100 word maximum. This should be the complete description as it will appear in the conference program if your submission is accepted (see a
sample PAW programs for examples). For both the session description and the session title (field above), please note that our events prefer concrete terms like machine learning (and specific ML methods) over the term artificial intelligence (AI), since AI is a subjective and often-misleading term that is highly ambiguous and frequently employed to over-hype. If you have a specific reason to instead use the term AI, such as to criticize it or to allude to a broader culture, you are welcome to do so, but we recommend that you word things so that this intent is clear.
Name of company to which the case study pertains (if it is your affiliation, name the company here as well as under "Affiliation" below). Please note that, if you are an analytics vendor or consultancy, in most cases, this field is not meant to be your company name - the field only applies if you will disclose and discuss the end-using organization that achieves value with the deployment of machine learning. If you are a vendor, for example, this may be one of your clients. This distinction also pertains to the two yes/no questions immediately above - 50 chars maximum.
Primary modeling or machine learning method employed - this information is collected for internal use and will not appear in your session title or description unless you include it in the pertinent fields above. If you are an analytics services vendor that works primarily or exclusively with one analytics software vendor, indicate this and name the software vendor (required) - 50 chars maximum.
Secondary modeling or machine learning method employed - this information is collected for internal use and will not appear in your session title or description unless you include it in the pertinent fields above - 50 chars maximum.
Primary modeling or machine learning software tool employed - this information is collected for internal use only and, according to PAW policy, may not appear in your session title or description unless it is a free tool - 50 chars maximum.
Secondary modeling or machine learning software tool employed - this information is collected for internal use only and, according to PAW policy, may not appear in your session title or description unless it is a free tool.
For which audience level would your presentation be a better fit: "Expert/practitioner" or "All levels"? Most event sessions are labelled as one or the other. Instead of choosing, you may indicate that either would work for you, and/or indicate a degree of preference. You also may optionally include more specific audience requirements, or other related comments. Note that "All levels" sessions are not necessarily more popular sessions; more than half of the event attendees are hands-on practitioners, many of whom look to "Expert/practitioner" sessions for primary content.
Speaker bio - 150 word maximum. This should be your complete bio, in paragraph form, as it will appear in the conference program if your submission is accepted (see prior
PAW speakers for examples). The bio should be written in third person. If you have previously spoken at PAW, please begin this field with, "PREVIOUS SPEAKER" (this phrase will not be included in your bio).
Speaking experience, a sentence on the quantitative evaluation results and/or project ROI you will present, and any other information, such as references (optional) or a second speaker. If you are proposing a co-presenter, provide name, affiliation, bio and email address. Note that co-presenters are only permitted if they will provide substantive content; co-presenters intended only for introductions, formalities or vendor information are not permitted. If your co-presenter has previously spoken at a PAW event, please include, "PREVIOUS SPEAKER" (this phrase will not be included in her or his bio).
