April 19th-21st, 2022
AI for Cybersecurity
Learn the essentials to become a skilled expert in Machine Learning for Cybersecurity
Leverage Your Programming Skills
Become a
Machine Learning Specialist in Cybersecurity
With the rapid growth of Artificial intelligence comes rising demand for Machine Learning specialists in Cybersecurity. To analyze massive amounts of data to detect and protect against the latest malware, ransom, trojan horses and other threats requires serious engineering. These projects of the future promise to be some of the most exciting and in demand jobs in software engineering today.
An ML specialist in Cybersecurity helps organizations evolve and transform their cybersecurity attitudes through intelligent code analysis, configuration analysis, and activity monitoring. At ODSC, build on your programming skills to implement cybersecurity solutions to protect organizations from existing cyber threats and identify new types of malware. You will learn from leading experts everything from data mining and organization to essential use of AI neural networks and automatic learning model recognition.
Some of our Previous AI for Cybersecurity Speakers

Jess Garcia
Jess Garcia is the Founder of the global Cybersecurity/DFIR firm One eSecurity and a Senior Instructor with the SANS Institute.
During his 25 years in the field, Jess has led a myriad of complex multinational investigations for Fortune 500 companies and global organizations. As a SANS Instructor, Jess stands as one of the most prolific and veteran ones, having taught 10+ different highly technical Cybersecurity/DFIR courses in hundreds of conferences world-wide over the last 19 years.
Jess is also an active Cybersecurity/DFIR Researcher. With the mission of bringing Data Science/AI to the DFIR field, Jess launched in 2020 the DS4N6 initiative (www.ds4n6.io), under which he is leading the development of multiple open source tools, standards and analysis platforms for DS/AI+DFIR interoperability.

Arica Kulm
Dr. Arica Kulm is the Director of Digital Forensic Services at Dakota State University. Arica received her PhD in Cyber Defense from Dakota State University in December of 2020, has a master’s degree in Cyber Defense from Dakota State University, a bachelor’s degree from South Dakota State University and holds several industry certifications. Her research interests include the dark web and dark web host-based forensics.
A Framework for Identifying Host-Based Artifacts in Dark Web Investigations(Talk)

Wendy Nather
Wendy Nather leads the Advisory CISO team at Cisco. She was previously the Research Director at the Retail ISAC, and Research Director of the Information Security Practice at 451 Research. Wendy led IT security for the EMEA region of the investment banking division of Swiss Bank Corporation (now UBS), and served as CISO of the Texas Education Agency. She was inducted into the Infosecurity Europe Hall of Fame in 2021. Wendy serves on the advisory board for Sightline Security, and is a Senior Cybersecurity Fellow at the Robert Strauss Center for International Security and Law at the University of Texas at Austin.

Charles Givre
Charles Givre recently joined JP Morgan Chase works as a data scientist and technical product manager in the cybersecurity and technology controls group. Prior to joining JP Morgan, Mr. Givre worked as a lead data scientist for Deutsche Bank. Mr. Givre worked as a Senior Lead Data Scientist for Booz Allen Hamilton for seven years where he worked in the intersection of cyber security and data science. At Booz Allen, Mr. Givre worked on one of Booz Allen’s largest analytic programs where he led data science efforts and worked to expand the role of data science in the program. Mr. Givre is passionate about teaching others data science and analytic skills and has taught data science classes all over the world at conferences, universities and for clients. Mr. Givre taught data science classes at BlackHat, the O’Reilly Security Conference, the Center for Research in Applied Cryptography and Cyber Security at Bar Ilan University. He is a sought-after speaker and has delivered presentations at major industry conferences such as Strata-Hadoop World, Open Data Science Conference and others. One of Mr. Givre’s research interests is increasing the productivity of data science and analytic teams, and towards that end, he has been working extensively to promote the use of Apache Drill in security applications and is a committer and PMC Member for the Drill project. Mr. Givre teaches online classes for O’Reilly about Drill and Security Data Science and is a coauthor for the O’Reilly book Learning Apache Drill. Prior to joining Booz Allen, Mr. Givre, worked as a counterterrorism analyst at the Central Intelligence Agency for five years. Mr. Givre holds a Masters Degree in Middle Eastern Studies from Brandeis University, as well as a Bachelors of Science in Computer Science and a Bachelor’s of Music both from the University of Arizona. Mr. Givre blogs at thedataist.com and tweets @cgivre.
Rapid Data Exploration and Analysis with Apache Drill(Half-Day Training)

Tempest Van Schaik, PhD
Tempest is passionate about improving lives using sensors, data, and AI. Some of the ways she’s driven impact have been through her startup, SoilCards, which aims to make mobile soil testing accessible to the world’s poorest farmers in order to improve their livelihood and protect the environment. She has also developed novel ways to measure cognitive function and mood in people with depression using wearables. She has used data science to improve physiotherapy for children with cystic fibrosis, and has put principles of responsible AI into practice to build predictive ICU models which treat different patient groups fairly. She is currently a Senior Machine Learning Engineer in Microsoft’s Commercial Software Engineering (CSE) team, where she is an ML Lead for collaborations with some of Microsoft’s biggest healthcare customers. She is a member of CSE’s Responsible AI board and a CSE ambassador for Diversity & Inclusion, because she believes in promoting positive change as a leader in the industry. She has a PhD in Bioengineering from Imperial College London, with an internship at MIT, and an Imperial College Rector’s Award. She is a Technical Advisory Board member of Ultromics Ltd as well as a TEDx and SXSW speaker. Her research has received awards from Innovate UK and the US National Academies of Science Engineering and Medic.

