IEEE Workshop on AI-Native Networking, Resilience and Forensics - Call for Participation

#AI #Networking #Infrastructure #Datacenters #Hyperscale #Cloud #Edge #Distributed #Resilience #Reliability #Availability #Recovery #Security #Trustworthiness #Observability #Telemetry #Forensics #Automation #Programmability #Scalability #Performance #Transport #Routing #Computing #Inference #Training #Agents #Innovation #Collaboration
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Rapid growth of artificial intelligence is driving a fundamental transformation of communication networks and the Internet. This workshop will explore how networking architectures and infrastructure must evolve to support AI training, inference, autonomous AI agents, and large-scale distributed AI computing. Broad themes of the workshop include AI Networking Challenges, AI-Native Network Architectures, Resilience and Trustworthiness of Distributed AI Systems, AI Infrastructure for Forensics and Cloud Native-AI Infrastructures.

The workshop will bring together researchers, industry practitioners and students to discuss current challenges, innovative solutions and identify future research directions and collaborations toward building the next generation AI-enabled networks and infrastructure.


ONE Author/Presenter is required to attend in person (register for the workshop) and present the work and

DEADLINE for Registration: 20th Oct 2026 

EVENTS

  1. Technical Talks - Students can also submit an abstract of related research projects
  2. Student Poster Session with Best Poster award
  3. Student Hackathon with Best Team Award
  4. Industry Led Panel Discussions
    • Networking for the AI Era? 
      Vidya Wadkar, Verizon; Swapna Chimanchodkar, Independent Researcher , Nirmala Shenoy, RIT 
    • Resilient Infrastructure for Distributed AI: Recovery and Availability
      Chitiz Tayal, Axtria; Sreejith Kaimal, Nirmal Jingar, Wayfair
    • Trustworthy Distributed AI Infrastructure: Security, Observability and Forensics.
      Chitiz Tayal, Axtria; Sreejith Kaimal, C3 AI; Prasanna, M&T Bank

Submit Technical Talks (abstract) 

  • Five Broad Themes:
    1. AI Networking Challenges
    2. AI-Native Network Architectures
    3. Resilience and Trustworthiness of Distributed AI Systems
    4. AI Infrastructure for Forensics
    5. Cloud Native-AI Infrastructures
  • Contact:
  • Deadline: 10th October, Notification 15th October
  • Submit your technical talk details here

Students Posters (submit a short write up)

Student Hackathon (submit a summary)

  • Student Hackathon will provide an opportunity for students to develop and demonstrate innovative solutions addressing emerging challenges in AI-Native Networking, Network Resilience, and Digital/Network Forensics.  Explore topics including AI-assisted network optimization, resilient and self-healing networks, failure recovery and resilience, network telemetry, anomaly detection, vulnerability and forensic analysis. Teams are encouraged to develop a prototype, algorithm, tool, or system concept and present their solution during the workshop. Projects will be recognized based on technical innovation, practical relevance, scalability, resilience, and security. Translate your ideas into solutions for networks of the AI era.
  • Contact:
  • Deadline: 3rd October, Registration Closes 10th October. Notification 13th Oct
  • Register for the Student Hackathon here

Industry Engagement:

  • Industry organizations are invited to nominate representatives from Human Resources, Talent Acquisition, Marketing, Technical Outreach, or related functions to participate in short presentations or informal talks designed to engage and interact with students. These sessions may highlight career and internship opportunities, desired skills, emerging industry needs, company initiatives, and pathways for students to engage with the organization.
  • Respond by 15th Oct.
  • Industry sponsors and participants apply here
  • Coordinators:
  • Industry Sponsors:
    • Lunch
    • Refreshments and coffee/tea breaks
    • Student awards
    • Souvenirs
  • Contributions will be recognized on IEEE Networking for AI Infrastructure Group website https://ainativenetworking.ieee.org. LinkdIn page and IEEE Collabratec®
  • Enquiries: Nirmala Shenoy, nxsvks@rit.edu

