2026 3rd International Conference on Intelligent Computing and Data Analysis (ICDA 2026)
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About this event
2026 3rd International Conference on Intelligent Computing and Data Analysis (ICDA 2026)
Dates: July 15–17, 2026 | Venue: Paris, France
About ICDA 2026
The 3rd International Conference on Intelligent Computing and Data Analysis (ICDA 2026) invites scholars, researchers, engineers, and practitioners to Paris, France, from July 15–17, 2026. This conference serves as a dynamic platform to explore cutting-edge advancements in intelligent computing, data science, artificial intelligence, machine learning, and related disciplines. ICDA 2026 aims to foster interdisciplinary collaboration, drive innovation, and address global challenges through technological solutions.
Key Focus Areas
- Artificial Intelligence and Machine Learning
- Data Mining and Big Data Analytics
- Natural Language Processing and Computer Vision
- Internet of Things (IoT) and Edge Computing
- Quantum Computing and Advanced Algorithms
- Healthcare Data Analysis and Bioinformatics
- Smart Systems and Autonomous Decision-Making
- Ethics, Security, and Privacy in Data-Driven Technologies
Target Audience
- Academic Researchers and Professors
- Industry Professionals in Tech, Healthcare, and Finance
- Software Developers and Data Scientists
- PhD Candidates and Graduate Students
- Government and Policy Advisors
- Entrepreneurs and Startup Founders
- IT and Engineering Managers
Why Attend ICDA 2026?
• Network with global experts and thought leaders
• Present groundbreaking research to an international audience
• Access workshops, tutorials, and panel discussions on emerging trends
• Explore collaboration opportunities with academia and industry
• Showcase innovative solutions in the exhibition hall
Important Dates
| Event | Date |
|---|---|
| Submission of Papers | March 15, 2026 |
| Notification of Acceptance | April 30, 2026 |
| Early Bird Registration Deadline | May 31, 2026 |
| Conference Dates | July 15–17, 2026 |
Call for Papers
Researchers and practitioners are invited to submit original, unpublished work in all areas of intelligent computing and data analysis. Submissions will undergo a rigorous double-blind peer review process. Accepted papers will be published in the conference proceedings and indexed in major academic databases.
Submission Guidelines: Visit ICDA 2026 Official Website for detailed instructions.
Contact Us
Email: info@icda2026.org
Phone: +33 1 23 45 67 89
Website: https://www.icda2026.org
Data sheet
2026 3rd International Conference on Intelligent Computing and Data Analysis (ICDA 2026) – Event Attendee & Buyer Profile Analysis
Event date: 21 Aug 2026 – 23 Aug 2026
Location: Shenzhen, China
Event status: Upcoming
Research date: 29 Jun 2026
Event Overview
| Event Name | 2026 3rd International Conference on Intelligent Computing and Data Analysis (ICDA 2026) |
| Event Date | 21 Aug 2026 – 23 Aug 2026 |
| Event Status | Upcoming |
| Venue | Venue not publicly confirmed in the supplied material. |
| City | Shenzhen |
| State / Region | Guangdong Province |
| Country | China |
| Organizer | Organizer not publicly confirmed in the supplied material. |
| Official Event Website | Official website not verified from the supplied materials. |
| Event Type | International academic and industry conference |
| Primary Category | IT & Technology |
| Secondary Applicable Categories | Science & Research; Education & Training |
| Audience Reach | Likely international academic and professional reach; exact reach not publicly confirmed. |
| Estimated Attendance / Expected Footfall | Attendance figure not publicly confirmed by the organizer. |
| Attendance Data Reliability | Low at this stage. Core event title, city, country, and dates were supplied by the user; venue, organizer, and attendance metrics require official verification. |
| Main Purpose of Event | Knowledge exchange, paper presentation, research collaboration, technical networking, and discussion of intelligent computing, AI, and data analysis applications. |
About the Event
ICDA 2026 appears to be positioned as the third edition of an international conference focused on intelligent computing and data analysis. Based on the supplied event description, the program scope likely covers artificial intelligence, machine learning, big data analytics, natural language processing, computer vision, IoT, edge computing, algorithms, privacy, and application-driven data science topics.
