Hemraj | Algorithms | Best Researcher Award

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Mr. Hemraj | Algorithms | Best Researcher Award

Research Scholar at IIT Guwahati, India.

Dr. Hemraj Raikwar is a Ph.D. research scholar in the Department of Computer Science & Engineering at IIT Guwahati, specializing in theoretical computer science and dynamic graph algorithms. His research focuses on designing incremental, decremental, and fully dynamic algorithms for maintaining approximate Steiner trees in dynamic graphs. With a strong foundation in algorithm analysis, object-oriented programming, and machine learning, he has contributed to top-tier international conferences and journals. His work has been recognized with the Outstanding Paper Award at CANDAR 2023, and he actively reviews for leading computer science journals.

Professional Profile:

Scopus

Orcid

Google Scholar 

Education Background

Dr. Raikwar is currently pursuing a Ph.D. in Computer Science & Engineering at IIT Guwahati, where he is working under the supervision of Prof. Sushanta Karmakar on developing efficient dynamic algorithms for the Steiner tree problem. He earned his B.Tech in Computer Science & Engineering from Guru Ghasidas Central University, Bilaspur, graduating with an 8.81 CGPA in 2018. His early education was at Jawahar Navodaya Vidyalaya, Khurai, where he excelled in mathematics and computer science, scoring 88.6% in higher secondary.

Professional Development

Dr. Raikwar has been an active reviewer for the American Journal of Computer Science and Technology since April 2024. He has also served as a Computing Lab Teaching Assistant at IIT Guwahati in multiple academic terms, including 2019, 2020, and 2022, where he mentored students in data structures and programming. His experience spans algorithm analysis, machine learning, Linux-based programming, and dynamic algorithm techniques, making him proficient in teaching and research.

Research Focus

Dr. Raikwar’s research primarily focuses on dynamic graph algorithms, with an emphasis on the Steiner tree problem. He works on designing incremental, decremental, and fully dynamic algorithms that maintain efficient approximations of Steiner trees in evolving graphs. His broader interests include algorithm optimization, combinatorial optimization, approximation algorithms, and artificial intelligence, particularly in applications requiring fast and scalable algorithmic solutions.

Author Metrics:

Dr. Raikwar has published extensively in leading IEEE, ACM, and computational science journals. His notable works include:

  • “Fully Dynamic Algorithm for Steiner Tree Using Dynamic Distance Oracle”, ICDCN 2022
  • “Fully Dynamic Algorithm for the Steiner Tree Problem in Planar Graphs”, CANDARW 2022
  • “An Incremental Algorithm for (2−𝜖)-Approximate Steiner Tree”, CANDAR 2023 (Outstanding Paper Award)
  • “Dynamic Algorithms for Approximate Steiner Trees”, Concurrency & Computation, 2025

His research contributions have been recognized in international conferences, earning best paper awards and citations in algorithmic research.

Honors & Awards

Dr. Raikwar has received several prestigious accolades, including the Outstanding Paper Award at CANDAR 2023 for his contributions to dynamic Steiner tree algorithms. He secured a GATE score of 671/1000 with an AIR of 840 and was selected for the Indo-German School for Algorithms in Big Data at IIT Bombay (2019). His academic achievements also include 1st position in the International Science Talent Search Exam (2007) and a 100% score in Logical Reasoning in the Science Olympiad Foundation (2010).

Publication Top Notes

1. Calorie Estimation from Fast Food Images Using Support Vector Machine

Authors: H. Raikwar, H. Jain, A. Baghel
Journal: International Journal on Future Revolution in Computer Science
Year: 2018
Citations: 9

2. Fully Dynamic Algorithm for the Steiner Tree Problem in Planar Graphs

Authors: H. Raikwar, S. Karmakar
Conference: 2022 Tenth International Symposium on Computing and Networking Workshops (CANDARW)
Year: 2022
Citations: 1

3. An Incremental Algorithm for (2-ε)-Approximate Steiner Tree Requiring O(n) Update Time

Authors: H. Raikwar, S. Karmakar
Conference: 2023 Eleventh International Symposium on Computing and Networking (CANDAR)
Year: 2023

4. Fully Dynamic Algorithm for Steiner Tree using Dynamic Distance Oracle

Authors: H. Raikwar, S. Karmakar
Conference: Proceedings of the 23rd International Conference on Distributed Computing (DISC)
Year: 2022

Conclusion

Dr. Hemraj Raikwar has demonstrated outstanding research capabilities, strong academic excellence, and impactful contributions to theoretical computer science. His expertise in dynamic graph algorithms, algorithmic optimization, and AI-driven techniques makes him a deserving candidate for the Best Researcher Award.

