At the forefront of AI strategy…
At the forefront of AI strategy…
Spotlight: News & Events
Stay informed with the latest Industry updates and AI news from around the world. From cutting-edge advancements in AI to impactful projects shaping the future, this is your hub for staying ahead in the world of transformative solutions. Explore what’s new today!
A quarterly briefing designed for directors and trustees, equipping boards to navigate AI’s strategic opportunities, governance duties, and emerging risks.
This quarterly briefing gives directors and trustees a focused, board-level view of artificial intelligence in a fast-paced two-hour session. After opening audience polling, it moves through four sections each with a moderated Q&A, covering the AI landscape and strategic opportunities, governance and fiduciary oversight, cybersecurity and organizational risk, and responsible AI and stakeholder trust. It closes with a Board Action Checklist of five questions every board should be asking about AI, plus a preview of next quarter’s session and recommended reading.
Hosted at Rutgers University on November 7, 2025, the NJBDA Research Collaboration Forum is a full-day gathering dedicated to advancing AI research and building new cross-sector collaborations.
Professor Jim Samuel — Vice-President of Research at NJBDA, Director of the Master of Public Informatics Program at Rutgers University, served as a host of the NJBDA Research Collaboration Forum, a gathering dedicated to advancing AI research with a spotlight on Life Sciences, Healthcare, and Biotechnology. Bringing his dual vantage point in research leadership and public informatics, he helped guide a program spanning generative AI–driven business applications, industry–academia collaboration, grants and research opportunities, and multidisciplinary AI applications — reflecting AIXosphere’s conviction that innovation delivers its greatest promise only when paired with responsibility, transparency, and human-centered design.
Presented at the 55th Annual Conference of the Northeast Decision Sciences Institute (NEDSI) April 9–11, 2026, Philadelphia, PA
As agentic AI moves into behavioral healthcare, a quiet question shapes everything these systems do: what happens before a single answer is generated? In retrieval-augmented setups, the posts an AI agent pulls from can steer the tone, framing, and guidance it delivers — a high-stakes dynamic for mental-health-facing systems judged not only on correctness, but on safety and empathy.
This study shines a light on that overlooked stage with a pre-indexing audit. Analyzing 500 posts across five subreddits (three behavioral health, two cannabis), the authors combine sentiment scoring (VADER), n-gram phrase patterns, topic discovery (BERTopic), and term co-occurrence graphs to reveal how each corpus is likely to steer an agent’s behavior.
AhaSphere is a supportive AI concept that fills the gap between everyday well-being and formal behavioral healthcare, offering continuous, non-clinical micro-support alongside an optional pathway to deeper help.
AhaSphere addresses the under-served space between everyday well-being and formal behavioral healthcare by providing continuous, non-clinical micro-support and an optional pathway to deeper help. It combines mood-lifting interactions — such as humor, motivation, and creativity — with adaptive personalization, bounded support for sleep, low mood, and addiction-related challenges, and connections to trusted contacts, community programs, and specialists. Grounded in evidence on supportive AI and everyday emotional uplift, AhaSphere is designed to reduce stigma, lower friction in help-seeking, and normalize supportive interaction within daily life, making well-being support more approachable, continuous, and connected for users across diverse care settings. Presented at the NJBDA Symposium, Rowan University, May 20, 2026.
introduces three complementary datasets of AI-related news headlines — capturing linguistic, temporal, and conceptual dimensions of AI narratives — to support research on media framing, public perception, and policy discourse.
In recent years, artificial intelligence has emerged as a transformative force shaping public discourse, with news media playing a critical role in influencing perceptions through the selective framing of opportunities, risks, and societal implications. This paper presents three complementary datasets of AI-related news headlines, designed to capture the linguistic, temporal, and multi-dimensional conceptual aspects of AI narratives.
The datasets support a broad range of applications across machine learning (ML), natural language processing (NLP), and large language model (LLM) frameworks — including sentiment analysis, thematic classification, and multi-label modeling. By incorporating human-centered and interdisciplinary dimensions, they enable systematic examination of the ethical, social, and economic perspectives surrounding AI, and facilitate research on media framing, public perception, and policy discourse — contributing to a more rigorous, transparent, and responsible understanding of AI’s evolving societal impact.
Presented at the 13th Annual NJBDA Symposium, Rowan University, May 20, 2026.
The 13th Annual NJBDA Symposium brings together industry, government, and academic experts at Rowan University on May 20, 2026, to explore building accessible and sustainable AI ecosystems.
Each year, the NJBDA Symposium provides a forum for industry, government, and academic experts to discuss the latest trends, current research, industry needs, and strategies for addressing big data, cyberinfrastructure, and advanced computation challenges and opportunities.
