Nikhil Suryawanshi | Software Development | Best Researcher Award

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Mr. Nikhil Suryawanshi | Software Development | Best Researcher Award

Principal Software Engineer at ADT, United States
Summary:

Dr. Nikhil Suryawanshi is a seasoned Principal Software Engineer with extensive experience in software development, machine learning, and data analysis. His career spans over a decade, during which he has contributed to numerous high-profile projects across industries, including technology, education, and healthcare. His commitment to quality software solutions, coupled with his passion for research, positions him as a thought leader in his field. Nikhil is also actively engaged in the academic community as a peer reviewer for several international journals, including the Cureus Springer Journal and the International Journal of Innovative Research in Engineering (IJIRE). He continues to contribute to advancements in software engineering and data science.

Professional Profile:

👩‍🎓Education:

Nikhil Suryawanshi earned his Doctorate in Computer Science from Judson University, Illinois, USA, in July 2024, achieving a CGPA of 3.7. He also holds two Master’s degrees: an M.S. in Information Technology Management from Campbellsville University, Kentucky, USA, with a CGPA of 3.5, awarded in 2019, and an M.S. in Computer Science from San Francisco Bay University, California, USA, with a CGPA of 3.94, awarded in 2016. He completed his Bachelor of Engineering in Information Technology at Sinhgad Academy of Engineering, Pune, India, in 2010, graduating with a CGPA of 3.50.

🏢 Professional Experience:

Nikhil Suryawanshi has amassed over 15 years of experience in the IT industry, currently serving as a Principal Software Engineer at ADT Commercial, CA, USA, since July 2019. He leads a team of eight, providing expertise in software development, project management, and training. His technical proficiencies span across Python, .Net, AngularJS, SQL, and software testing, where he has delivered high-quality software solutions and collaborated in leadership meetings to drive corporate strategy. Previously, he worked as a Senior Software Engineer at the same company, contributing to Python-based software development and network testing.

Earlier in his career, Nikhil was an Analytics Manager at IMRB Abacus, Pune, India (2014–2015), where he led data mining and analysis projects for Unilever brands using SPSS and SQL. Before that, he was an Assistant Professor at Sandip Foundation, Nashik, India (2012–2014), teaching Database Management Systems and Computer Networks, while also guiding students on final-year projects. His industry journey began as a Software Engineer at IMRB Abacus, Mumbai, India (2011–2012), where he designed online surveys and dashboards for statistical analysis.

Research Interests:

Nikhil Suryawanshi’s research interests lie in machine learning, sentiment analysis, and data clustering techniques. He is particularly focused on predictive analytics in healthcare and enhancing diagnostic capabilities using machine learning algorithms. His recent research delves into sentiment analysis with machine learning and deep learning techniques, as well as applications of clustering methods like K-Means and Gaussian Mixture Models in healthcare data.

Author Metrics:

  • Suryawanshi, N. S. (2024). “Sentiment analysis with machine learning and Deep Learning: A survey of techniques and applications.” International Journal of Science and Research Archive (IJSRA). Volume 12, Issue 2, June 2024.
  • Suryawanshi, N. S. (2024). “Accurate Prediction of Heart Disease Using Machine Learning: A Case Study on the Cleveland Dataset.” International Journal of Innovative Science and Research Technology (IJISRT). Volume 9, Issue 7, July 2024.
  • Suryawanshi, N. S. (2023). “Enhancing Breast Cancer Diagnosis Through Clustering: A Study of K-Means, Agglomerative, and Gaussian Mixture Models.” International Journal of Innovative Science and Research Technology (IJISRT). Volume 8, Issue 7, July 2023.

In addition to his publications, Nikhil has been a peer reviewer for several prestigious journals and serves as a judge at the Stevie Awards for Women In Business. He is also an active member of multiple professional associations, including the International Association of Engineers (IAENG) and the Scholars Academic and Scientific Society (SASS).

Top Noted Publication:

Accurate Prediction of Heart Disease Using Machine Learning: A Case Study on the Cleveland Dataset

  • Author: Nikhil Sanjay Suryawanshi
  • Published in: International Journal of Innovative Science and Research Technology (IJISRT)
  • Volume: 9, Issue: 7
  • Publication date: July 2024
  • Pages: 1042-1049
  • DOI: https://doi.org/10.38124/ijisrt/IJISRT24JUL1400
  • Abstract: This paper explores the use of machine learning techniques to predict heart disease using the Cleveland dataset. By analyzing multiple machine learning models, the study highlights how accurate predictions can improve medical diagnoses.

Sentiment Analysis with Machine Learning and Deep Learning: A Survey of Techniques and Applications

  • Author: Nikhil Sanjay Suryawanshi
  • Published in: International Journal of Science and Research Archive (IJSRA)
  • Volume: 12, Issue: 2
  • Publication date: June 2024
  • Pages: 005-015
  • DOI: https://doi.org/10.30574/ijsra.2024.12.2.1205
  • Abstract: This paper provides a comprehensive survey of sentiment analysis techniques using machine learning and deep learning. It discusses various algorithms and their applications in analyzing textual data, emphasizing advancements in natural language processing.

Enhancing Breast Cancer Diagnosis Through Clustering: A Study of KMeans, Agglomerative, and Gaussian Mixture Models

  • Author: Nikhil Sanjay Suryawanshi
  • Published in: International Journal of Innovative Science and Research Technology (IJISRT)
  • Volume: 8, Issue: 7
  • Publication date: July 2023
  • Pages: 3497-3504
  • DOI: https://doi.org/10.38124/ijisrt/ijisrt23jul2308
  • Abstract: This study focuses on enhancing breast cancer diagnosis using clustering algorithms, including KMeans, agglomerative clustering, and Gaussian Mixture Models. It evaluates the effectiveness of these clustering methods in identifying patterns that can support medical professionals in diagnosing breast cancer.

Conclusion:

Mr. Nikhil Suryawanshi is a highly qualified candidate for the Best Researcher Award, particularly due to his innovative work in machine learning and its applications in healthcare. His career reflects a strong balance between industry leadership and academic contributions, with research that directly impacts medical diagnostics and software engineering practices. However, to further solidify his candidacy for such an award, he could focus on increasing his contributions to high-impact academic research and fostering multi-disciplinary international collaborations. Overall, his body of work demonstrates a commendable blend of applied research and practical problem-solving, making him a strong contender for the award.