Kanika | Machine Learning | Best Researcher Award

Kanika | Machine Learning | Best Researcher Award

Ms. Kanika, National institute of technology Agartala, India.

Ms. Kanika, hailing from Hasanpur, Haryana, is an enthusiastic researcher with a strong passion for applied mathematics 🧮 and advanced computing technologies 💻. Her expertise spans optimization, uncertainty theory, numerical analysis, graph theory, artificial intelligence 🤖, and machine learning. With an M.Sc. in Mathematics and Computing 🎓 from NIT Agartala, where she ranked 6th, and a B.Sc. in Mathematics, Physics, and Computer Science 🎓 from Banasthali Vidyapith, she has consistently demonstrated academic excellence. Kanika is driven to solve real-life problems 🌍 through mathematics and is currently working on a machine-learning research paper while aspiring to contribute to computational imaging and AI.

Publication Profiles 

Googlescholar

Education and Experience

Education 🎓
  • M.Sc. in Mathematics and Computing (2021–2023), NIT Agartala: 89.5%, 8.95/10, Rank: 6️⃣
  • B.Sc. in Mathematics, Physics, and Computer Science (2017–2020), Banasthali Vidyapith: 85.8%, 8.58/10 🧮
  • Senior Secondary Examination (2016–2017), Board of School Education Haryana: 85.0% 🧑‍🎓
  • Secondary Examination (2014–2015), Board of School Education Haryana: 91.4% 🌟
Experience 🧑‍🔬
  • M.Sc. Thesis (2022–2023) at NIT Agartala: Focused on portfolio optimization under uncertainty 🌐.

Suitability For The Award

Ms. Kanika is an exceptional candidate for the Best Researcher Award, showcasing a strong academic foundation, innovative research contributions, and a deep commitment to advancing applied mathematics, machine learning, and artificial intelligence. Her dedication to leveraging mathematical and computational tools for solving real-world problems highlights her potential to make a significant impact in her field.

Professional Development

Kanika’s professional journey showcases her dedication to research and continuous learning 📚. She has gained expertise in machine learning 🤖, MATLAB 🧪, and scientific computing 🖥️. Her technical skills extend to programming languages like C/C++ and database management systems 💾. As a mathematics enthusiast, she has completed rigorous training programs like the Mathematics Training and Talent Research (MTTS) and the National Mathematics Talent Contest 🏅. She actively participates in workshops and online programs, enhancing her skills in cutting-edge mathematical technologies 🌟. Kanika is also a certified karateka 🥋, showcasing her versatile interests beyond academics.

Research Focus

Ms. Kanika’s research interests lie at the intersection of applied mathematics and emerging technologies 🌐. Her focus areas include optimization 📈, uncertainty theory, numerical analysis, graph theory, machine learning 🤖, and artificial intelligence. She aims to bridge theoretical mathematics with practical computing applications 💻, contributing to fields like computational imaging and decision-making under uncertainty. Currently working on a machine-learning research paper 📝, Kanika aspires to tackle real-life problems 🌍 using her expertise in applied mathematics and AI. Her passion for solving complex problems drives her to explore innovative solutions in these interdisciplinary domains.

Awards and Honors

  • IIT JAM 2021 🎓: All India Rank 2169 (Mathematical Sciences).
  • MTTS Level 1 🏅: Selected in the top 20 students, IISER Thiruvananthapuram (2020).
  • Banaras Hindu University Entrance Exam 🎓: All India Rank 363 (Mathematical Sciences, 2020).
  • Common Entrance Exam (CEE) by NCERT 🏆: State Rank 63 (General), NCERT (2017).
  • National Mathematics Talent Contest 🥇: Top 10%ile, Junior Level Screening Test, AMTI (2014).
  • Certified Karateka 🥋: 8th, 7th, and 6th Kyu (Blue Belt), JKMO (2018).
  • Olympic Value Education Program Ambassador 🏅: Honored by Banasthali Vidyapith (2017).

Publication Top Notes 

  • 📚 Tools and techniques for teaching computer programming: A review – Journal of Educational Technology Systems, 2020, Cited by: 88
  • 🤝 Effect of different grouping arrangements on students’ achievement in collaborative learning – Interactive Learning Environments, 2023, Cited by: 12
  • 🧬 Genetic algorithm‐based approach for making pairs and assigning exercises in programming – Computer Applications in Engineering Education, 2020, Cited by: 8
  • 📖 Enriching WordNet with subject-specific out-of-vocabulary terms using ontology – Data Engineering for Smart Systems, 2022, Cited by: 6
  • 🎓 KELDEC: A recommendation system for extending classroom learning with visual cues – Proceedings of SSIC, 2019, Cited by: 6
  • 🎯 VISTA: A teaching aid to enhance contextual teaching – Computer Applications in Engineering Education, 2021, Cited by: 3
  • 🌐 Linking classroom studies with dynamic environment – International Conference on Computing, Power and Communication, 2019, Cited by: 2
  • 🔄 Effect of varying the size of the initial parent pool in genetic algorithm – International Conference on Contemporary Computing and Informatics, 2014, Cited by: 2
  • 🌍 A review of English to Indian language translator: Anusaaraka – International Conference on Advances in Computer Engineering & Applications, 2014, Cited by: 2