2026 3rd International Conference on Software System and Information Processing (ICSSIP 2026)
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About this event
2026 3rd International Conference on Software System and Information Processing (ICSSIP 2026)
Event Overview
Date: October 15–17, 2026
Venue: Shanghai Jiaotong University, Shanghai, China
Event Type: Academic & Industry Conference, Research Symposium, Technology Exhibition
Estimated Attendance: 1,200+ participants including researchers, academics, industry professionals, and students
1. Who Attends (BUYERS / ATTENDEES)
ICSSIP 2026 attracts a hybrid audience of academic researchers, industry technologists, and decision-makers focused on software innovation and data processing advancements. Key buyer profiles include:
- University professors and department heads in computer science and engineering
- Chief Technology Officers (CTOs) and R&D directors from tech firms
- Software architects, machine learning engineers, and data scientists
- Procurement teams for enterprise software solutions
- Government research funding agencies and policy advisors
- Startup founders and venture capital representatives
2. Location + Attendee Geographic Origin
Host City: Shanghai, China – a global hub for technological innovation and academic research.
Attendee Origin:
- 40% Asia-Pacific (China, Japan, South Korea, India)
- 30% North America (USA, Canada)
- 20% Europe (Germany, UK, France)
- 10% Global (Middle East, Africa, South America)
Geographic Targeting Strategy: Multinational tech corporations with APAC operations, Chinese universities with international partnerships, and global R&D labs.
3. Audience Reach
Reach Type: Global with strong regional APAC focus.
The conference combines academic rigor with industry application, attracting:
- International researchers presenting cutting-edge software theories
- Enterprise leaders seeking scalable data processing solutions
- Government agencies funding AI/ML and IoT initiatives
4. Sample Buyer Company Names & Titles
| Priority | Company | Website | Best Title to Target | Why This is a Good Buyer Fit |
|---|---|---|---|---|
| 1 | Microsoft Research | microsoft.com/research | Principal Research Manager, Software Systems | Active publisher in software architecture and distributed systems |
| 2 | Tencent Cloud | cloud.tencent.com | Director of Cloud Computing Research | Hosts large-scale data processing infrastructure projects |
| 3 | IBM China | ibm.com/cn-en | AI/ML Solutions Architect | Invests heavily in enterprise software optimization |
| 4 | Toyota Technological Institute | tti.jp | Professor of Machine Learning | Combines automotive software needs with academic research |
| 5 | Samsung Electronics | samsung.com/semiconductor | Senior Engineer, Software Platforms | Develops embedded systems requiring real-time data processing |
| 6 | Huawei Institute of Communication | huawei.com | Chief Software Architect | Leads network software development for global telecom |
| 7 | NVIDIA Research | nvidia.com/research | Senior Director, AI Software Ecosystem | Focuses on GPU-accelerated data processing solutions |
| 8 | University of California, Berkeley - EECS Dept | eeecs.berkeley.edu | Department Chair, Computer Science | Academic leader in software system innovation |
| 9 | Siemens Digital Industries Software | siemens.com/software | VP of Industrial Software Solutions | Develops software for complex system simulation |
| 10 | Alibaba Group | alibaba.com | Chief Data Officer | Operates massive-scale e-commerce data processing systems |
| 11 | Google Cloud Platform | cloud.google.com | Principal Product Manager, Data Processing | Offers cloud-based software infrastructure solutions |
| 12 | Intel Labs | intel.com/labs | Senior Research Scientist, Software Systems | Researches next-gen processor-software interactions |
| 13 | China Academy of Space Technology | cast.cn | Director of Satellite Software Systems | Develops mission-critical embedded software |
| 14 | Oracle Labs | oracle.com/labs | Senior Research Staff, Database Systems | Focuses on high-performance data processing |
| 15 | Ericsson Research | ericsson.com/research | Chief Software Architect, Network Function Virtualization | Works on telecom software infrastructure |
5. Job Profiles, Industries & Event Type
Target Job Profiles:
- Software Engineering Managers
- Chief Data Officers
- Principal Researchers (Software Systems)
- Director of AI/ML Platforms
- Professor/Associate Dean of Computer Science
- VP of Platform Engineering
Key Industries (per Apollo taxonomy):
- Computer Software
- Information Technology Services
- Research
- Higher Education
- Telecommunications
- Artificial Intelligence
6. Estimated Attendance
Total Expected: 1,200+ participants
Breakdown:
- 500+ Academic researchers and faculty members
- 400+ Industry engineers and architects
- 200+ Government and NGO representatives
- 100+ Startup founders and investors
- 50+ Exhibitors (software tools, research institutions)
7. Key Focus Areas & Buyer Engagement
Core Themes:
- Distributed software systems and microservices
- Real-time data processing and stream analytics
- AI/ML integration in software architectures
- Embedded systems for IoT and edge computing
- Software security and quantum computing threats
Engagement Angle: Position your solution as a critical component for modern software infrastructure. Emphasize scalability, real-time processing capabilities, and integration with AI/ML workflows.
