Nikhil Suryawanshi | Software Development | Best Researcher Award

Posted on by Best Paper Award

Mr. Nikhil Suryawanshi | Software Development | Best Researcher Award

Principal Software Engineer at ADT, United States
Summary:

Mr. 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:

He holds two Master’s degrees: an M.S. in 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 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:

Number of Publications: 6

Significant contributions in fields such as machine learning, healthcare, sentiment analysis, air quality prediction, and consumer behavior.

  • Accurate Prediction of Heart Disease Using Machine Learning: 2024
  • Sentiment Analysis with Machine Learning and Deep Learning: A Survey: 2024
  • Enhancing Breast Cancer Diagnosis Through Clustering: 2023
  • Predicting Mental Health Outcomes Using Wearable Device Data and Machine Learning: 2021 
  • Air Quality Prediction in Urban Environment Using IoT Sensor Data: 2020
  • Predicting Consumer Behavior in E-Commerce Using Recommendation Systems: 2019 

Top Noted Publication:

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

  • Journal: International Journal of Innovative Science and Research Technology (IJISRT)
  • Year: 2024
  • Summary: This paper presents a case study on heart disease prediction using the Cleveland dataset, comparing various machine learning models to assess their accuracy and efficacy in diagnosing heart disease.

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

  • Journal: International Journal of Science and Research Archive
  • Volume: 12
  • Issue: 2
  • Pages: 005-015
  • Year: 2024
  • Summary: The paper provides a comprehensive survey of machine learning and deep learning techniques for sentiment analysis, discussing their applications and performance in various domains such as social media, e-commerce, and customer feedback.

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

  • Journal: International Journal of Innovative Science and Research Technology (IJISRT)
  • Year: 2023
  • Summary: This research explores clustering algorithms like K-Means, Agglomerative, and Gaussian Mixture Models to enhance the accuracy of breast cancer diagnosis, emphasizing the role of unsupervised learning in medical diagnostics.

Predicting Mental Health Outcomes Using Wearable Device Data and Machine Learning

  • Journal: International Journal of Innovative Science and Research Technology (IJISRT)
  • Year: 2021
  • Summary: The study investigates the application of machine learning on data collected from wearable devices to predict mental health outcomes, focusing on stress, anxiety, and other health indicators.

Air Quality Prediction in Urban Environment Using IoT Sensor Data

  • Journal: International Journal of Innovative Science and Research Technology (IJISRT)
  • Year: 2020
  • Summary: The paper discusses air quality prediction using IoT sensor data in urban areas, applying machine learning models to predict air pollution levels and analyze environmental impacts.

Predicting Consumer Behavior in E-Commerce Using Recommendation Systems

  • Journal: International Journal of Innovative Science and Research Technology
  • Volume: 4
  • Issue: 9
  • Year: 2019
  • Summary: The study focuses on predicting consumer behavior in e-commerce platforms using recommendation systems, highlighting the effectiveness of machine learning in improving customer engagement and personalization.

Conclusion:

Mr. Nikhil Suryawanshi’s strengths in software development, machine learning, and healthcare analytics, combined with his extensive professional experience, make him a solid candidate for the Best Researcher Award. His technical expertise and contributions to the IT and academic communities are commendable. However, expanding his research impact through more collaborative efforts and publishing in top-tier journals could further enhance his candidacy for such an award. Overall, Nikhil is a deserving candidate, particularly given his innovative work in healthcare and predictive analytics.

 

 

 

Shriyash Shete | User Experience Design | Best Researcher Award

Posted on by Best Paper Award

Mr. Shriyash Shete, User Experience Design, Best Researcher Award

Shriyash Shete at Zscaler, Inc, United States

Summary:

Mr. Shriyash Shete is a seasoned professional in Product and User Experience Design, currently serving as a Senior UX Designer at Zscaler. With over 8 years of industry experience, he specializes in demystifying the complexities of Cybersecurity through innovative design solutions. Shriyash holds a Master of Science degree in Human-Computer Interaction (HCI) from Indiana University Bloomington, where he honed his expertise in designing user-centric interfaces. Throughout his career, he has led diverse UX projects spanning cybersecurity, emerging technologies, healthcare, education, e-commerce, and mobility, making significant contributions to both consumer-facing and enterprise products. Shriyash’s achievements include being a top mentor on ADPList, receiving international awards for his innovations in UX design for cybersecurity, and filing several US patents. He is known for his dedication to shaping impactful user experiences and driving design excellence in the cybersecurity domain.

Professional Profile:

Google Scholar Profile

👩‍🎓Education & Qualification:

Professional Experience:  

Mr. Shriyash Shete has accumulated over 8 years of professional experience in Product and User Experience Design. Currently, he holds the position of Senior UX Designer at Zscaler, where he plays a pivotal role in shaping the design strategy by collaborating with security researchers and executives. His responsibilities include leading UX projects for brand new enterprise security products such as Risk360 and ZSLogin, designing critical features, and ensuring a seamless user experience for over 8000 customers worldwide. Additionally, Shriyash is actively involved in the UX hiring committee at Zscaler, contributing to the growth and development of the design team. Throughout his career, he has led diverse projects spanning cybersecurity, emerging technologies, healthcare, education, e-commerce, mobility, and design systems for both consumer-facing (B2C) and enterprise (B2B) products. Shriyash’s dedication to excellence in UX design is reflected in his achievements, including being recognized as one of the top mentors on ADPList, receiving international awards for his innovations in UX design for cybersecurity, and filing several US patents.

Research Interest:

Mr. Shriyash Shete’s research interests revolve around enhancing user experiences and addressing challenges in cybersecurity through innovative design solutions. He is particularly interested in investigating the intersection of cybersecurity and emerging technologies such as artificial intelligence (AI), machine learning (ML), augmented reality (AR), and virtual reality (VR) to develop intuitive and secure user interfaces. Additionally, Shriyash is passionate about exploring the application of data analytics in cybersecurity, aiming to leverage insights for proactive threat detection and mitigation strategies. His research also extends to areas such as healthcare, education, e-commerce, and mobility, where he seeks to identify opportunities for enhancing user engagement, accessibility, and trust. Through his research endeavors, Shriyash aims to contribute to the advancement of cybersecurity practices and improve the overall user experience in digital environments.

Publication Top Noted:

Title: ReMotive: Enhancing Digital Calendar Experience with AI

  • Journal: Journal of Artificial Intelligence & Cloud Computing
  • Volume: 1
  • Issue: 2
  • Year: 2022

Title: Ansys AR: Augmented Reality App Concept to Enhance 3D Design and Simulation Experience

  • Journal: Journal of Artificial Intelligence & Cloud Computing
  • Volume: 1
  • Issue: 1
  • Year: 2022

Title: Gamifying Jellow: A Communication Aid for Children with Developmental Disabilities

  • Journal: Journal of Engineering and Applied Sciences Technology
  • Volume: 3
  • Issue: 3
  • Year: 2021

Title: Designing Financial Fitness Smartphone App: A Case Study

  • Journal: Journal of Economics & Management Research
  • Volume: 2
  • Issue: 2
  • Year: 2021

Title: Envisioning The Enhanced Experience of Pune Metro Commuters with A User-Centered Information System

  • Journal: Journal of Engineering and Applied Sciences Technology
  • Volume: 3
  • Issue: 1
  • Year: 2021