Responsible Tech Forum

ACM Distinguished Speaker Series
Title: A Hands-On Workshop: Building Advanced AI Applications and Agents in One Hour
Speaker: Mehdi Bahrami – Santa Clara, CA, United States
Date/Time: Friday | 11:30 AM – 1:00 PM

AI systems are rapidly evolving from simple prompt-based tools to autonomous agents capable of perception, reasoning, and action. But how do you move from concept to deployment responsibly and efficiently?

In this ACM Distinguished Speaker Series session, we shift from discussion to construction.
This interactive workshop will guide participants through the design and implementation of advanced AI applications and AI agents using state-of-the-art Large Language Models (LLMs) and Vision Language Models (VLMs). Together, we will explore how modern AI systems are architected, tuned, and deployed in real-world environments.
Rather than focusing on hype, this session emphasizes architecture, design tradeoffs, scalability, and ethical deployment.

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Distinguished Speaker
Mehdi Bahrami
Santa Clara, USA
Dr. Bahrami brings deep expertise across Artificial Intelligence, Machine Learning, Human-Computer Interaction, Computer Vision, Natural Language Processing, Information Systems, Search & Retrieval, Data Mining, and Applied Computing.

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What We Will Build and Explore
Participants will work through core components of advanced AI application design:

• Selecting and working with open-source models
• Understanding Python package requirements and development environments
• Leveraging LLMs and VLMs for: Natural Language Understanding (NLU); Text and image generation; Decision-making workflows; Task automation
• Designing AI agents (language agents vs. vision agents)
• Integrating external data sources
• Fine-tuning and parameter optimization
• Architecture design for scalability and efficiency
• Ethical and responsible deployment considerations

The workshop adapts to audience background, ensuring relevance whether you are an engineer, researcher, product leader, or systems architect.

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Format
This is a guided, hands-on technical workshop.
Technical Framing (15 mins)
AI application architecture and model selection
Live Build + Guided Implementation (45 mins)
Agent design, model integration, tuning, and deployment considerations
Architecture & Ethics Discussion (15 mins)
Scalability, efficiency, and responsible AI tradeoffs
Q&A and Closing (15 mins)

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What to Expect
You will leave with:

• A working mental model for building full-stack AI applications
• Practical understanding of LLM/VLM integration and agent design
• Clarity on tuning, deployment, and scaling considerations
• Insight into responsible AI architecture decisions

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About Responsible Tech
Responsible Tech is an ACM-sponsored forum for practitioners examining how AI systems are designed, deployed, and governed in real-world contexts where trust, safety, and accountability matter.

This event is virtual and will be held from 11:30 AM to 1:00 PM US Central Time (CST).

ACM Distinguished Speaker Series
Title: Advancing AGI: From Training and Fine-Tuning to Interactive Agent Development
Speaker: Mehdi Bahrami – Santa Clara, CA, United States
Date/Time: Friday, April 17 | 11:30 AM – 1:00 PM

As we continue the ACM Distinguished Speaker Series, Month 3 explores one of the most ambitious frontiers in computing: the advancement of Artificial General Intelligence (AGI) and the evolution from model training to fully interactive, adaptive agents.
This session traces the historical foundations of AGI and examines where the field is heading next. Beyond improving model performance, AGI aims to enable systems that can autonomously interact, reason, and perform unseen tasks in complex, dynamic environments.

Dr. Bahrami will guide us through the critical stages of the AGI journey, including:

• Training and fine-tuning large language and vision models
• Optimization and alignment techniques
• Multimodal integration across text, vision, and beyond
• Designing interactive agents that learn, adapt, and reason across domains
• Practical strategies for safety, reliability, and long-term coherence in autonomous systems
• Societal and technical challenges in pursuing fully autonomous AGI

This talk emphasizes both technical depth and responsible development, aligning with the Responsible Tech Forum’s commitment to advancing innovation while addressing ethical, societal, and professional considerations.

Who Should Attend
AI engineers, data scientists, researchers, product leaders, students, and professionals interested in advanced AI systems, agent design, and the responsible evolution of AGI.

What You’ll Gain
By the end of the session, attendees will:

• Understand the architectural and optimization pathways from foundational models to interactive agents
• Gain insight into cutting-edge techniques shaping AGI development
• Develop a deeper perspective on the societal and safety implications of autonomous AI systems
• Be equipped to think critically about building scalable, reliable, and responsible AI agents

This session continues our structured progression from foundations to applied agent systems, thereby building technical rigor while placing responsibility at the center of next-generation AI development.

About Responsible Tech
Responsible Tech is an ACM-sponsored forum for practitioners examining how AI systems are designed, deployed, and governed in real-world contexts where trust, safety, and accountability matter.

This event is virtual and will be held from 11:30 AM to 1:00 PM US Central Time (CST).

Responsible Tech Forum – Month 4 Event
ACM Distinguished Speaker Series
Date: Friday, May 15 | Time: 11:30 AM – 1:00 PM
Format: Distinguished Lecture + Interactive Discussion

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Discovering Bias in Large Language Models (LLMs)
Speaker: Mehdi Bahrami – ACM Distinguished Speaker, Santa Clara, USA

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Overview
As large language models (LLMs) become increasingly embedded in enterprise systems, healthcare, education, and everyday digital tools, it is essential to understand not only their capabilities but also their limitations and risks. While these models enable powerful automation, decision support, and productivity gains, they can also reflect and amplify societal biases, generate misleading information, and introduce unintended harms.

This ACM Distinguished Lecture will explore how bias emerges in LLMs and why it matters for developers, researchers, business leaders, and policymakers. The session will examine both the technical foundations and societal implications of bias in generative AI systems.

Participants will gain a deeper understanding of how bias manifests, how it can be detected, and what practical strategies exist to mitigate it. Through real-world examples and research-backed approaches, this lecture will advance the conversation on building more trustworthy, fair, and accountable AI systems.

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What You Will Learn

• What bias in large language models is and how it originates
• Common forms of bias, stereotypes, hallucinations, and misinformation in LLM outputs
• Current methods and tools for detecting bias in generative AI systems
• Emerging mitigation strategies to improve fairness and accountability
• Practical considerations for deploying responsible and ethical AI in real-world applications

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Why This Matters
As organizations rapidly adopt generative and Agentic AI, ensuring fairness, transparency, and responsible deployment is essential. This session is designed to equip technical professionals, product leaders, researchers, and policymakers with the knowledge needed to recognize risks and implement safeguards.

This lecture directly supports Responsible Tech Forum’s mission to advance responsible, human-centered AI and strengthen the community’s ability to build trustworthy intelligent systems.

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Who Should Attend

• AI engineers and developers
• Data scientists and machine learning practitioners
• Product managers and technology leaders
• Researchers, students, and academics
• Anyone interested in ethical, responsible, and trustworthy AI

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Part of the ACM Distinguished Speaker Series hosted by Responsible Tech Forum.

More Information coming soon!
Techathon details will be provided a month prior to this event.