With further expansion into global collaborations, industry applications, and high-impact journal publications, he can solidify his position as a leading researcher in algorithmic science.

Sidra Jubair | Machine Learning | Best Researcher Award

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Ms. Sidra Jubair | Machine Learning | Best Researcher Award

Ph.D Student at Dalian University of Technology, China📖

Dr. Sidra Jubair is a dedicated researcher in the field of applied mathematics, currently pursuing her Ph.D. at the School of Mathematical Sciences, Dalian University of Technology, China, under the supervision of Prof. Jie Yang. Her research focuses on machine learning, computational fluid dynamics, and neurocomputing. With a strong academic background and numerous high-impact publications in top-tier journals, she is committed to advancing knowledge in data-driven scientific computation.

Profile

Scopus Profile

Google Scholar Profile

Education Background🎓

  1. Ph.D. in Applied Mathematics (2019 – Present)
    • Dalian University of Technology, China
    • Project: Imbalanced Data Learning through Examples and Classifiers
  2. M.Sc. in Applied Mathematics (2016 – 2018)
    • Hazara University, Pakistan
    • Supervised by Prof. Dr. Muhammad Shahzad
  3. B.Sc. in Mathematics (2011 – 2015)
    • International Islamic University, Islamabad, Pakistan

Professional Experience🌱

Dr. Sidra Jubair has extensive research experience in applied mathematics, focusing on the integration of computational intelligence with fluid dynamics. She has collaborated with researchers globally and contributed to high-impact scientific journals. Her work primarily revolves around machine learning applications in engineering and environmental sciences. Additionally, she has actively participated in international conferences and workshops, sharing her insights on topics such as neurocomputing and imbalanced data learning.

Research Interests🔬

Her research interests include:

  • Neurocomputing
  • Computational Fluid Dynamics
  • Imbalanced Data Learning
  • Machine Learning Applications in Engineering

Author Metrics

Dr. Sidra Jubair has established a strong research presence in the fields of applied mathematics, machine learning, and computational fluid dynamics. Her scholarly contributions have garnered significant recognition, with over 900 citations on Google Scholar, reflecting the impact and relevance of her work within the scientific community. She holds an H-index of 15, demonstrating the consistent influence and citation of her research, and an i10-index of 12, highlighting her ability to produce multiple highly cited publications. Dr. Jubair has published extensively in top-tier, high-impact journals, including Information Processing and Management, Alexandria Engineering Journal, and Applied Water Sciences, with impact factors reaching up to 7.4. Her research on imbalanced data learning and computational modeling has been widely acknowledged, contributing valuable insights to the advancement of data-driven scientific computation.

Publications Top Notes 📄

1. Mixed convective flow of hybrid nanofluid over a heated stretching disk with zero-mass flux using the modified Buongiorno model

  • Authors: B. Ali, N.K. Mishra, K. Rafique, S. Jubair, Z. Mahmood, S.M. Eldin
  • Journal: Alexandria Engineering Journal
  • Volume: 72
  • Pages: 83-96
  • Citations: 74
  • Year: 2023

2. Numerical simulation of the nanofluid flow consists of gyrotactic microorganism and subject to activation energy across an inclined stretching cylinder

  • Authors: H.A. Othman, B. Ali, S. Jubair, M. Yahya Almusawa, S.M. Aldin
  • Journal: Scientific Reports
  • Volume: 13, Issue 1
  • Article Number: 7719
  • Citations: 51
  • Year: 2023