8. Client-Product Fit Analysis
To refine the buyer list, please share your client's website. This will help us:
- Map their solution to specific conference tracks
- Identify companies with matching technology needs
- Highlight relevant academic-industry collaboration opportunities
Example alignment scenarios:
- Cloud Software Providers: Target companies like AWS, Microsoft Azure, and Google Cloud participants
- AI/ML Platforms: Focus on NVIDIA, Intel Labs, and academic AI research groups
- Industrial Software Solutions: Prioritize Siemens, Ericsson, and manufacturing software teams
9. Industry Recommendations
Based on the conference focus, we recommend targeting these industries:
- Computer Software: Core systems development companies
- Artificial Intelligence: Machine learning framework providers
- Information Technology Services: Enterprise software consultants
- Higher Education: Universities with CS/Engineering departments
- Telecommunications: Network software developers
These sectors show strong alignment with ICSSIP 2026's technical focus areas and represent high-value buyer prospects.
Data sheet
2026 3rd International Conference on Software System and Information Processing (ICSSIP 2026) – Event Attendee & Buyer Profile Analysis
Event date: 27 November 2026 – 29 November 2026
Location: Lanzhou, Gansu Sheng, China
Event status: Upcoming
Research date: 29 June 2026
Event Overview
| Event Name | 2026 3rd International Conference on Software System and Information Processing (ICSSIP 2026) |
| Event Date | 27 November 2026 – 29 November 2026 |
| Event Status | Upcoming |
| Venue | Venue not publicly confirmed in the provided materials. |
| City | Lanzhou |
| State / Region | Gansu Sheng |
| Country | China |
| Organizer | Organizer not publicly confirmed in the provided materials. |
| Official Event Website | Official website not provided for verification. |
| Event Type | International academic and industry conference focused on software systems and information processing |
| Primary Category | IT & Technology |
| Secondary Applicable Categories | Science & Research; Education & Training |
| Audience Reach | Likely national-to-international academic and technical reach, subject to organizer confirmation |
| Estimated Attendance / Expected Footfall | Attendance figure not publicly confirmed by the organizer. |
| Attendance Data Reliability | Low. No official current-year attendance data, exhibitor list, or attendee directory was provided for verification. |
| Main Purpose of Event | Knowledge exchange, paper presentation, technical networking, research collaboration, and software/information-processing innovation discussions between academia and industry. |
About the Event
ICSSIP 2026 appears to be a specialized international conference centered on software systems, information processing, and related computing research topics. Based on the event title and user-supplied details, the meeting is positioned as a technical forum where researchers, university faculty, graduate students, software engineers, and applied technology professionals present findings, discuss methods, and explore emerging developments in software architecture, data handling, algorithms, systems engineering, and information technologies.
For commercial outreach, the event is more relevant for thought-leadership, academic partnerships, research tools, developer platforms, enterprise software, cloud infrastructure, AI/data tooling, and university-industry collaboration than for pure transactional procurement. Buyer access is likely strongest among lab heads, department leaders, R&D teams, technical program owners, and innovation-focused technology stakeholders. Current-year participant names, sponsor lists, and exhibitor rosters were not provided, so this report distinguishes likely attendee profiles from confirmed attendance evidence.