  Date and Time

  Location

  Hosts

  Registration


  • Add_To_Calendar_icon Add Event to Calendar

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  • 76, Lomb Memorial Drive
  • Rochester , New York
  • United States 14623
  • Building: Carlson Auditorium
  • Room Number: CAR/076 -1125
  • Click here for Map
  • Contact Event Hosts

  • General Enquiries:  ieee.networking.ai.sig@gmail.com 

     

  • Co-sponsored by IEEE Rochester Networking for AI Infrastructure Group : https://www.linkedin.com/groups/36950078
  • Starts 04 September 2026 08:30 PM UTC
  • Ends 20 October 2026 08:40 PM UTC
  • No Admission Charge

  Speakers

Vidya of Verizon

Topic:

Panel Theme: Networking for the AI Era?

Are existing IP/Ethernet architectures adequate for emerging AI workloads? Which limitations are most significant? Can incremental enhancements address them, or are AI-native/clean-slate approaches needed? What should next-generation AI networks look like?

Biography:

Vidya Wadkar is an AI systems architect and technology leader with over 18 years of experience in building large-scale AI platforms, intelligent automation, and applied machine learning solutions. Her expertise spans multi-agent AI systems, conversational AI, distributed intelligence, and scalable AI architectures, with a strong focus on reliability, governance, and human-centered design. Vidya has published peer-reviewed research, holds a patent on a hybrid multi-agent AI system, serves as a Technical Program Committee member for the IEEE Integrated STEM Education Conference, and actively promotes responsible, ethical, and sustainable AI through research, innovation, and global technology engagement.

Email:

Chitiz of Axtria

Topic:

Panel Theme: Resilience at Scale: Building Robust Infrastructure for Distributed AI

What are the most significant failure modes in distributed AI infrastructure? How should networks respond to failures without disrupting synchronized AI workloads? What roles should redundancy, telemetry, automation, and AI schedulers play?

Biography:

Chitiz Tayal is Senior Director of Data and AI at Axtria, where he leads enterprise data, AI, and analytics transformation programs for global pharmaceutical companies, including Sanofi, Novartis, Bristol Myers Squibb, and GSK. With more than 20 years of experience in AI strategy, enterprise data architecture, and commercial analytics, he specializes in applying AI to healthcare and life sciences. An IEEE Senior Member, Chitiz is an active contributor to the research community, serving on IEEE committees, Technical Program Committees, and as a reviewer for IEEE, Springer, and ACM publications. He is also the author of Data Governance and AI Ethics in Healthcare (2025).

Email:


Sreejith

Topic:

Panel Theme: Trustworthy Distributed AI Infrastructure: Security, Observability, and Forensic Readiness

How can distributed AI infrastructure provide sufficient visibility for detecting and investigating failures or attacks? What telemetry should be collected? How can forensic readiness be designed into AI infrastructure rather than added after deployment?

Biography:

Sreejith Kaimal is a Principal Site Reliability Engineer at C3 AI with over 24 years of experience in distributed systems, cloud infrastructure, site reliability engineering, blockchain, and AI-native platforms. He specializes in designing and operating large-scale, highly available AI and machine learning infrastructure, with previous experience as Lead Blockchain Architect at Hedera Hashgraph. An active researcher, IEEE Senior Member, BCS Fellow, and IETE Fellow, Sreejith has published on AI infrastructure reliability and federated learning, serves on international conference Technical Program Committees, and is recognized with multiple global innovation awards for his contributions to distributed systems and AI infrastructure.

Email:




Agenda

  1. Technical Talks

  2. Student Poster Session with Best Poster award

  3. Student Hackathon with Best Team Award

  4. Industry Led Panel Discussions


General Enquiries:  ieee.networking.ai.sig@gmail.com

Steering Committee:

  • Dr. Nirmala Shenoy, Rochester Institute of Technology, NY
  • Vidya Wadkar, Verizon
  • Chitiz Tayal, Axtria
  • Ketankumar Savajiyani, S&P Global Ratings
  • Prasanna Kumar Kandregula, M&T Bank
  • Alok Tibrewala, Independent Researcher
  • Sreejith Kaimal, C3 AI
  • Jitin Khanna, IBM
  • Ishan Sharma, Google