From a lead generation perspective, this event is more relevant for academic partnerships, research commercialization, applied technology networking, and enterprise innovation outreach than for high-volume trade show buyer-list sales. The strongest attendee groups are likely to include university researchers, applied scientists, technology engineers, innovation teams, data leaders, and solution providers exploring collaboration, publishing, pilot projects, and technical adoption opportunities.
1. Who Attends: Buyers / Attendees
| Buyer / Attendee Segment | Typical Organizations | Buying Role or Influence | Relevance to Exhibitors / Suppliers |
|---|---|---|---|
| Academic researchers and professors | Universities, research institutes, laboratories | Influence software, compute, datasets, instruments, and collaboration decisions | High relevance for research tools, AI platforms, academic publishing, and sponsored projects |
| Data scientists and AI engineers | Technology firms, startups, enterprise innovation teams | Evaluate technical fit, performance, deployment feasibility, and model tooling | High relevance for MLOps, cloud, GPU, data infrastructure, and analytics solutions |
| R&D leaders and lab directors | Corporate R&D centers, national labs, university departments | Influence strategic partnerships, grants, and pilot investments | Strong fit for advanced computing, simulation, and applied research services |
| Industry practitioners in healthcare, finance, manufacturing, and smart systems | Hospitals, fintech firms, industrial companies, IoT solution operators | Assess use cases, ROI, compliance, and implementation needs | Good fit for vertical AI applications and data-driven transformation offerings |
| Graduate students and doctoral candidates | Universities and research programs | Early-stage influence; future adopters and researchers | Useful for talent brand-building and academic ecosystem outreach |
| Technology vendors and solution providers | AI software firms, cloud companies, analytics platforms, hardware providers | Potential sponsors, collaborators, or ecosystem partners rather than end buyers | Relevant for channel partnerships and technical co-marketing |
| Innovation and digital transformation leaders | Large enterprises, public sector innovation units, industrial parks | Influence pilot approval and enterprise adoption roadmaps | High relevance for proof-of-concept services and applied AI deployment |
2. Event Location and Attendee Geographic Origin
| Geographic Area | Likely Attendee Origin | Buyer Concentration | Notes |
|---|---|---|---|
| Shenzhen | Local universities, research parks, AI startups, electronics and software firms | High for applied technology and innovation teams | Shenzhen is a major hardware, software, and innovation hub. |
| Guangdong Province | Regional academic institutions and enterprise R&D teams | High | Likely draw from Guangzhou, Dongguan, Foshan, and other innovation-heavy cities. |
| Greater Bay Area | Shenzhen, Hong Kong, Guangzhou, Macau, and nearby clusters | Very strong for cross-border research and technology networking | Likely strategic corridor for AI, smart systems, and commercialization. |
| Mainland China | National academic, government-backed research, and enterprise participants | Medium to high | National participation is likely if the conference publishes internationally and accepts broad paper submissions. |
| International | Scholars and practitioners from Asia-Pacific and selected global institutions | Moderate, subject to program reputation and visa accessibility | The event title suggests international positioning, but current-year country mix is not publicly confirmed. |
3. Audience Reach
| Reach Level | Assessment | Explanation |
|---|---|---|
| Global | Primary classification | The event is presented as an international conference and the subject matter is globally relevant to AI, data analysis, and intelligent computing communities. |
| Regional | Secondary practical reach | In commercial terms, the strongest in-person concentration is likely to come from Shenzhen, Guangdong, and the Greater Bay Area. |
4. Sample Buyer Companies and Websites
| Buyer Company / Organization | Buyer Type | Why It Is Relevant | Website | Best Job Titles to Target | Evidence Level |
|---|---|---|---|---|---|
| Southern University of Science and Technology | University / research buyer | Shenzhen-based institution with strong engineering and computing relevance | sustech.edu.cn | Professor, Lab Director, Dean, Research Administrator, IT Director | Strong Market Fit, Attendance Not Confirmed |