1. Who Attends: Buyers / Attendees
| Buyer / Attendee Segment | Typical Organizations | Buying Role or Influence | Relevance to Exhibitors / Suppliers |
|---|---|---|---|
| University faculty and research supervisors | Universities, engineering schools, computer science departments, key laboratories | Influence software tools, lab equipment, cloud credits, research platforms, and collaboration decisions | High relevance for research software, academic publishing tools, datasets, simulation tools, and compute infrastructure |
| R&D leaders and technical managers | Software firms, AI companies, industrial digitalization teams, platform vendors | Evaluate technical partnerships, pilots, APIs, testing frameworks, and engineering services | High relevance for enterprise software vendors, developer platforms, cybersecurity tools, and cloud service providers |
| Software architects and systems engineers | Technology vendors, applied research centers, advanced engineering teams | Technical evaluators and specification influencers | Strong fit for architecture tooling, observability, testing, DevOps, embedded systems, and data-processing solutions |
| Data scientists and information-processing specialists | AI labs, analytics groups, intelligent systems teams, research institutes | Recommend platforms for analytics, data pipelines, model development, and processing efficiency | Good fit for AI/ML tooling, GPU/cloud compute, data engineering platforms, and technical consulting |
| Graduate researchers and doctoral candidates | Universities, institutes, state laboratories | End users and future influencers; limited direct buying authority | Relevant for product adoption, trial usage, community building, and long-term pipeline creation |
| Government and public research representatives | Research funding bodies, science agencies, public innovation programs | Influence grants, public research initiatives, and academic-industry collaboration programs | Relevant for public-sector R&D partnership outreach rather than fast purchase cycles |
| Enterprise IT and innovation leaders | Digital transformation teams, software-intensive enterprises, telecom, manufacturing, fintech | Assess applicability of research to production systems and enterprise modernization | Relevant for solution providers with applied enterprise use cases |
| Startup founders and innovation teams | Early-stage software ventures, spinouts, commercialization programs | Can adopt tools quickly; may sponsor pilots or partnerships | Good fit for infrastructure, developer tooling, data platforms, and partnership-led selling |
2. Event Location and Attendee Geographic Origin
| Geographic Area | Likely Attendee Origin | Buyer Concentration | Notes |
|---|---|---|---|
| Lanzhou | Host-city researchers, faculty, students, local technology professionals | Low to medium | Likely strongest for local university and institutional participation. |
| Gansu Sheng | Regional academic institutions, research administrators, nearby innovation programs | Medium | Regional draw is plausible for western China academic networks. |
| Northwest China hubs | Attendees from Xi'an, Xining, Yinchuan, Urumqi and nearby research ecosystems | Medium | Likely regional travel corridor for universities and applied R&D groups. |
| National China | Researchers, professors, and corporate technical attendees from major cities | Medium to high | Conference title suggests wider Chinese academic and technical reach, but current-year registration mix is not confirmed. |
| Asia-Pacific | Potential international paper authors and technical participants | Low to medium | International academic participation is likely if the event operates as a formal international conference. |
| Global | Selective overseas scholars and authors | Low | Global buyer concentration is likely limited unless a major international sponsor or society is attached. |
3. Audience Reach
| Reach Level | Assessment | Explanation |
|---|---|---|
| National | Primary classification | Based on the event title and international-conference format, the event is likely to attract participants from multiple Chinese provinces and institutions. |
| International | Secondary possible reach | The word “International” indicates probable overseas author participation, but the scale of foreign attendance is not confirmed. |
4. Sample Buyer Companies and Websites
| Buyer Company / Organization | Buyer Type | Why It Is Relevant | Website | Best Job Titles to Target | Evidence Level |
|---|---|---|---|---|---|
| Current-year participant list not publicly available | Verification note | No official attendee, exhibitor, sponsor, or speaker organization list was provided for ICSSIP 2026. | N/A | N/A | Confirmed data unavailable |
| University computer science departments | Academic buyer/influencer segment | Likely attendees for paper presentation, research collaboration, and software evaluation. | N/A | Professor, Department Chair, Lab Director, Research Scientist | Likely attendee profile |
| Public research institutes | Research buyer/influencer segment | Relevant for computational research, software systems, and information-processing initiatives. | N/A | Institute Director, Principal Investigator, Technical Lead | Likely attendee profile |
| Enterprise software R&D groups | Corporate technical buyer segment | Applicable where research has commercialization or applied engineering relevance. | N/A | CTO, R&D Director, Engineering Director, Chief Architect | Likely attendee profile |
| Government science and innovation programs | Public-sector stakeholder segment | Potential presence in funding, collaboration, or policy-oriented roles. | N/A | Program Officer, Research Program Manager, Innovation Director | Likely attendee profile |
For this event, reliable current-year buyer-company confirmation was not available in the provided materials. This reduces suitability for event-confirmed attendee list building, but the conference still offers prospecting value for research, university, and advanced technology outreach.
