Event owner lens
Use this record to benchmark whether a comparable event makes the work after the room visible. The score is 40/100, so the next move is to benchmark the weakest pillars before repeating the format.
technology ai startup agenda agenda analysis
ICML - WCA4Z Platform - Accelerating Legacy Code Modernization Using AI Agents, Deep Program Analysis, and - Workshops - 2nd Generative AI for...
This technology ai startup agenda in Technology / AI / Startup shows 28 visible agenda rows from icml.cc and scores 40/100: a moderate design signal with incomplete evidence. The clearest public signals sit in Future-of-Work Fit and Participation Architecture; the main limits are Follow Through and Network Design. Visible mechanisms include Participant work, Network design, and Learning transfer. The public record does not show follow-up or tracking, so the score should be read as design intent rather than... A practical reading: For a reader, this is a comparison record more than a model to copy: it reads as a technology ai startup agenda, with the strongest visible signal in future-of-work fit and participation architecture and the biggest open question around follow through and network design. The practical test is whether the published agenda connects the room to post-event continuation and evidence. This page is an original public-evidence analysis, not a copy of the source agenda or an endorsement of the event. The score places the visible agenda in the moderate design signal band. The strongest visible pillars are Future-of-Work Fit, Participation Architecture, and Problem Specificity; the thinnest visible pillars are Follow Through, Network Design, and Personalization. Visible mechanisms include Participant work, Network design, and Learning transfer. The extracted agenda preview includes 48 visible rows. The most common formats are Unknown, Presentation, and Workshop; the most common inferred purposes are Unknown, Knowledge Transfer, and Showcase.
Eight-pillar fingerprint
Hover any pillar to see what it measures and, where it scored low, what the agenda is missing.
Participation Architecture?56
Participation Architecture - 56/100. Participant work, contribution, interaction, and alternatives to passive broadcast.
Follow Through?5
Follow Through - 5/100. Owners, dates, commitments, progress checks, and accountability after the room.Missing: Add named owners, dates, implementation checkpoints, and a visible post-event continuation path.
Problem Specificity?49
Problem Specificity - 49/100. A clear costly problem, objective, decision, or performance target.
Personalization?34
Personalization - 34/100. Role, path, goal, preparation, or connection tailoring for participants.Missing: Create role-based paths, prepared questions, tailored breakouts, or participant-specific next steps.
Network Design?20
Network Design - 20/100. Structured weak ties, bridge-building, mixers, and relationship persistence.Missing: Replace generic networking blocks with designed introductions, ask-offer exchanges, peer groups, or bridge-building rituals.
Learning Transfer?40
Learning Transfer - 40/100. Applied practice, feedback, workplace use, refreshers, and 30-90 day transfer.
Evidence Maturity?45
Evidence Maturity - 45/100. Baseline, comparison, follow-up, isolation, and attribution confidence.
Future-of-Work Fit?66
Future-of-Work Fit - 66/100. Value against time, hybrid reality, accessibility, AI, and meeting load.
Fix the gaps
Field-tested exercises matched to this agenda's weakest pillars, from the exercise library.
Follow Through (5/100)
Exercises that strengthen it: Mental Toughness Workshop • WorkshopBank · 15% Solutions • WorkshopBank · Network Patches
Network Design (20/100)
Exercises that strengthen it: Fun Trust-Building Group Game for Team Connection - Izzat... · Exciting Group Trust Activity for Building Confidence... · PFP: September 2005
Personalization (34/100)
Exercises that strengthen it: Journey Mapping • WorkshopBank · Group Energiser & Perspective-Changing Exercise - Paradigm... · Photo Storytelling
Agenda Preview
The actual agenda we captured. Every block is classified by format and purpose. Open any block to see how we read it; the colored edge shows whether it is participant work, broadcast, logistics, or a showcase.
Room vs wrapper
23 percent of the 48 classified blocks put participants to work; the rest broadcast, show, or handle logistics. That mix is what drives the participation score.
