AI brings many changes and challenges to separate industries, also changing the way professors and students research inside and outside of the classrooms, but SICCS is making sure students and professors learn to use these AI responsibly while also using it to aid them in their research and labs. <\/p>\n\n\n\n
This fall semester, SICCS welcomed five new faculty members who are using AI to explore their different themes of study and research, including forecasting diseases, improving healthcare, building trustworthy networks, advancing quantum computing, and understanding cultural technology. <\/p>\n\n\n\n
Assistant professor Spencer Fox directs research that uses machine learning to understand and predict the spread of diseases, such as Covid-19 and the flu. His work combines data science, epidemiology, and AI to help public health officials try and predict outbreaks before they happen. <\/p>\n\n\n\n
\u201cIt\u2019s a bit like weather forecasting but for outbreaks,\u201d Fox explained. \u201cJust as meteorologists look at temperature, humidity, and wind, I look at data like case counts, behavior, and immunity to forecast what might happen next.\u201d <\/p>\n\n\n\n
Fox\u2019s Computational Epidemiology and Forecasting Lab at NAU is developing models that learn from data about many diseases, like influenza and Covid-19, to predict how new or evolving pathogens might behave. These systems help medical professionals make faster decisions about vaccines, medical supplies, and emergency responses. <\/p>\n\n\n\n
Students working with Fox gain experience in coding, statistical modeling, and public health analytics, helping them to apply AI to global scale health issues. <\/p>\n\n\n\n
Assistant professor Mayank Bakshi focuses on making AI systems reliable. His research combines information theory and AI to ensure that systems can collaborate and learn, even if the data is noisy or incomplete. <\/p>\n\n\n\n
At NAU, Bakshi and his students work on designing AI frameworks that balance efficiency with promises of trust. The lab projects explore how multiple devices, such as sensors, drones, or servers, can train all AI models without sharing data, keeping privacy while maintaining accuracy. <\/p>\n\n\n\n
\u201cI hope my research contributes to the foundation of trust and scalability of intelligent systems,\u201d Bakshi said. \u201cAs AI becomes embedded in every aspect of life, its reliability and efficiency are becoming increasingly important.\u201d <\/p>\n\n\n\n
In the classroom, Bakshi emphasizes AI literacy as an understanding of when and how to trust these AI algorithms. <\/p>\n\n\n\n
Assistant professor Evan Donahue combines technology and humanities by working in both comparative cultural studies and SICCS. His research explores how ideas about intelligence and creativity have evolved throughout history and how those ideas continue to design AI today. <\/p>\n\n\n\n
\u201cI\u2019m interested in understanding how the history of AI continues to shape the way we\u2019re having these conversations about AI in the present,\u201d Donahue said. <\/p>\n\n\n\n
Within SICCS, Donahue is helping develop new courses to examine how researchers define, test, and measure \u201cintelligence\u201d in different systems. His future lab space will serve as a humanities and technology research studio, aiming for collaborations between coders, artists, and historians to explore how AI changes writing, media, and communication. <\/p>\n\n\n\n
For Donahue, AI literacy means more than knowing how to use AI tools; it also means understanding why they were built. His cross-college teaching and research helps students engage with AI in both scientific and cultural ways. <\/p>\n\n\n\n
Assistant Professor Mithun Paul leads research into quantum AI, a field that explores how quantum computing can change how AI understands language, meaning, and context. <\/p>\n\n\n\n
Paul helps develop algorithms that are faster and more energy efficient. A major focus of his lab is preventing and understanding languages that may not be represented as frequently, including Indigenous languages, which often do not have the online datasets needed for traditional AI training. <\/p>\n\n\n\n
\u201cAI in its current form is a mess,\u201d Paul said. \u201cOnce we accept that students and professionals will use it, we can focus on building safer, more precise systems. That\u2019s exactly what we created with VERDE AI.\u201d <\/p>\n\n\n\n
Paul\u2019s team created VERDE AI, a platform capable of distributing language models. This platform is used in many NAU departments. His lab also provides students with hands-on experience with both AI and quantum computing. <\/p>\n\n\n\n
Assistant professor Fariha Hossain combines computer techniques and medical data science to improve how healthcare professionals interpret clinical information. She recently launched the Clinical Vision & AI Lab at NAU, which develops AI tools to analyze medical images and reports while still keeping patients’ trust and privacy and treating them fairly. <\/p>\n\n\n\n
\u201cTo me, AI literacy means knowing what you\u2019re using, what trained it, and what it\u2019s actually good\u2014or not good\u2014at,\u201d Hossain said. \u201cIt\u2019s about using AI responsibly and knowing when to double-check or defer to a human.\u201d <\/p>\n\n\n\n
C-VAIL\u2019s projects include disease detection and prognosis tracking systems that help medical professionals make more consistent decisions. <\/p>\n\n\n\n
Her models can detect when an image is too low-quality to use, flag urgent cases, and track disease progression. The lab also focuses on ensuring that AI performs fairly across different devices and lighting conditions. <\/p>\n\n\n\n
Hossain said AI should act as a partner, not a replacement. Her students can gain experience working with medical datasets and developing algorithms that can reduce diagnosis time and improve patient care. <\/p>\n\n\n\n
These new SICCS faculty members are changing what it means to teach and study with AI. Their labs not only fuel research but also offer NAU students to participate in labs and job opportunities. <\/p>\n","protected":false},"excerpt":{"rendered":"
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