3. MHD flow of nanofluid over moving slender needle with nanoparticles aggregation and viscous dissipation effects

  • Authors: B. Ali, S. Jubair, D. Fathima, A. Akhter, K. Rafique, Z. Mahmood
  • Journal: Science Progress
  • Volume: 106, Issue 2
  • Article Number: 00368504231176151
  • Citations: 42
  • Year: 2023

4. Boundary layer and heat transfer analysis of mixed convective nanofluid flow capturing the aspects of nanoparticles over a needle

  • Authors: B. Ali, S. Jubair, L.A. Al-Essa, Z. Mahmood, A. Al-Bossly, F.S. Alduais
  • Journal: Materials Today Communications
  • Volume: 35
  • Article Number: 106253
  • Citations: 38
  • Year: 2023

5. Numerical investigation of heat source induced thermal slip effect on trihybrid nanofluid flow over a stretching surface

  • Authors: B. Ali, S. Jubair, A. Aluraikan, M. Abd El-Rahman, S.M. Eldin, H.A.E.W. Khalifa
  • Journal: Results in Engineering
  • Volume: 20
  • Article Number: 101536
  • Citations: 37
  • Year: 2023

Conclusion

Dr. Sidra Jubair is a highly deserving candidate for the Best Researcher Award. Her outstanding research in applied mathematics, particularly in machine learning and computational fluid dynamics, has had a profound impact on both the academic and scientific communities. Her consistent publication in top-tier journals and strong research metrics underscore her ability to produce high-quality, impactful research. While there are opportunities for her to broaden the scope of her research through real-world applications and interdisciplinary collaborations, her current work demonstrates tremendous potential for further breakthroughs in applied mathematics and engineering.

Her dedication to advancing knowledge in data-driven scientific computation, coupled with her innovative approaches, makes her an ideal candidate for the Best Researcher Award.

Sankar Shanmuganathan – Generative adversarial networks

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Dr. Sankar Shanmuganathan – Leading Researcher in Generative adversarial networks

Dr.  Sankar Shanmuganathan  a distinguished academic and researcher in the field of Generative adversarial networks. He is currently serving as a Professor in the Department of Computer Science and Engineering at Saveetha School of Engineering, SIMATS, Chennai, Tamil Nadu, India. A dedicated, resourceful, and goal-driven professional educator, he is passionate about programming and has a solid commitment to academic growth. With over 20 years of experience, he is a seasoned researcher and has taught courses for both undergraduate and postgraduate students. He has successfully supervised 20 Bachelor’s theses and 10 Master’s theses, demonstrating his mentorship skills. His contributions extend to publishing articles in peer-reviewed journals and conferences, obtaining three patents, and securing grants from AICTE for organizing technical events.🌟💻🔬

Eduvation

He completed his Ph.D. in Information Technology from Hindustan University in 2018. 🎓 Prior to that, he earned a Master’s degree in Software Engineering from Periyar Maniammai College of Technology, affiliated with Anna University, Chennai, Tamil Nadu, in 2006, achieving a first-class distinction. 🏆 His academic journey began with a Bachelor’s degree in Computer Engineering from Arulmigu Kalasalingam College of Engineering, Srivilliputhur, Tamil Nadu, in 1992, where he also excelled with a first-class distinction. 🏅 This degree was affiliated with Madurai Kamaraj University, Madurai, Tamil Nadu. 🌟

Professional Profiles:

RESEARCH ACTIVITIES

🗣️He has obtained three patents from IP Australia, showcasing his innovative contributions. The first patent, dated October 27, 2021 (Patent No: 2021102955), is titled “A System and Method for Agile Meeting Dashboard.” The second patent, dated May 5, 2021 (Patent No: 2021101703), pertains to “3D Printing of Cost-Effective Human Skull Models and Skull Implants.” The third patent, dated April 7, 2021 (Patent No: 2021100286), is for “Aqua Life: A Compact Device Extracting Drinkable Water from Sea Water.”

In addition to his research achievements, he has undertaken various consultancy projects. Notably, he developed a software product for MEL Systems and Services Ltd, Chennai, involving the creation of advanced reports using Python, Django, and MongoDB. Another significant project involved the development of a software product to detect glaucoma in optical coherence tomography images for M/s Appasamy Associates R & D, Chennai, implemented in Java and Matlab.

