Laxmikant Sharma, PhD

Email: lkrdkrishnan@gmail.com

Phone: +91 8979069550

Location: Mathura, UP 281001, India

I am a researcher specializing in soft computing, evolutionary algorithms, quantum computing, and mathematical optimization, with a keen interest in both their theoretical foundations and practical applications. I have recently submitted my Ph.D. thesis, supervised by Prof. C. Vasantha Lakshmi and Prof. C. Patvardhan at Dayalbagh Educational Institute in Agra, India. My doctoral research focused on the design and analysis of socio-inspired evolutionary algorithms for solving complex optimization problems.

My research combines principles from evolutionary computation, social behavior modeling, and optimization to improve the performance and adaptability of computational algorithms. I have published my findings in peer-reviewed journals and have presented at various national and international conferences. One of my recent publications, titled "Socio-inspired Evolutionary Algorithms: A Unified Framework and Survey," has garnered positive feedback and is seeing an increasing number of citations.

I am actively seeking postdoctoral opportunities that enable me to contribute to and collaborate on research in fields such as artificial intelligence, quantum information theory, soft computing, optimization theory, and cryptography. I have a strong passion for developing solutions that are not only mathematically rigorous but also have a meaningful impact on real-world applications.

Research Interests

• Evolutionary Computation
• Soft Computing
• Quantum Computing
• Socio-inspired Evolutionary Computation
• Combinatorial Optimization
• Machine and Deep Learning
• Robotics

Education

• Ph.D. in Computer Science, Dayalbagh Educational Institute (Thesis Submitted, 2018–2025)
• MCA, Dr. A.P.J. Abdul Kalam Technical University, Lucknow (2014–2016, 76.85%)
• B.Sc. in Computer Science, Dr. Bhimrao Ambedkar University, Agra (2011–2014, 59.27%)

Publications

1. Socio-inspired evolutionary algorithms: a unified framework and survey. Soft Computing, 2023. DOI: https://doi.org/10.1007/s00500-023-07929-z
2. Improved Imperialist Competitive Algorithm with Binary-encoding for selection problems in Combinatorial optimization (Submitted to ICTACT Soft Computing)
3. Vedic Society Optimizer (VSO): A new socio-inspired metaheuristic for real-world engineering optimization (Submitted to Soft Computing, Springer)
4. QKPICA: A Socio-Inspired Algorithm for Solution of Large-Scale Quadratic Knapsack Problems. Lecture Notes in Electrical Engineering, Springer, 2023. DOI: https://doi.org/10.1007/978-981-99-0047-3_59
5. Design of optimal trusses using novel Socio-inspired Evolutionary Algorithm. International Conference On Recent Advancement and Innovation In Engineering & Technology (RAIET), 2023.
6. Read aloud text in Indian languages with NAO Robot. DSC Conference, 2024.

Talks and Presentations

• Socially-inspired Evolutionary Algorithms. UGC-SAP Seminar, March 2019
• Educational applications of NAO Robot. Fundamentals of AI and Its Applications in Education, December 2020.

Awards and Honors

• UGC Junior Research Fellowship (2019–2022)
• UGC Senior Research Fellowship (2022–2024)

Memberships

• Soft Computing Research Society (SCRS)

Academic Contributions

• Developed official LaTeX thesis template for DEI
• Created departmental posters and displays
• Assisted scholars in thesis formatting and documentation
• Maintained lab infrastructure and research tools
• Guided BTech/BSc projects

Teaching Experience

• TA, DEI Agra (2019–2024): C Programming, Data Structures
• Teacher, Lord Krishna Institute, Mathura (2017–2018)

Technical Skills

• Programming: C/C++, Java, JavaScript, Python, MATLAB
• Web: HTML5, CSS3
• Tools: Docker, Qt Creator, LaTeX, gnuplot, MS Office
• IDEs: Android Studio, Visual Basic Studio, TEXstudio, CLion, PyCharm, MATLAB

Languages

• English: Proficient
• Hindi: Native
• Sanskrit: Intermediate

Teaching