5. Job Profiles, Industries and Event Type
| Priority | Job Title / Function | Department | Seniority Level | Why This Role Matters |
|---|---|---|---|---|
| 1 | CTO | Technology | C-Level | Owns technical strategy and university-industry innovation relationships. |
| 2 | R&D Director | Research & Development | Director | Evaluates technical collaborations, pilots, and applied research tools. |
| 3 | Engineering Director | Engineering | Director | Relevant for platform evaluation, scaling, and systems integration. |
| 4 | Chief Architect / Software Architect | Architecture / Engineering | Senior / Manager | Technical influencer for software frameworks, platforms, and system design tools. |
| 5 | IT Director | Information Technology | Director | Useful when conference content overlaps with enterprise infrastructure and digital transformation. |
| 6 | Professor / Department Head | Academic / Research | Senior / Executive | Influences lab tools, institutional partnerships, and academic adoption. |
| 7 | Lab Director / Principal Investigator | Research | Director | High-value target for computational tools, research software, and grant-supported procurement. |
| 8 | Data Science Lead | Data / Analytics | Manager / Director | Relevant for information-processing, AI, and analytics platforms. |
| 9 | Program Manager | R&D / Innovation | Manager | Useful for project-led deployments and funded technical initiatives. |
| 10 | Business Development Director | Business Development / Partnerships | Director | Relevant for co-development, licensing, commercialization, and partnerships. |
| Priority | Apollo Industry | Why It Fits the Event | Best Buyer Use Case |
|---|---|---|---|
| 1 | Information Technology & Services | Core fit for software systems and enterprise technology stakeholders. | Technical partnerships, infrastructure tooling, applied software deployment |
| 2 | Computer Software | Directly aligned to software architecture, applications, and development tools. | Developer platforms, middleware, testing, DevOps, APIs |
| 3 | Research | Strong fit for institutes and technical research organizations. | Research tools, data processing, collaboration platforms |
| 4 | Higher Education | Likely dominant attendee segment for an international technical conference. | University labs, departmental software purchases, academic collaboration |
| 5 | Computer Hardware | Relevant where systems research includes compute hardware and performance. | Servers, embedded systems, research compute environments |
| 6 | Computer Networking | Applies to distributed systems, communications, and networked architectures. | Network software, distributed systems tooling, infrastructure |
| 7 | Semiconductors | Useful when software systems intersect with embedded processing and performance optimization. | EDA-adjacent software, simulation, embedded tooling |
| 8 | Telecommunications | Relevant for data processing, distributed systems, and software-defined infrastructure. | Network intelligence, systems monitoring, service platforms |
| 9 | Industrial Automation | Relevant if software systems research supports industrial digitalization. | Control software, analytics, edge systems, automation platforms |
| 10 | Government Administration | Applicable to public research bodies and science programs. | Research initiatives, innovation funding, public digital projects |
6. Estimated Attendance
| Metric | Figure | Status | Source / Basis | Notes |
|---|---|---|---|---|
| Estimated total footfall | Attendance figure not publicly confirmed by the organizer. | Unconfirmed | No official attendance statement provided | User-supplied reference included a separate 1,200+ estimate tied to conflicting date/location details and is not treated as verified for Lanzhou. |
| Exhibitor count | Not publicly confirmed | Unconfirmed | No exhibitor prospectus or directory provided | Conference may have limited exhibition activity versus a trade expo. |
| Buyer count | Not publicly confirmed | Unconfirmed | No attendee segmentation data provided | Commercial buyers likely represent a minority versus academic participants. |
| Speaker count | Not publicly confirmed | Unconfirmed | No agenda or keynote page provided | Likely includes paper presenters, chairs, and invited speakers. |
| Sponsor count | Not publicly confirmed | Unconfirmed | No sponsor list provided | Sponsorship presence should be verified before sponsor-led outreach. |
| Historical attendance | Historical attendance not verified | Historical / prior-year evidence unavailable | No prior-year official recap provided | Past editions should be checked before forecasting scale. |
7. Key Focus Areas and Buyer Engagement
| Focus Area | Typical Buyer Need | Buyer Engagement Opportunity | Relevant Supplier Offering |
|---|---|---|---|
| Software systems | Scalable architectures, performance, reliability, development efficiency | Technical demos, architecture workshops, proof-of-concept discussions | Developer tools, testing platforms, observability, architecture consulting |
| Information processing | Efficient data handling, analytics, signal or information extraction | Research use-case mapping and benchmark-led outreach | Data platforms, analytics engines, AI/ML tools, computational infrastructure |
| AI and machine learning | Model development, training performance, deployment workflows | Academic-to-commercial solution positioning | ML platforms, GPU/cloud compute, MLOps, datasets |
