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:

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.

 

 

 

Ramana Reddy | Electronics Engineering | Most Cited Article Award

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Dr. K.V. Ramana Reddy | Electronics Engineering | Most Cited Article Award

ASSOCIATE PROFESSOR at MALLA REDDY COLLEGE OF ENGINEERING AND TECHNOLOGY, INDIA

Summary:

Dr. K.V. Ramana Reddy is an accomplished academician and researcher with over 8 years of experience in the field of Electrical Engineering. Currently serving as an Associate Professor at Malla Reddy College of Engineering and Technology (Autonomous), his expertise spans power electronics, electric drives, and renewable energy systems. Dr. Reddy is known for his innovative approach to research, which includes exploring advanced technologies in smart grids and electric vehicles. He has previously held leadership roles, including serving as H.O.D., and has been actively involved in mentoring and guiding students through their academic journeys.

Professional Profile:

👩‍🎓Education:

Ph.D. in Electrical Engineering, VIT University, Vellore (2020)

  • Research Focus: Power Electronics and Electric Drives

M.Tech. in Power Electronics & Electric Drives (PE&ED), Jawaharlal Nehru Technological University Anantapur (JNTU-A), A.P. (2011)

  • Sri Venkateswara College of Engineering and Technology (SVCET), Chittoor
  • Grade: 81%

B.Tech. in Electrical and Electronics Engineering (E.E.E.), Jawaharlal Nehru Technological University Anantapur (JNTU-A), A.P. (2009)

  • Sri Mekapati Raja Mohan Reddy Institute of Technology & Science, Udayagiri
  • Grade: 79%

🏢 Professional Experience:

Associate Professor and IIC Coordinator, Malla Reddy College of Engineering and Technology (Autonomous), January 2023 – Present

Associate Professor, Sri Sai Rajeswari Institute of Technology, Proddatur, March 2022 – January 2023

Associate Professor, Sri Sairam College of Engineering, Bangalore, November 2020 – February 2022

Research Scholar, VIT University, Vellore, December 2016 – August 2020

Assistant Professor & H.O.D (Ratified by JNTU-A), Gouthami Institute of Technology & Management for Women, Proddatur, June 2011 – December 2016

Research Interests:

  • Power Electronics
  • Electric Drives
  • Renewable Energy Systems
  • Smart Grids
  • Electric Vehicle Technologies

Dr. K.V. Ramana Reddy’s research primarily focuses on power electronics, electric drives, and renewable energy systems. His work includes the integration of advanced technologies in smart grids and electric vehicle systems, aiming to contribute to sustainable energy solutions. His dedication to academic research and innovative thinking is reflected in his journal publications and his role in guiding students as an academic leader.

Author Metric:

  • Publications: Several peer-reviewed journal articles in reputed journals.
  • Research Citations: A growing number of citations reflecting the impact of his work in the fields of power electronics and renewable energy systems.

Top Noted Publication:

“A review of swarm-based metaheuristic optimization techniques and their application to doubly fed induction generator”

  • Journal: Heliyon
  • Year: 2022
  • Volume: 8, Issue 10
  • Citations: 17

“A review on grid codes and reactive power management in power grids with WECS”

  • Book Chapter: Advances in Smart Grid and Renewable Energy: Proceedings of ETAEERE-2016
  • Year: 2018
  • Citations: 15

“A heuristic approach to optimal crowbar setting and low voltage ride through of a doubly fed induction generator”

  • Journal: Energies
  • Year: 2022
  • Volume: 15, Issue 24
  • Article ID: 9307
  • Citations: 9

“A modified Whale Optimization Algorithm for exploitation capability and stability enhancement”

  • Journal: Heliyon
  • Year: 2022
  • Volume: 8, Issue 10
  • Citations: 9

“An adaptive neuro-fuzzy logic controller for a two-area load frequency control”

  • Journal: International Journal of Engineering Research and Application
  • Year: 2013
  • Pages: 989-995
  • Citations: 8

Ahmed Elhenawy | Drug Design | Best Researcher Award

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Prof. Ahmed Elhenawy, Drug Design, Best Researcher Award

Doctorate at Al-Azhar University, Egypt

Summary:

Prof. Ahmed El-Henawy is a distinguished academic and researcher in the field of Chemistry, specializing in organic chemistry and pharmaceutical sciences. He holds a Ph.D. in Organic Chemistry with a focus on amino acids and proteins from Al-Azhar University in Cairo, Egypt. With over a decade of experience in academia, Prof. El-Henawy has served as a lecturer, assistant lecturer, and demonstrator at Al-Azhar University, where he has taught a wide range of undergraduate and postgraduate courses in organic chemistry.

Throughout his career, Prof. El-Henawy has made significant contributions to the field of peptide synthesis, particularly in the design and synthesis of novel peptide derivatives with antimicrobial and anticancer properties. His research interests also extend to the development of small molecule drugs, biochemical mechanisms of drug action, and spectroscopic analysis techniques.

Professional Profile:

Google Scholar Profile

👩‍🎓Education & Qualification:

Ph.D. in Organic Chemistry:

  • Completed at Al-Azhar University, Cairo, Egypt.
  • Thesis Title: “Synthesis and Study of New Amino Acid Derivatives of Expected Biological Activities”.
  • Specialization: Amino Acids & Proteins.
  • Year of Completion: 2005-2008.