Participant workBroadcastShowcaseLogistics
all eventTutorialsTrainingSkill building+
Format · Participant workTrainingGuided skill building where participants practice. Counts as participant work and learning transfer.
Evidence basisParticipant work is implied by the formatInferred from format
all eventSpotlight PostersPoster sessionShowcase+
Format · ShowcasePoster sessionPresenters display work; attendees browse and ask questions. Some interaction, not structured work.
Evidence basisOutcome inferred from formatInferred from format
all eventWorkshopsWorkshopParticipant work+
Format · Participant workWorkshopParticipants work on a problem and produce something. The strongest signal of participation architecture.
Evidence basisParticipant work is implied by the formatInferred from format
all eventWorkshopWorkshopParticipant work+
Format · Participant workWorkshopParticipants work on a problem and produce something. The strongest signal of participation architecture.
Evidence basisParticipant work is implied by the formatInferred from format
all event2nd Generative AI for Biology WorkshopWorkshopParticipant work+
Format · Participant workWorkshopParticipants work on a problem and produce something. The strongest signal of participation architecture.
Evidence basisParticipant work is implied by the formatInferred from format
8:30 AMOpening remark VideoPresentationKnowledge transfer+
Format · BroadcastPresentationSpeakers present, the audience receives. Awareness only unless paired with practice or follow-up.
Evidence basisNo participant output visible from this rowRead from source, no work signal
8:45 AMInvited speaker: James J. Collins (Generative AI for Antibiotic Discovery and Synthetic Biology)PresentationKnowledge transfer+
Format · BroadcastPresentationSpeakers present, the audience receives. Awareness only unless paired with practice or follow-up.
Evidence basisNo participant output visible from this rowRead from source, no work signal
9:25 AMSpotlight1 VideoPresentationKnowledge transfer+
Format · BroadcastPresentationSpeakers present, the audience receives. Awareness only unless paired with practice or follow-up.
Evidence basisNo participant output visible from this rowRead from source, no work signal
9:35 AMPoster and breakBreakShowcase+
Format · LogisticsBreakA pacing or recovery block between sessions.
Evidence basisOutcome inferred from formatInferred from format
10:00 AMInvited speaker: David Baker (Design of new protein functions using deep learning) Video LinkPresentationKnowledge transfer+
Format · BroadcastPresentationSpeakers present, the audience receives. Awareness only unless paired with practice or follow-up.
Evidence basisNo participant output visible from this rowRead from source, no work signal
11:00 AMInvited speaker: Martin Renqiang Min (Agentic Generative Biomedicine) VideoPresentationKnowledge transfer+
Format · BroadcastPresentationSpeakers present, the audience receives. Awareness only unless paired with practice or follow-up.
Evidence basisNo participant output visible from this rowRead from source, no work signal
11:40 AMSpotlight2 VideoPresentationKnowledge transfer+
Format · BroadcastPresentationSpeakers present, the audience receives. Awareness only unless paired with practice or follow-up.
Evidence basisNo participant output visible from this rowRead from source, no work signal
12:00 PMPoster and lunchMealShowcase+
Format · LogisticsMealA pacing block. Can carry unstructured networking, not scored as participant work.
Evidence basisOutcome inferred from formatInferred from format
1:00 PMInvited speaker: Mengdi Wang ( From Genome to Theorem: Can AI Agents Do Science?) VideoPresentationKnowledge transfer+
Format · BroadcastPresentationSpeakers present, the audience receives. Awareness only unless paired with practice or follow-up.
Evidence basisNo participant output visible from this rowRead from source, no work signal
1:40 PMInvited speaker: Marinka Zitnik (Empowering biomedical discovery with "AI scientists”) VideoPresentationKnowledge transfer+
Format · BroadcastPresentationSpeakers present, the audience receives. Awareness only unless paired with practice or follow-up.
Evidence basisNo participant output visible from this rowRead from source, no work signal
2:20 PMInvited speaker: Maruan Al-Shedivat (Driving Small Molecule Drug Discovery with Generative Modeling) VideoPresentationKnowledge transfer+
Format · BroadcastPresentationSpeakers present, the audience receives. Awareness only unless paired with practice or follow-up.