Rutgers AI & Data Science Hub, in collaboration with the RAD Collaboratory, has launched Defining Artificial Intelligence (DefAI) — a global research initiative bringing together 100+ co-authors from academia, industry, government, and nonprofit sectors.
The project seeks to unlock the semantic black box surrounding artificial intelligence by engaging scholars and practitioners in a global collaborative inquiry into critical AI concepts, including chatbots, generative AI, and agentic AI. Contributions will be synthesized and published in at least one major journal, with all contributors recognized as co-authors.
A dedicated Co-Author Collaboration Interface is available for submissions, and selected authors are invited to share their original insights. For full participation details, please visit: https://sites.rutgers.edu/raise/ai-definition/
AIXosphere is a proud collaborator with RAISE-26, the leading NLP-AI national competition at the intersection of informatics, data science, and artificial intelligence.
RAISE-26, hosted by the MPI program, Bloustein School – Rutgers University, and RAISE Research, is calling on undergraduate and graduate students from all disciplines to take on one of the most urgent questions of our time: Is artificial intelligence (AI) transforming us? This groundbreaking Artificial Intelligence – Informatics – Data Science competition challenges participants to investigate how AI is shaping human behavior, education, careers, and societal change.
View more details: Linkedin post
Register for the event: https://lnkd.in/eVDxvEyW
On October 22, thought leaders Udayan Bose (NetElixir) and Professor Jim Samuel (Rutgers University) led an insightful session on “Generating Real ROI from Generative AI.”
The engaging session will explore how organizations can move beyond experimentation and effectively harness Generative AI to achieve measurable business value. Drawing from their ongoing research and practical industry experience, Udayan and Professor Samuel will share frameworks and real-world examples for driving ROI in AI-powered initiatives.
The Rutgers Informatics Forum on Agentic Artificial Intelligence featured Professor Jim Samuel, who led discussions on the opportunities, challenges, and societal implications of agentic AI.
Professor Samuel shared insights on how AI systems are reshaping research, business, and policy. His session highlighted both the technical and human dimensions of AI, emphasizing the importance of cross-disciplinary collaboration and ethical innovation.
A highlight of the event was Professor Jim Samuel, whose insights sparked dynamic discussions on innovation, AI, and the intersection of academia and industry. Professor Samuel engaged with attendees, sharing his expertise and inspiring conversations that energized the forum.
Professor Jim Samuel’s course, AI Concepts and Strategy, has been ranked #3 on The CTO Club’s 2025 list of “Best AI Strategy Courses.” This recognition places the course alongside top programs from world-renowned institutions such as MIT, Stanford, INSEAD, and London Business School.
The AI Concepts and Strategy course equips business executives, government leaders, data scientists, and practitioners with essential knowledge on generative AI, foundation models, AI risks, and strategic applications. This achievement reflects Professor Samuel’s global leadership in AI education and his commitment to advancing human-centered, responsible, and strategic approaches to artificial intelligence.
NJBDA Research Collaboration Forum
As Vice-President of Research at NJBDA, and Director of the Master of Public Informatics Program at Rutgers University, Professor Samuel delivered a powerful and thought-provoking session that addressed the core challenges facing society in adapting to AI technologies.
AIXosphere is a proud collaborator with RAISE-25, the leading NLP-AI national competition at the intersection of informatics, data science, and artificial intelligence.
Hosted by the prestigious Rutgers Bloustein School’s Master of Public Informatics (MPI) program, RAISE-25 invites the next generation of thinkers to explore AI’s transformative role in shaping our future. This competition challenges participants to delve into pressing questions surrounding AI’s impact on education, careers, and societal change, offering an unparalleled opportunity for young talents to showcase their skills in a real-world context. As we collaborate with RAISE-25, AIXosphere continues to champion the advancement of AI solutions that drive positive change and global impact.
A highlight of the summit was Professor Jim Samuel’s insightful talk on “Why do Individuals, Institutions, and Businesses Struggle with AI?”
He explored the limits of AI in understanding human language, the intricacies of large language models (LLMs), and natural language processing (NLP) applications. His critical perspectives on the implications for the future of AI sparked engaging post-presentation discussions, resonating deeply with the audience.
A collaborative forum for information sharing, networking, research, and discovery of how intelligent technologies are transforming the workplace.
This dynamic symposium will delve into the transformative power of AI, showcasing how it empowers workers to unlock unprecedented levels of creativity, innovation, and impact. Don’t miss this opportunity to connect, learn, and lead the charge in building a future where humans and AI work together to achieve remarkable success!
Outstanding keynotes will be announced soon!