Master of Science (M.Sc.) in Organic Chemistry:

  • Earned at Al-Azhar University, Cairo, Egypt.
  • Thesis Title: “Synthesis and Study of Some Amino Acids Derivatives”.
  • Specialization: Amino Acids & Proteins.
  • Year of Completion: 2002-2005.

One-year Graduate Courses for M.Sc. Degree:

  • Partial fulfillment of the requirements for the M.Sc. degree.
  • Chemistry Department, Faculty of Science, Al-Azhar University, Cairo, Egypt.
  • Year: 2001.

Bachelor of Science (B.Sc.) in Special Chemistry:

  • Obtained from Al-Azhar University, Cairo, Egypt.
  • Year of Completion: 2000.

Professional Experience:  

Prof. Ahmed El-Henawy boasts a rich and extensive professional experience in the field of Chemistry, spanning over several roles and institutions. Since August 2008, he has served as a Lecturer in the Chemistry Department at Al-Azhar University, Cairo, Egypt, where he has been actively involved in teaching undergraduate and postgraduate courses, supervising theses, and contributing to curriculum development. Prior to this, from September 2005 to August 2008, he held the position of Assistant Lecturer at the same institution, where he further honed his teaching and academic skills. Prof. El-Henawy began his academic career as a Demonstrator at Al-Azhar University in September 2002, gaining valuable experience in laboratory instruction and student supervision. In addition to his roles at Al-Azhar University, he has also served as an Assistant Professor at Albaha University, Albaha, KSA, from October 2012 to the present, and as a Professor at Al-Azhar University, Cairo, Egypt, from February 2020 to the present. Throughout his career, Prof. El-Henawy has demonstrated a commitment to excellence in education, research, and academic leadership.

Research Interest:

Peptide Synthesis: Prof. El-Henawy explores the synthesis of novel dipeptide, tripeptide, tetrapeptide, and pentapeptide derivatives with potential antimicrobial activity. This research area involves designing and synthesizing peptide analogs to investigate their bioactivity against microbial pathogens.

Anticancer Agents: He is interested in the synthesis and evaluation of new analogs, such as 2-amino-1,3,4-thiadiazol derivatives, as potential anticancer agents. This research aims to develop novel compounds with enhanced anticancer activity and reduced toxicity profiles.

Small Molecule Drug Design: Prof. El-Henawy is involved in designing and synthesizing small molecule compounds with therapeutic potential. This includes the development of sulfonamide derivatives and other organic molecules with antimicrobial properties.

Biochemical Mechanisms: He investigates the biochemical mechanisms underlying the activity of synthesized compounds, focusing on their interaction with biological targets and elucidating their mode of action. This research contributes to understanding the molecular basis of drug efficacy and toxicity.

Spectroscopic Analysis: Prof. El-Henawy utilizes various spectroscopic techniques, such as UV spectroscopy, FTIR spectroscopy, and NMR spectroscopy, for structural elucidation and characterization of synthesized compounds. These analytical methods provide insights into the chemical structure and properties of organic molecules.

Publication Top Noted:

Title: Synthesis and characterization of some arylhydrazone ligand and its metal complexes and their potential application as flame retardant and antimicrobial additives

  • Authors: H Abd El-Wahab, M Abd El-Fattah, AH Ahmed, AA Elhenawy, NA Alian
  • Journal: Journal of Organometallic Chemistry
  • Volume: 791
  • Pages: 99-106
  • Year: 2015
  • Citations: 46

Title: Nano-amino acid cellulose derivatives: Eco-synthesis, characterization, and antimicrobial properties

  • Authors: M Hasanin, A El-Henawy, WH Eisa, H El-Saied, M Sameeh
  • Journal: International Journal of Biological Macromolecules
  • Volume: 132
  • Pages: 963-969
  • Year: 2019
  • Citations: 45

Title: Naproxen based 1, 3, 4-oxadiazole derivatives as EGFR inhibitors: Design, synthesis, anticancer, and computational studies

  • Authors: MM Alam, S Nazreen, ASA Almalki, AA Elhenawy, NI Alsenani, …
  • Journal: Pharmaceuticals
  • Volume: 14
  • Issue: 9
  • Pages: 870
  • Year: 2021
  • Citations: 41

Title: Experimental and theoretical investigation for 6-Morpholinosulfonylquinoxalin-2 (1H)-one and its haydrazone derivate: Synthesis, characterization, tautomerization and …

  • Authors: DM Elsisi, A Ragab, AA Elhenawy, AA Farag, AM Ali, YA Ammar
  • Journal: Journal of Molecular Structure
  • Volume: 1247
  • Pages: 131314
  • Year: 2022
  • Citations: 36

Title: Design, synthesis and molecular docking studies of thymol based 1, 2, 3-triazole hybrids as thymidylate synthase inhibitors and apoptosis inducers against breast cancer cells

  • Authors: MM Alam, AM Malebari, N Syed, T Neamatallah, ASA Almalki, …
  • Journal: Bioorganic & Medicinal Chemistry
  • Volume: 38
  • Pages: 116136
  • Year: 2021
  • Citations: 35