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Mathematics identified as core driver of AI progress at Indian conference

Reported by Tanvi Pillai (Section Editor) · The Hindu - National ·

Source: The Hindu
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GeneralMathematics identified as core driver of AI progress at Indian conference
Representative image · Wikimedia Commons

Mathematics was declared the essential engine behind modern artificial intelligence by Reheena Nasrin of BUET during the valedictory session of the three‑day Computation Science and Intelligent Engineering conference in Vijayawada.

Key Insight

Nasrin stressed that advanced AI capabilities, predictive power and logical reasoning all depend on mathematical equations, frameworks and data algorithms.

Speakers

G. Sobhalatha of Sri Krishnadevaraya University presented a talk on the lexicographic product graph. Bukke Kiran Naik, scientist at NIT Rourkela, discussed intelligent thermodynamics, highlighting data‑driven system optimisation and solutions for the energy‑water nexus.

Participation

Conference convener Charan announced that more than 200 research papers were presented by scholars from leading Indian universities. Certificates of participation and excellence were handed out by the dignitaries. The valedictory session was attended by Vice‑Chancellor P. Venkateswara Rao, Pro‑Vice‑Chancellor A.V. Ratna Prasad, Dean D. Venkata Rao, Registrar M. Ravichand, Head of the Mathematics Department Ch. Baby Rani and senior faculty K. Hemalatha, J. Siva Ram Prasad and M.V.D.N.S. Madhavi, along with other faculty, department heads, research scholars and students.

Context

Mathematics underpins the algorithms that power AI, so strong mathematical training is seen as crucial for future digital intelligence developments.

ExplainerWhy this matters

What Happened

The three‑day Computation Science and Intelligent Engineering conference concluded with a valedictory session where Reheena Nasrin highlighted mathematics as the core engine of AI. More than 200 research papers were presented, and experts such as G. Sobhalatha and Bukke Kiran Naik delivered talks on graph theory and data‑driven thermodynamics.

Why It Matters

AI systems rely on mathematical models to learn, predict and reason. Without solid mathematical foundations, algorithms cannot be optimized for accuracy or efficiency. The conference emphasized that future advances in digital intelligence will depend on deeper mathematical research, influencing fields from energy management to natural language processing.

What Happens Next

Researchers are expected to build on the presented papers, exploring new mathematical frameworks for AI. Academic institutions may expand curricula to strengthen math‑AI links, and upcoming conferences will likely showcase further breakthroughs in this interdisciplinary area.

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