Event highlights:
● Academic research sessions with presentations
● Industry panel on AI impacts across sectors
● Hands-on student workshop
● Workforce development panel on advanced technologies
● Poster presentations
● Networking
● Exhibit opportunities
The NJBDA’s annual symposium is New Jersey’s premier conference for big data & advanced computing, consistently attracting 200+attendees from industry, government, and academia.
This year’s symposium will be held in person at William Paterson University.
News and Events: Upcoming: Prof. Samuel to speak to MSFT on 7th Feb, NYC
In his presentation, he will share his research and reflections on the nature of generative artificial intelligence, examining the interplay between creativity and originality in the context of human intelligence. He will also explore the immense potential of AI’s creative capabilities, discussing their constructive applications and addressing critical concerns about their potential misuse.
Regenerative agriculture, a transformative approach to restoring soil health, water resources, and biodiversity, is crucial for combating climate change and ensuring food security for a growing global population.
AI’s integration into this field is proving to be a game-changer. Technologies such as geospatial imagery enable landscape-level planning, helping farmers adopt holistic resource management practices. AI-driven tools like digital extension platforms, pest prediction systems, and rapid soil tests are revolutionizing farm-level decision-making, enhancing productivity while minimizing environmental impact. Furthermore, AI-enabled financial incentives, such as carbon credit payments, are simplifying complex processes, making regenerative practices more accessible to farmers worldwide.
Despite its potential, the scalability of AI in agriculture faces challenges like high carbon footprints, fragmented data, and limited farmer access to technology. Addressing these hurdles requires a multi-pronged approach: adopting renewable energy for AI systems, building robust digital infrastructure for data sharing, and fostering community-level support networks for technology adoption. As AI solutions evolve, their accuracy and impact will grow, driving a global shift towards sustainable farming practices. By integrating AI into regenerative agriculture programs today, we can lay the foundation for a resilient, climate-adaptive food system that meets the needs of future generations.
The editorial explores the paradigm of Human-Centered AI (HAI), emphasizing its potential to align technological advancements with human values and societal goals.
HAI is framed around three critical dimensions: human-enhancive, culturally sensitive, and personally adaptive. Human-enhancive AI prioritizes human well-being by integrating inclusive governance frameworks and educational tools tailored to individual needs, such as personalized learning experiences and gamified tutoring systems. Culturally sensitive AI ensures inclusivity by addressing diverse sociocultural contexts and adapting learning scenarios to respect cultural differences. Personally adaptive AI focuses on dynamically tailoring tools and experiences to meet individual and collective needs, enhancing engagement, and fostering inclusivity in education and governance.
The editorial highlights key contributions from various research papers, showcasing how HAI principles can address challenges such as bias, inclusivity, and adaptability. Examples include the development of teacher dashboards, emotionally adaptive tutoring systems, and culturally responsive educational frameworks like CATE-AI. These innovations underline the necessity of multidisciplinary approaches to prepare for AI-driven transformations while preserving human aspirations. By integrating human-centered, culturally sensitive, and adaptive approaches, HAI offers a pathway for responsible and ethical AI development, paving the way for agentic AI systems that prioritize societal well-being and values.
The study, “Are Emotions Conveyed Across Machine Translations?” establishes a systematic process to evaluate the effectiveness of applying English-language sentiment analysis tools to Italian text using machine translations.
The research highlights the challenges of multilingual NLP, particularly for under-resourced languages. It uses a novel Italian dataset, machine translation tools like Google Translate and Marian MT, and sentiment analysis methods to create a repeatable and effective framework for validating multilingual sentiment analysis.
This pioneering work explores how machine translations can bridge the gap for languages lacking robust NLP tools, offering a transparent method to evaluate translation quality and sentiment accuracy. By addressing limitations such as dataset size and diversity, the research opens pathways for extending NLP advancements across diverse languages, driving equitable technology access and empowering global communities.
For more information: Link to Paper
Speculative RAG is a groundbreaking framework that enhances Retrieval-Augmented Generation (RAG) by integrating a smaller specialist language model (LM) for drafting responses and a larger generalist LM for verifying and selecting the best draft.
This novel approach significantly improves both the accuracy and efficiency of knowledge-intensive tasks. By generating multiple drafts in parallel and verifying them quickly, Speculative RAG achieves up to 12.97% better performance compared to standard RAG systems across benchmarks like TriviaQA, PubHealth, MuSiQue, and ARC-Challenge. Additionally, it reduces latency by 51%, ensuring faster processing even when handling large volumes of documents. This innovative method showcases the power of collaborative AI architectures in achieving higher-quality, faster results for real-world applications.
Unlocking the Potential of AI: Our research extends to additional areas, including AI for agriculture and human-centric robotics!