Furthermore, he contributed to software bug fixing for General Electricals T & D Limited, Chennai, utilizing VB.NET technology. Additionally, he conducted corporate training for General Electricals T & D Limited, Chennai, imparting VB.NET platform skills to GE employees, preparing them to independently develop utility software. The funds received for training amounted to Rs. 2,00,000. Overall, his diverse expertise and accomplishments reflect his commitment to both innovation and practical application in the field.

BOOKS AUTHORED / CHAPTER CONTRIBUTED

AUTHORED BOOK on OBJECT ORIENTED PROGRAMMING Published by Laxmi PublicationsChennai,
2009
CHAPTER CONTRIBUTED LEAN SIX SIGMA: SIX SIGMA PROJECTS AND PERSONAL EXPERIENCEPublished by In-Tech Open Access Publications, Crotia, 2012

RESEARCH PAPERS PUBLISHED

  • Deep generative adversarial networks with marine predators algorithm for classification of Alzheimer’s disease using electroencephalogram
    • Authors: J.C. Sekhar, Ch Rajyalakshmi, S. Nagaraj, S. Sankar, Rajesh Saturi, A. Harshavardhan
    • Published in: Journal of King Saud University – Computer and Information Sciences
    • Volume 35, Issue 10, December 2023
    • DOI: 10.1016/j.jksuci.2023.101848
  • Exploration of Performance of Dynamic Branch Predictors used in Mitigating Cost of Branching
    • Authors: Akash Ambashankar, Ganesh Chandrasekar, AR Charan, S Sankar
    • Published in: 2022 IEEE Third International Conference on Intelligent Computing Instrumentation and Control Technologies (ICICICT)
  • AI Enabled Educational Bot to Improve Learning Outcomes using Bag of Words Algorithm
  • Intelligent Organ Transplantation System Using Rank Search Algorithm to Serve Needy Recipients
    • Authors: S Sankar, U Shuruti, B Bhuvaneshwari
    • Published in: 2022 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems (ICSES)
  • Understanding Query Intention in Search Queries of Learners in Blended Learning Environments
    • Authors: Vivekananthamoorthy Natarajan, Sankar Shanmuganathan
    • Published in: 2022 IEEE 4th International Conference on Cybernetics, Cognition and Machine Learning Applications (ICCCMLA)
  • Sign language translator using YOLO algorithm
    • Authors: Bhavadharshini, M., Josephine Racheal, J., Kamali, M., Sankar, S.
    • Published in: Advances in Parallel Computing, 2021, 39, pp. 159-166
  • Detection of Anomalous Behaviour in Online Exam towards Automated Proctoring
    • Authors: Susithra V, Resham A, Bishruti Gope, Sankar
    • Published in: IEEE International Conference on System, Computation, Automation and Networking
    • DOI: 10.1109/ICSCAN53069.2021.9526448
  • Development of Novel Technique to Detect and Validate Pulmo Malignancy during Early Stages
    • Authors: Dhanalakshmi R, Shree Harini R, Pravallika M, S Sankar
    • Published in: International Journal of Current Research and Review, volume: 13 issue: 17, pp. 56-60, 12th September 2021
    • DOI: http://dx.doi.org/10.31782/IJCRR.2021.131711
  • Sentiment Analysis of Twitter Political Data using GRU Neural Network
    • Authors: Seenaiah Pedipina, Sankar S and R Dhanalakshmi
    • Published in: International Journal of Advanced Science and Technology 29(6), pp. 5307-5320, ISSN 2207-6360, SERSC Australia
  • Sentimental Analysis On Twitter Data Of Political Domain
    • Authors: Seenaiah Pedipina, Sankar S and R Dhanalakshmi
    • Published in: Dogo Rangsang Research Journal, UGC Care Group I Journal, Vol-10 Issue-07 No. 16 July 2020, ISSN:2347-7180
  • An Improved Framework for Sentiment Analysis for College Reviews
    • Authors: T. Sri Devi, R. Dhanalakshmi, S. Sankar
    • Published in: International Journal of Advanced Trends in Computer Science and Engineering, 9(2), 1959-1963