| Shenzhen University | University / research buyer | Local academic institution likely relevant to conference participation and collaboration | szu.edu.cn | Department Chair, Professor, Research Center Director, Procurement Lead | Strong Market Fit, Attendance Not Confirmed |
| The Chinese University of Hong Kong, Shenzhen | University / research buyer | Active in data science, AI, and cross-border academic collaboration | cuhk.edu.cn | Professor, Research Scientist, Lab Operations Manager, CIO | Strong Market Fit, Attendance Not Confirmed |
| Harbin Institute of Technology, Shenzhen | University / engineering research buyer | Strong fit for intelligent systems, engineering, and applied computing topics | hitsz.edu.cn | Professor, Research Director, Dean, Technical Lab Manager | Strong Market Fit, Attendance Not Confirmed |
| Tsinghua Shenzhen International Graduate School | Graduate school / research buyer | Relevant for advanced analytics, smart systems, and interdisciplinary computing research | sigs.tsinghua.edu.cn | Professor, Program Director, Research Manager, Innovation Lead | Strong Market Fit, Attendance Not Confirmed |
| Huawei | Enterprise technology buyer / R&D organization | Major AI, cloud, telecom, and enterprise digital transformation stakeholder in the region | huawei.com | AI Director, Chief Scientist, Cloud Architect, R&D Director, Procurement Manager | Strong Market Fit, Attendance Not Confirmed |
| Tencent | Enterprise technology buyer | Strong relevance across AI, cloud, data platforms, and applied machine learning | tencent.com | Head of Data Science, AI Product Director, Research Engineer Lead, Innovation Manager | Strong Market Fit, Attendance Not Confirmed |
| Ping An Technology | Enterprise AI and analytics buyer | Relevant for fintech, healthtech, risk analytics, and enterprise AI deployment | pingan.com | Chief Data Officer, Analytics Director, ML Engineering Manager, Innovation Director | Strong Market Fit, Attendance Not Confirmed |
| ZTE | Enterprise technology buyer / telecom R&D | Relevant for AI, edge computing, networking, and smart infrastructure use cases | zte.com.cn | CTO Office, R&D Director, Data Platform Lead, Technical Procurement Manager | Strong Market Fit, Attendance Not Confirmed |
| Shenzhen Institute of Artificial Intelligence and Robotics for Society | Research institute / applied innovation buyer | Highly aligned with intelligent computing, robotics, and data-driven applications | airs.cuhk.edu.cn | Institute Director, Research Scientist, Program Manager, Partnerships Lead | Strong Market Fit, Attendance Not Confirmed |
Note: No current-year attendee, exhibitor, speaker, or sponsor list was publicly verified from the supplied materials. The organizations above are prospecting targets with strong market fit to the event theme and host city, not confirmed participants.
5. Job Profiles, Industries and Event Type
| Priority | Job Title / Function | Department | Seniority Level | Why This Role Matters |
|---|---|---|---|---|
| 1 | Professor / Principal Investigator | Research / Academic | Senior | Key influencer for collaboration, software, datasets, and lab adoption decisions |
| 2 | Research Director | R&D | Director | Owns applied research direction and external partnership priorities |
| 3 | Chief Data Officer | Data / Analytics | C-Level | Relevant for enterprise analytics strategy and data platform investment |
| 4 | Head of AI / AI Director | AI / Innovation | Director / VP | Evaluates new algorithms, models, infrastructure, and research partnerships |
| 5 | Data Science Manager | Analytics / Engineering | Manager | Practical evaluator of deployment tools, workflows, and technical fit |
| 6 | Machine Learning Engineering Manager | Engineering | Manager | Strong buyer signal for MLOps, compute, data pipelines, and experimentation stacks |
| 7 | CTO | Technology | C-Level | Strategic technology authority for enterprise and startup adoption |
| 8 | IT Director | IT | Director | Relevant for infrastructure, systems integration, security, and deployment readiness |
| 9 | Innovation Director | Strategy / Innovation | Director | Good target for pilot projects, partnerships, and commercialization outreach |
| 10 | Procurement Manager | Procurement | Manager | Relevant where software licenses, hardware, lab tools, and cloud services are purchased centrally |
| Priority | Apollo Industry | Why It Fits the Event | Best Buyer Use Case |
|---|---|---|---|
| 1 | Information Technology & Services | Core fit for AI, analytics, software, and technical services | Enterprise AI adoption and consulting |
| 2 | Computer Software | Strong alignment with ML, analytics, visualization, and data tools | MLOps, model management, analytics platforms |