Evidence basisNo participant output visible from this rowRead from source, no work signal
2:35 PMSpotlight3 VideoPresentationKnowledge transfer+
Format · BroadcastPresentationSpeakers present, the audience receives. Awareness only unless paired with practice or follow-up.
Evidence basisNo participant output visible from this rowRead from source, no work signal
3:30 PMInvited speaker: Eric P. Xing (Multiscale Foundation Models for Predicting, Simulating, and Programming Biology at All Levels) VideoPresentationKnowledge transfer+
Format · BroadcastPresentationSpeakers present, the audience receives. Awareness only unless paired with practice or follow-up.
Evidence basisNo participant output visible from this rowRead from source, no work signal
4:10 PMPanel discussion: Arash Vahdat, David Li-Bland, Eric P. Xing, Mengdi Wang, Martin Renqiang Min and Marinka Zitnik VideoPanelDiscussion+
Format · BroadcastPanelExperts discuss while the audience watches. Surfaces perspective but rarely creates participant work.
Evidence basisNo participant output visible from this rowRead from source, no work signal
5:40 PMAward and Closing VideoClosingOrientation+
Format · BroadcastClosingFormat not classified from the source; treated as a broadcast block by default.
Evidence basisNo participant output visible from this rowRead from source, no work signal
all eventTutorialsTrainingSkill Building+
Format · Participant workTrainingGuided skill building where participants practice. Counts as participant work and learning transfer.
Evidence basisMediumRead from source
all eventMain ConferenceUnknownUnknown+
Format · BroadcastUnknownFormat not classified from the source; treated as a broadcast block by default.
Evidence basisLowRead from source
all eventSpotlight PostersPoster SessionShowcase+
Format · ShowcasePoster SessionPresenters display work; attendees browse and ask questions. Some interaction, not structured work.
Evidence basisMediumRead from source
all eventWorkshopsWorkshopCo Creation+
Format · Participant workWorkshopParticipants work on a problem and produce something. The strongest signal of participation architecture.
Evidence basisMediumRead from source
all eventCommunityUnknownUnknown+
Format · BroadcastUnknownFormat not classified from the source; treated as a broadcast block by default.
Evidence basisLowRead from source
all eventRocketChat Desktop ClientUnknownUnknown+
Format · BroadcastUnknownFormat not classified from the source; treated as a broadcast block by default.
Evidence basisLowRead from source
all eventWorkshopWorkshopCo Creation+
Format · Participant workWorkshopParticipants work on a problem and produce something. The strongest signal of participation architecture.
Evidence basisMediumRead from source
all event2nd Generative AI for Biology WorkshopWorkshopCo Creation+
Format · Participant workWorkshopParticipants work on a problem and produce something. The strongest signal of participation architecture.
Evidence basisMediumRead from source
all eventProject Page [ OpenReview]UnknownUnknown+
Format · BroadcastUnknownFormat not classified from the source; treated as a broadcast block by default.
Evidence basisLowRead from source
all eventTimezone: America/LosAngelesUnknownUnknown+
Format · BroadcastUnknownFormat not classified from the source; treated as a broadcast block by default.
Evidence basisLowRead from source
8:30 AMOpening remark VideoUnknownUnknown+
Format · BroadcastUnknownFormat not classified from the source; treated as a broadcast block by default.
Evidence basisMediumRead from source
8:45 AMInvited speaker: James J. Collins (Generative AI for Antibiotic Discovery and Synthetic Biology)UnknownUnknown+
Format · BroadcastUnknownFormat not classified from the source; treated as a broadcast block by default.
Evidence basisMediumRead from source
9:25 AMSpotlight1 VideoUnknownUnknown+
Format · BroadcastUnknownFormat not classified from the source; treated as a broadcast block by default.
Evidence basisMediumRead from source
9:35 AMPoster and breakPoster SessionShowcase+
Format · ShowcasePoster SessionPresenters display work; attendees browse and ask questions. Some interaction, not structured work.