Christopher Crowley
Christopher Crowley has 20 years of experience managing and securing networks, beginning with his first job as an Ultrix and VMS systems administrator at 15 years old. Today, Crowley is a Senior Instructor at the SANS Institute and the course author for SOC-Class.com: the culmination of his thoughts on effective cybersecurity operations.
He works with a variety of organizations across industries providing cybersecurity technical analysis, developing and publishing research, sharing expert security insights at conferences, and chairing security operations events. He has provided training to
thousands of students globally.
Crowley holds a multitude of cybersecurity industry certifications and provides independent consulting services specializing in effective computer network defense via Montance®, LLC, based in Washington, DC.
Data Analysis for SOC Survey(Workshop)

Paul Vixie
Dr. Paul Vixie is an Internet pioneer. Currently, he is the Chairman, Chief Executive Officer and Cofounder of Farsight Security, Inc. He was inducted into the Internet Hall of Fame in 2014 for work related to DNS and DNSSEC. Dr. Vixie is a prolific author of open-source Internet software including BIND, and of many Internet standards documents concerning DNS and DNSSEC. In addition, he founded the first anti-spam company (MAPS, 1996), the first non-profit Internet infrastructure software company (ISC, 1994), and the first neutral and commercial Internet exchange (PAIX, 1991). He earned his Ph.D. from Keio University.
Passive Privacy-respecting Collection of DNS Transaction Data(Talk)

Steven Konecny
Steve is a high-tech investigator and business consultant with over 25 years of experience having worked within a big four accounting firm, a national accounting firm as well as having started his own software and consulting company. He specializes in the utilization of information technology and information analysis within complex corporate disputes, investigations, litigation and business turnarounds. His broad range of experience spans the disciplines in digital forensics, investigations, risk management, cyber security, IT management, data analytics and litigation support. He has worked on hundreds of engagements, from investigating small IP theft and employee misconduct cases to large complex international Ponzi and fraud schemes where he managed cross border teams that collected and analyzed information on matters that often took years to resolve. Steve also serves as a testifying expert on cases.
Mitigating Risk Through Threat Hunting(Tutorial)
Click Here For Full Lineup
See all sessionsYou Will Meet
Some of the world’s leading AI experts
Some of the best minds and authors behind today’s most popular AI platforms
Artificial Ingelligence and data science innovators
Data science & analytics specialists
Developers, engineers and programmers looking to build AI enabled software
Hundreds of attendees focused on AI engineering
CTOs and Chief Data Scientists from startups and Fortune 500 companies
Data scientists, data engineers, and AI platform experts
Peers from startups to Fortune 500 companies wrestling with large sets of consumer data
Representatives from Government agencies, universities, and other large institutions
What You'll Learn
Talks + Workshops + Special Events on these topics:
UpSkill Topics
Enhanced Machine Learning for Cybersecurity
Building a Holistic Risk Profile: Near Real-Time Approach to Insider Threat Detection
Linear Algebra, Calculus, and Probability: The Math ML Experts Master
Solving the Data Scientist’s Cold-Start Problem with Machine Learning Examples
Atypical Applications of Typical Machine Learning Algorithms
Introduction to Scikit-learn: Machine learning in Python
Intermediate Machine Learning with Scikit-learn: Cross-validation, Parameter Tuning, Pandas Interoperability, and Missing Values
Intermediate Machine Learning with Scikit-learn: Evaluation, Calibration, and Inspection
Advanced Machine Learning with Scikit-learn: Text Data, Imbalanced Data, and Poisson Regression
and more…
Languages & Frameworks
Tensorflow 2, PyTorch, Keras, Caffe 2.0, CNTK
Python scikit-learn, SciPy, Pandas, PyMC3,
R Programming, Keras, CARET
spaCy, AllenNLP, Stanford NLP
Spark, MLlib, Storm, Hadoop, Mahout
Kubernetes, Kafka, Zeppelin, Ignite
Apache Airflow, KubFlow, MLFlow
NLP Transformers, BERT, ULMFit, ElMo
Julia, Java, Jupyter Notebooks, NoSql, Neo4J
Why Attend?
Immerse yourself in talks and workshops on AI Engineering frameworks, topics, and languages
Learn about AI Engineering from leading AI experts who authored and built many of the platforms in use today
Network and connect with like-minded attendees to discover your next job, service, product or startup
Get speaker insights and training in AI frameworks such as TensorFlow, MXNet, PyTorch, Spark, Storm, Drill, Keras, and other AI platforms