| 3 | Research | Academic and institutional research is a core conference audience | Research tools and collaboration platforms |
| 4 | Higher Education | Universities are likely primary participants | Lab software, compute resources, academic partnerships |
| 5 | Computer Hardware | Relevant to compute, accelerators, edge devices, and systems | High-performance compute and AI hardware |
| 6 | Telecommunications | Strong regional relevance in Shenzhen and edge/IoT themes | Network intelligence and edge analytics |
| 7 | Industrial Automation | Intelligent computing often maps to smart manufacturing and automation | Predictive analytics and machine intelligence for operations |
| 8 | Electrical/Electronic Manufacturing | Shenzhen ecosystem relevance for embedded, edge, and intelligent devices | AI-enabled device and manufacturing optimization |
| 9 | Hospital & Health Care | The supplied description references healthcare data analysis and bioinformatics | Clinical analytics and medical AI use cases |
| 10 | Financial Services | Data science and intelligent decision systems are highly relevant in finance | Risk analytics, fraud detection, predictive modeling |
6. Estimated Attendance
| Metric | Figure | Status | Source / Basis | Notes |
|---|---|---|---|---|
| Estimated total footfall | Attendance figure not publicly confirmed by the organizer. | Unconfirmed | No verified official attendance data available in supplied materials | Do not use for list-volume commitments without official confirmation. |
| Exhibitor count | Not publicly confirmed | Unconfirmed | Conference appears content-led rather than trade-floor-led | This may have sponsors or poster/demo sessions instead of a large expo hall. |
| Buyer count | Not publicly confirmed | Unconfirmed | No verified attendee segmentation available | Likely mixed academic and practitioner audience rather than pure procurement attendance. |
| Speaker count | Not publicly confirmed | Unconfirmed | No verified program agenda supplied | Would typically include keynote speakers, authors, session chairs, and panelists. |
| Sponsor count | Not publicly confirmed | Unconfirmed | No verified sponsor page available in supplied materials | Potential sponsorship opportunities may exist for technical vendors. |
| Historical attendance | Historical attendance not publicly confirmed from supplied materials | Historical / prior-year evidence unavailable | No prior-year official report provided | Prior-year participation evidence. Not a confirmed attendee list for the current edition. |
7. Key Focus Areas and Buyer Engagement
| Focus Area | Typical Buyer Need | Buyer Engagement Opportunity | Relevant Supplier Offering |
|---|---|---|---|
| Artificial Intelligence and Machine Learning | Model development, experimentation, deployment, and evaluation | Technical demos, research collaboration, pilot discussions | AI platforms, MLOps, model optimization, GPU infrastructure |
| Data Mining and Big Data Analytics | Scalable analytics, data integration, and insight generation | Use-case mapping for enterprise and academic data environments | Data lakes, analytics platforms, ETL, BI, data engineering services |
| Computer Vision and NLP | Pattern recognition, automation, and language processing | Prototype reviews, benchmark comparisons, application partnerships | Vision models, speech/NLP stacks, annotation tools, inference engines |
| IoT and Edge Computing | Low-latency processing, smart devices, and connected operations | Partnerships with telecom, hardware, and smart-device teams | Edge AI software, embedded compute, device analytics |
| Security, Privacy, and Ethics | Governance, safe deployment, and data protection | Advisory conversations and policy-aware solution positioning | Privacy tooling, governance frameworks, secure compute, compliance support |
| Healthcare Data Analysis and Bioinformatics | Clinical analytics, diagnostics support, and research modeling | Cross-sector applied AI outreach | Medical AI, analytics software, scientific computing services |
Lead Quality Assessment
| Factor | Assessment | Explanation |
|---|---|---|
| Buyer relevance | Medium | Good for research, innovation, and technical adoption leads; less suitable for pure procurement-driven list building. |
| Decision-maker availability | Medium | Academic and technical decision influencers are likely present; direct commercial budget owners may be fewer than at a trade expo. |
| Data collection potential | Low to Medium | No verified attendee or exhibitor directory was available from supplied materials. |
| Apollo targeting potential | High | Theme-based targeting is strong across AI, software, higher education, telecom, and research organizations. |