Evidence basisMediumRead from source
10:00 AMInvited speaker: David Baker (Design of new protein functions using deep learning) Video LinkUnknownUnknown+
Format · BroadcastUnknownFormat not classified from the source; treated as a broadcast block by default.
Evidence basisMediumRead from source
11:00 AMInvited speaker: Martin Renqiang Min (Agentic Generative Biomedicine) VideoUnknownUnknown+
Format · BroadcastUnknownFormat not classified from the source; treated as a broadcast block by default.
Evidence basisMediumRead from source
11:40 AMSpotlight2 VideoUnknownUnknown+
Format · BroadcastUnknownFormat not classified from the source; treated as a broadcast block by default.
Evidence basisMediumRead from source
12:00 PMPoster and lunchPoster SessionShowcase+
Format · ShowcasePoster SessionPresenters display work; attendees browse and ask questions. Some interaction, not structured work.
Evidence basisMediumRead from source
1:00 PMInvited speaker: Mengdi Wang ( From Genome to Theorem: Can AI Agents Do Science?) VideoUnknownUnknown+
Format · BroadcastUnknownFormat not classified from the source; treated as a broadcast block by default.
Evidence basisMediumRead from source
1:40 PMInvited speaker: Marinka Zitnik (Empowering biomedical discovery with "AI scientists”) VideoUnknownUnknown+
Format · BroadcastUnknownFormat not classified from the source; treated as a broadcast block by default.
Evidence basisMediumRead from source
2:20 PMInvited speaker: Maruan Al-Shedivat (Driving Small Molecule Drug Discovery with Generative Modeling) VideoUnknownUnknown+
Format · BroadcastUnknownFormat not classified from the source; treated as a broadcast block by default.
Evidence basisMediumRead from source
2:35 PMSpotlight3 VideoUnknownUnknown+
Format · BroadcastUnknownFormat not classified from the source; treated as a broadcast block by default.
Evidence basisMediumRead from source
3:30 PMInvited speaker: Eric P. Xing (Multiscale Foundation Models for Predicting, Simulating, and Programming Biology at All Levels) VideoUnknownUnknown+
Format · BroadcastUnknownFormat not classified from the source; treated as a broadcast block by default.
Evidence basisMediumRead from source
4:10 PMPanel discussion: Arash Vahdat, David Li-Bland, Eric P. Xing, Mengdi Wang, Martin Renqiang Min and Marinka Zitnik VideoPanelDeliberation+
Format · BroadcastPanelExperts discuss while the audience watches. Surfaces perspective but rarely creates participant work.
Evidence basisMediumRead from source
5:40 PMAward and Closing VideoUnknownUnknown+
Format · BroadcastUnknownFormat not classified from the source; treated as a broadcast block by default.
Evidence basisMediumRead from source
all eventSpatial Cell-Guided Pretraining for Scalable Spatial Transcriptomics Foundation Model Jing Gong ⋅ Yixuan Wang ⋅ Nicholas Ho ⋅ Xingyi Cheng ⋅ Le Song ⋅ Eric Xing LinkTrainingSkill Building+
Format · Participant workTrainingGuided skill building where participants practice. Counts as participant work and learning transfer.
Evidence basisMediumRead from source
all eventFORT: Forward-Only Regression Training of Normalizing Flows Danyal Rehman ⋅ Oscar Davis ⋅ Jiarui Lu ⋅ Jian Tang ⋅ Michael Bronstein ⋅ Yoshua Bengio ⋅ Alexander Tong ⋅ Joey Bose LinkTrainingSkill Building+
Format · Participant workTrainingGuided skill building where participants practice. Counts as participant work and learning transfer.
Evidence basisMediumRead from source
all eventTwo-Stage Pretraining for Molecular Property Prediction in the Wild Kevin Tirta Wijaya ⋅ Minghao Guo ⋅ Michael Sun ⋅ Hans-peter Seidel ⋅ Wojciech Matusik ⋅ Vahid Babaei LinkTrainingSkill Building+
Format · Participant workTrainingGuided skill building where participants practice. Counts as participant work and learning transfer.
