Millie Pant
Papers
2
Total Citations
33
H-Index
2
About
Millie Pant is a leading figure in computational intelligence, with a primary focus on swarm intelligence, optimization algorithms, and their engineering applications. Her major contributions lie in enhancing nature-inspired metaheuristics, particularly the Artificial Bee Colony (ABC) algorithm, to solve complex real-world problems. In her highly cited 2011 work, she introduced a levy-mutated ABC algorithm for fractional-order PID control of DC motors, a critical advancement for precision in robotics and automation. She further demonstrated her impact in 2018 with an improved block matching algorithm for motion estimation in video sequences, directly applicable to robotic vision systems. With over 18 and 15 citations respectively on these key papers, Pant’s work bridges theoretical algorithm development and practical control engineering. Her research is notable for its interdisciplinary reach, from fractional calculus in control systems to video processing, consistently pushing the boundaries of how swarm intelligence can be tailored for high-stakes, real-time applications.
Research Focus
Key Achievements
Top Papers
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