ · Team / Project Dev / Mng, Leadership, etc.
Lead Data Scientist (report to Co-Founder), Ordr.net, Santa Clara, CA, 2019 ~ 2020
Developing and improving IOT device security products by using ML and knowledge-based technologies.
Data Scientist Lead (report to VP), Oracle, San Jose, CA, 2018 ~ 2019
Developed AI based Cloud Security solutions (CASB, etc.), First author for 3 USA patents in Cloud Security.
Responsibilities: Led projects from new ideas, prototyped and tested new ML algorithms, assisted in deploying them to production on cloud for AWS, MS O365, Oracle Cloud, for cloud security (user privilege escalation, etc.).
Lead Data Scientist, Midea Emerging Technology. San Jose, CA, 2017 ~ 2018.
Developed AI products for Smart retails and ecommerce by ML, NLP, big data analytics, knowledge graph.
Responsibilities: Led projects (1) prototyped NLP based sentiment analyses; (2) analyzed all major products sales.
Lead Data Scientist (report to VP), Comcast Innovation Labs. Sunnyvale, CA, 2016 ~ 2017.
Developed cognitive services for AI recommendations, anomaly prediction. Author of 2 USA patents.
Responsibilities: Led projects (1) predict anomalies in TV and WiFi networks, (2) content recommendation engine.
Lead Data Scientist, Intel. Santa Clara, CA, 2016 (cyber security, threat intelligence).
Developed new threat management products for large enterprises and security operation centers (SOCs).
Designed knowledge graph, malware playbooks, info-seekers for AI based threat detection products.
Responsibilities: Led software architecture, developed malware detection ML algorithms, improved our products.
Lead Data Scientist, Infoblox, Inc. Santa Clara, CA, 2015 ~ 2016.
Developed advanced ML and AI algorithms to detect DNS tunneling data leaks, Fast Flux Net, DGA malware.
Responsibilities: Led development of new algorithms to detect and block new threads to protect DNS and data assets.
Principal Computer Scientist, PM, Honeywell Advanced Tech, San Diego, CA, 2008 ~ 2015.
Worked on CBM products for worldwide airplanes maintenance ($6 B / Y) and Led and completed external contracts ($3M ~ $50+ M) and as PM, PI & IC in Big Data Analytics, anomaly detection, predictive analyses.
Have completed over 12 programs by using AI/ML in preventive maintenance, predictive analytics, etc.
Responsibilities: Led and managed 2+ programs per year for aerospace and defense industries, federal contracts, etc.
Group Leader (of Scientist Teams), Physical Optics Co, Torrance, CA, 2004 ~ 2008.
Won and completed 7 federal contracts as sole PI successfully. Completed 15 programs in AI and cyber security. Built/led teams of 5 ~ 10 scientists, completed 20 AI solutions funded by customers.
Responsibilities: Won, led and managed 8 programs as PI for big customers (Army, AF, Navy, DHS, etc.)
Python, Spark, PySpark, Scala, TensorFlow, SK-Learn, NLP NLU, H2O.ai, AutoML, Deep Learning, Jupyter, Pandas, AWS, Apache Ecosystem; Cassandra, HBase, AWS, EC2, SW3, HDFS; Dockers, Kafka, Matlab, MLlib, ELK, R, RStudio, C++, C, C#; Oracle, MySQL, SQL; ASP.net, Jupyter, PyCharm, SDK tools, more.
R&D CONTRACTS solely won by Dr. Xu (and completed 28+ national programs)
Principal Investigator (PI): Dr. Xu, U.S. Citizen
1.Networked Intelligent Agents and Distributed Decision Aids.
2006 - 2008. U.S. Army Contract: W15QKN-06-C-0183. (Phase II, as top 3% in USA).
2.Integrated Intelligent Decision and Information System.
2006 – 2008. U.S. Air Force Contract: FA8750-06-C-0030. (Phase II, as top 3% in USA).
3. Blackboard Pattern-Enabled Integrated Intelligent Toolset. The U.S. Army, 2008, Army Contract: W15P7T-08-C-P405. (Phase II awarded, as top 3% in USA) https://www.sbir.gov/sbirsearch/detail/272887
4. Human Neocortex-Inspired Intelligent Database.
The U. S. Navy/Joint Forces Command, 2006 - 2007. Navy/JFC Contract Number: N00014-07-M-0061. Navy N06-159 https://www.sbir.gov/sbirsearch/detail/272939
5. Intelligent Microagent Grid for Botnet Detection and Mitigation.
The Dept. of Homeland Security, 2006 – 2007. DHS Contract: NBCHC060120.
6. Integrated Intelligent Decision and Information System. The U.S.A. Air Force, 2005 - 2006. U.S. Air Force Contract: FA8750-05-C-0175. https://www.sbir.gov/sbirsearch/detail/272578
7. Networked Intelligent Agents and Distributed Decision Aids (NIADDA).
The U.S. Army Contract Number: W15QKN-06-C-0037, 2006. https://www.sbir.gov/sbirsearch/detail/272442
All classified programs (DARPA, DHS, $5M ~ $50M / Y) cannot be listed here.
PUBLICATIONS (Selected from over 38 Technical Publications)
1. Brian Xu, D. Mylaraswamy, and P. Dietrich. A Cloud Computing Framework with Machine Learning Algorithms for Industrial Applications. Int’l Conf. on Artificial Intelligence, 2013, Las Vegas, NV.
2. Brian Xu, Malware Detection and Mitigation Using Micro-agents. The Proceedings of 2012 International Conference on Artificial Intelligence (ICAI), July, 2012, Las Vegas, Nevada, USA.
3. Brian Xu, S. Kumar, and M. Kumar. Cloud Based Architecture for Enabling Intuitive Decision Making. Proceedings of the 7th IEEE 2013 World Congress on Services, June 2013, Santa Clara, CA, USA.
4. Brian Xu, Integrated Link Analyzers and Associative Search Engines. The Proceedings of 2010 International Conference on Artificial Intelligence (ICAI), July 2010. Las Vegas, NV.
5. Brian Xu and Andrew Kostrzewski, Networked Intelligent Agents for Distributed Decision Making. The 2007 Intl Conf. on Artificial Intelligence (ICAI), 2007, Las Vegas, USA.
6. Brian Xu, A. Kostrzewski, P. LaMonica, R. Jurgens, Net-Centric Rule Engines for Decision Support, The 2008 Intl Conf. on Artificial Intelligence (ICAI), July 2008, Las Vegas, Nevada.
7. Brian Xu, Sathish A.P Kumar, "Big Data Analytics Framework for System Health Monitoring", The 11th IEEE World Congress on Services, July, 2015, NYC, NY.
8. D. Mylaraswamy, Brian Xu, etc., Case Studies: Big Data Analytics for System Health Monitoring. International Conf. on Artificial Intelligence (WorldCom), July, 2014, Las Vegas, NV, USA.
Ph.D. degree in EE, CS (AI, Neural Nets, etc.). Dalhousie University, Canada.
One of USA Patents: 8,468,144, https://encrypted.google.com/patents/US8468144
Tackling the Challenges of Big Data (MIT, 2014).