| Geographic targeting potential | High | Shenzhen and the Greater Bay Area provide a concentrated prospect universe. |
| Best outreach approach | High | Use thought leadership, collaboration offers, benchmarking content, and pilot-oriented messaging rather than generic sales copy. |
| Overall lead quality | Medium | High thematic relevance, but limited verified participant data reduces certainty for attendee-list monetization. |
| Best use case | High | Best for targeted ABM, research outreach, academic partnerships, AI platform prospecting, and regional tech ecosystem engagement. |
| Limitations / risks | High caution | Supplied reference text conflicts with the supplied city/date details, indicating verification risk. Venue, organizer, and official website must be confirmed before campaign launch. |
Apollo.io Targeting Recommendation
| Filter Type | Recommended Filters | Purpose |
|---|---|---|
| Apollo industries | Information Technology & Services; Computer Software; Research; Higher Education; Telecommunications; Computer Hardware; Industrial Automation; Electrical/Electronic Manufacturing; Financial Services; Hospital & Health Care | Align prospecting with likely event-attendee sectors |
| Departments | Engineering; Information Technology; Research; Education; Data/Analytics; Innovation; Operations; Procurement | Reach technical and budget-influencing teams |
| Seniority | C-Level; VP; Director; Head; Manager; Partner; Professor equivalent where searchable | Focus on decision-makers and implementation owners |
| Job titles | Chief Data Officer, CTO, AI Director, Director of Research, Data Science Manager, Machine Learning Engineer Manager, Professor, Principal Investigator, Innovation Director, IT Director, Lab Director, Procurement Manager | Pinpoint technically aligned buyers and influencers |
| Geography | Shenzhen; Guangdong; Hong Kong; Greater Bay Area; Mainland China; APAC for expanded outreach | Build local-first and regional expansion lists |
| Employee size | 51–200; 201–500; 501–1,000; 1,001–5,000; 5,001+ | Cover startups, scale-ups, major enterprises, and institutions |
| Keywords | artificial intelligence, machine learning, data analysis, intelligent computing, computer vision, NLP, big data, analytics, edge computing, IoT, data mining, bioinformatics | Capture thematic relevance where job titles alone are too broad |
| Technologies | Cloud AI stacks, data platforms, analytics tooling, edge infrastructure where searchable | Refine accounts already investing in technical capability |
| Revenue range | Mid-market to enterprise for commercial accounts; not applicable to all universities | Improve prioritization for paid pilots and larger contracts |
| Company type | Private; Public; Educational; Research institute | Balance enterprise and institutional outreach |
Suggested Apollo Search Logic: ("artificial intelligence" OR "machine learning" OR "data analysis" OR "intelligent computing" OR "computer vision" OR "NLP" OR "big data" OR "edge computing") AND (Director OR Head OR CTO OR "Chief Data Officer" OR Professor OR "Research Director" OR "Data Science Manager") AND (Shenzhen OR Guangdong OR Hong Kong OR China).
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Sources & Verification Notes
| Source | Type | What It Verified | Reliability |
|---|---|---|---|
| User-supplied event details | Provided brief | Event title, Shenzhen location, China country, and dates 21–23 Aug 2026 | Medium |
| User-supplied reference description | Provided reference text | Topic scope including AI, machine learning, big data, NLP, IoT, edge computing, healthcare analytics, ethics, security, and privacy | Medium |
| User-supplied reference description conflict note | Consistency check | Reference text mentions Paris, France and 15–17 Jul 2026, which conflicts with the supplied Shenzhen and Aug 2026 details | High importance verification note |
| Official organizer / event site | Primary source | Not verified from supplied materials | Pending |
| Venue website | Primary source | Venue not publicly confirmed in supplied materials | Pending |
Suitability note for B2B attendee list building: Moderately suitable for niche, high-intent technical and research lead generation; not yet suitable for high-confidence attendee list sales until the official website, organizer, venue, and participant evidence are verified.
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Tell us your work email and our AI instantly builds a buyer list matched to 2026 3rd International Conference on Intelligent Computing and Data Analysis (ICDA 2026) — the best‑fit companies to target, the exact decision‑maker job titles, and the industry filters that fit what you sell.
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