Evidence basisMediumRead from source
The Full Reading
Why It Ranks This Way +
Calibrated from GES design 39/100 and verified 39/100 with no fourth-loop cap.
Reader Takeaway. For a reader, this is a comparison record more than a model to copy: it reads as a technology ai startup agenda, with the strongest visible signal in future-of-work fit and participation architecture and the biggest open question around follow through and network design. The practical test is whether the published agenda connects the room to post-event continuation and evidence.
Strongest signals: Future-of-Work Fit, Participation Architecture, and Problem Specificity. Weakest signals: Follow Through, Network Design, and Personalization.
How This Agenda Could Improve +
- Add named owners, dates, implementation checkpoints, and a visible post-event continuation path.
- Replace generic networking blocks with designed introductions, ask-offer exchanges, peer groups, or bridge-building rituals.
- Create role-based paths, prepared questions, tailored breakouts, or participant-specific next steps.
Fastest next move: Add named owners, dated next steps, and a visible continuation path before treating the event as outcome-ready.
Role-Specific Reading +
Sponsor lens
Look beyond exposure. Strong sponsor value would show qualified interaction, problem work, buyer learning, customer evidence, or follow-up. The practical sponsor move is to look for structured introductions, buyer-seller fit, and relationship persistence.
Designer lens
The agenda is useful as a pattern sample from icml.cc. Redesign attention should go first to the lowest-scoring pillars; in practice, turn the thinnest agenda blocks into participant work.
Executive lens
Treat the visible agenda as an operating plan. The executive move is to require owners, dates, and evidence before treating the event as strategic. If owners, proof, and follow-through are not visible, the public record does not yet prove strategic movement.
Aggregator lens
Treat the source URL as evidence, not decoration. The data-product move is to label the source boundary clearly before ranking the record before ranking or syndicating the record.
What GES Means Here +
The Gathering Effectiveness Score is a strict 0-100 public-evidence reading of the agenda across eight pillars. It rewards visible participant work, follow-through, transfer, network design, and proof mechanisms more than polish, speaker fame, attendance, or satisfaction.
Visible mechanisms: Participant work, Network design, Learning transfer.
Evidence boundary: Scores reflect visible agenda/source evidence and should not be read as proof of causal event impact.
Limitations, Score Caps, and Review Flags +
Limitations
- No visible follow-up, progress monitoring, or longitudinal tracking.
- No baseline measurement is visible.
Score caps
- No fourth-loop score cap applied.
Review flags
- No source-backed follow-up, validation, baseline, tracking, or impact evidence.
- No tracking, validation, feedback, or impact measurement found in the visible source text.
Is this proof the event worked? +
No. This is a strict public-evidence reading of the agenda. Proof would require baseline, comparison, follow-up, attribution, and impact evidence beyond the listing.
What should a reader inspect first? +
Start with the source URL, then compare the eight pillar scores against the agenda rows. The biggest opportunities usually sit in follow-through, evidence maturity, and participant work.
Why publish weak records? +
Weak records are part of the map. They show where public agendas still describe sessions and speakers more often than outcomes, commitments, transfer, or proof.
How should I use the rows? +
Read the agenda rows as the visible design trace: formats, purposes, and evidence labels show what the public source made inspectable, not everything that happened in the room. This is a source-grounded interpretation of the public agenda record, not a copy of the source, and not an endorsement of the event.
Embed the verified badge +
This record is in the hand-verified gold set. Copy the snippet below to embed the verified badge on your own site.
<a href="https://unitedwetransform.com/events/evt_2025_icml_wca4z_platform_accelerating_legacy_code_modernization_using_ai_agents_87f316"><img src="https://unitedwetransform.com/badge/ges-verified.svg" alt="GES verified by United We Transform" height="40"></a>Where To Go Next
Compare this agenda against other Technology / AI / Startup events scored on the same eight pillars.