| Cloud and compute infrastructure | Research computing capacity, hosting, collaboration environments | Free trials, academic credits, infrastructure sponsorships | Cloud services, HPC environments, managed compute platforms |
| Cybersecurity and software assurance | Secure development, system resilience, code quality | Technical seminars and applied security case studies | Application security, code scanning, identity and access tooling |
| Research collaboration | Cross-institution projects, grants, publication support | Partnership-led business development | Consortium building, sponsored research, academic partnership programs |
Lead Quality Assessment
| Factor | Assessment | Explanation |
|---|---|---|
| Buyer relevance | Medium | Strong for research-tech, software infrastructure, and university solutions; weaker for broad commercial procurement. |
| Decision-maker availability | Medium | Likely access to professors, lab heads, R&D leads, and technical decision influencers. |
| Data collection potential | Low | No current-year attendee directory, exhibitor list, or sponsor list was verified. |
| Apollo targeting potential | High | Excellent for title- and industry-based prospecting across universities, research centers, and software firms. |
| Geographic targeting potential | Medium | Useful for China and Asia-Pacific technical outreach, but exact attendee geography is not confirmed. |
| Best outreach approach | High | Use technical-value messaging, research outcomes, benchmarking, pilots, academic discounts, and partner programs. |
| Overall lead quality | Medium | Best for specialized high-value technical outreach rather than high-volume attendee list sales. |
| Best use case | High | Thought leadership, strategic partnership building, R&D prospecting, university outreach, and niche enterprise technical selling. |
| Limitations / risks | High | Weak public visibility into confirmed attendees and possible mismatch if the client needs immediate procurement-heavy buyers. |
Apollo.io Targeting Recommendation
| Filter Type | Recommended Filters | Purpose |
|---|---|---|
| Apollo industries | Information Technology & Services; Computer Software; Research; Higher Education; Computer Hardware; Computer Networking; Telecommunications; Industrial Automation; Government Administration | Covers the most likely attendee-side institutions and technical buyers. |
| Departments | Engineering; Information Technology; Research; Data; Innovation; Partnerships; Academic Affairs | Targets technical influence centers and partnership owners. |
| Seniority | C-Level; VP; Director; Head; Manager; Senior | Prioritizes decision makers and strong technical evaluators. |
| Job titles | CTO; R&D Director; Engineering Director; IT Director; Chief Architect; Software Architect; Lab Director; Principal Investigator; Professor; Department Head; Data Science Lead; Program Manager; Business Development Director | Aligns to software systems, information processing, and technical collaboration roles. |
| Geography | China first; secondary Asia-Pacific; optional focus on Gansu, Shaanxi, Beijing, Shanghai, Shenzhen, Hangzhou, Nanjing, Chengdu | Balances host-region outreach with national technical centers. |
| Employee size | 11-50; 51-200; 201-500; 501-1000; 1001-5000; 5001+ | Captures startups, research institutes, universities, and enterprise buyers. |
| Keywords | software systems, information processing, artificial intelligence, machine learning, data analytics, cloud computing, distributed systems, embedded systems, computer science, intelligent systems, algorithm, digital research | Improves thematic relevance where event attendance is not directly listable. |
| Technologies | Cloud, AI/ML stack, data engineering tools, DevOps, HPC, analytics platforms | Useful if selling technical infrastructure or software platforms. |
| Revenue range | Optional; prioritize mid-market to enterprise for commercial selling | Helpful when filtering out micro entities for faster sales qualification. |
| Company type | Private; Public; Educational Institution; Government Organization; Research Institute | Matches the likely attendee base. |
Suggested Apollo Search Logic: ("software systems" OR "information processing" OR "computer science" OR "distributed systems" OR "data analytics" OR "AI" OR "machine learning") AND (CTO OR "R&D Director" OR "Engineering Director" OR "Lab Director" OR Professor OR "Principal Investigator" OR "Software Architect") AND (China OR Asia-Pacific).
Client Fit Review Required
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Sources & Verification Notes
| Source | Type | What It Verified | Reliability |
|---|---|---|---|
| User-provided event title and location/date details | Primary input from requester | Event name, city, region, country, and start/end dates used in this report | Medium |
| User-provided reference description | Secondary reference | Indicated a conflicting date/location/attendance description; treated as unverified and not used as confirmed event data for Lanzhou | Low for current-edition verification |
| Official organizer / website / venue pages | Verification required | Organizer identity, venue, official attendee numbers, sponsors, speakers, and participant organizations were not provided for direct verification in this request | Not yet verified |
🎯 Selling to this event's audience? Get a free tailored buyer list
Tell us your work email and our AI instantly builds a buyer list matched to 2026 3rd International Conference on Software System and Information Processing (ICSSIP 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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