Kusum Deep
Indian Institute of Technology Roorkee, Central Building Research Institute Roorkee, Loughborough University, University of Roorkee, Punjab University
About
Prof. Kusum Deep is full Professor (HAG), with the Department of Mathematics and Joint Faculty with the Mehta Family School of Data Science and Artificial Intelligence. She was awarded the University Gold Medal in M.Phil (Mathematics) from University of Roorkee in 1984. She was the first student and only student in 1984 in Mathematics Department to have qualified UGC-NET for pursuing PhD. She was awarded PhD in Mathematics from University of Roorkee in 1988. In 1981 she was awarded the Khosla Award by University of Roorkee. During her tenure as Scientist C, in Central Building Research Institute, (1988-1996), she was awarded the prestigious Post-Doctoral Bursary funded by Commission of European Communities, Brussels, at Department of Computer Studies, Loughborough University of Technology, Loughborough, U.K. from November 1993 to November 1994. In 1996, Kusum joined the University of Roorkee as an Assistant Professor, as Associate Professor in 2004 and Professor in 2012. In 2020 she moved to the HAG scale of Professor.
Kusum has won numerous national and international awards, namely: Career Research Award, UGC, 2002 – 2005; Star Performer, IIT Roorkee, 2001 – 02 & 2002–03, 2003 – 04, 2004 – 05; Special facilitation in memory of late Prof. M. C. Puri, during 40th Convention of ORSI, Golden Jubilee Celebrations, New Delhi, Dec. 2007; Best Technical Paper Award, Railway Bulletin of Indian Railways 2005; Nominated as EXPERT, Dept. of Science and Technology, New Delhi; Nominated as Senior Member, Operations Research Society of India; Nominated as Senior Life Member, Computer Society of India, 2010; Founding President, Soft Computing Research Society, New Delhi, 2014; Best Paper Award during 2nd International Conference on Harmony Search Algorithms, Seoul, Korea University, Korea, August 19-21, 2015; received Association of Inventory Academicians and Practitioners Excellence Award, 2018; Visiting Professor at Liverpool Hope University, UK, 2019; Visiting Professor, University of Technology Sydney, Australia, 2019; Visiting Professor, University of Wollongong, Australia, 2019; Best Paper Award during International Conference on Operations Research and Decision Sciences, IIM Visakhapatanam, December 28-30, 2019; Awarded Performance Based HAG, IIT Roorkee w.e.f. Jan 1, 2020; Appointed Joint Faculty, Mehta Family School of Data Science and Artificial Intelligence w.e.f. June 2, 2020 till date; awarded MOOC NPTEL lectures, Operations Research, 2019, 2020, 2021, 2022; One of the four women of IIT Roorkee to feature in the ebook “Women in STEM-2021” celebrating the contributions made by 50 Indian women in STEM published by Confederation of Indian Industries; enlisted among top 2% scientists in the world according to Stanford University Ranking; Awarded the prestigious 60 lakhs grant from SERB under Promoting Opportunities for Women in Exploratory Research (POWER), 2021; awarded consultancy Project by AI Academy, Deloitte, 2022.
Kusum has authored two books, supervised 25 PhDs, and published over 150 research papers. She is a Senior Member of ORSI, CSI, IMS and ISIM. She is the Executive Editor of International Journal of Swarm Intelligence, Inderscience. She is Associate Editor of Swarm and Evolutionary Algorithms, Elsevier and Associate Editor of Engineering Applications of Artificial Intelligence, and is on the editorial board of many reputed journals. She is the General Chair of series of International Conference on Soft Computing for Problems Solving (SocProS). She has a vast teaching experience in Mathematics, Operations Research, Numerical and Analytical Optimization, Parallel Computing, Computer Programming, Numerical Methods, etc. Her research interests are nature inspired optimization techniques, particularly Evolutionary Algorithms, and Swarm Intelligence Techniques and their applications to solve real life problems.
The target of Kusum’s research is to design efficient and reliable nature inspired optimization techniques with a view to solve real life optimization problems.
Her breakthrough paper on real coded GA for integer and mixed integer optimization problems in 2009 continues to be the most downloadable paper of the Journal of Applied Mathematics and Computation, Elsevier. It is based on Laplace Crossover-a real coded crossover operator and Power mutation – a real coded mutation operator. Later, these operators were hybridized with numerous algorithms like, BBO, GSA, ALO and used to solve problems like: Management of multipurpose multi reservoir, Minimization of Molecular Potential Energy Function, Minimizing Lennard-Jones Potential, etc.
Kusum has designed and applied new PSO: e.g. shrinking hypersphere PSO, Co-Swarm PSO, novel Inertia Weight strategies in PSO; binary PSO for knapsack problems, Hybrid discrete PSO for trim loss, arthquake engineering, stereo camera calibration, Parameter Optimization of Multi-pass Turning[, Extraction Process of Bioactive Compounds from Gardenia, Cell-lik
Employment
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Indian Institute of Technology Roorkee Professor1996 - Present
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Central Building Research Institute Roorkee Scientist1988 - 1996
Education
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Loughborough University Post Doctorate under Commission of European Communities, Brussels1993 - 1994
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University of Roorkee PhD1984 - 1988
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University of Roorkee M.Pkil1983 - 1984
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Punjab University M.Sc. Honours1982 - 1983
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Punjab University B.Sc Honours1976 - 1979
Projects & Funding
Projects & funding information is unavailable.
Publications (182)
- Q-Learning-Integrated Real Coded Genetic Algorithms for the Circle Packing Problem Save
- RDeltaCAM: Gradient-Free Causal Inference for Visual Interpretability Save
- Q-learning-driven real coded genetic algorithm for dynamic dose optimization in radiotherapy Save
- Information fusion in smart agriculture: machine learning applications and future research directions Save
- A Deep Reinforcement Learning-Based Adaptive Model for Sepsis Treatment in ICU Save
- Explainable KNN Classification Using SHAP Values and Particle Swarm Optimization Save
- Optimizing Mechanical Ventilation Strategies in Critical Care Through Deep Reinforcement Learning Save
- Regenerative population strategy-I: A dynamic methodology to mitigate structural bias in metaheuristic algorithms Save
- State‐Of‐The‐Art on Ensemble of Real Coded Genetic Algorithm Operators Save
- Efficient Waste Collection Routing Using F-CVRP and Dynamic Parameter Optimization via Q-Learning Save