Anmol Aggarwal | Computer Science | Best Researcher Award | 13432

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Mr. Anmol Aggarwal | Computer Science | Best Researcher Award | 13432

Mr. Anmol Aggarwal, Intuit, United States

Anmol Aggarwal is a seasoned product leader and computer science professional with a strong foundation in AI, pricing strategy, and marketplace dynamics. He has delivered high-impact results at companies like Uber and Intuit, while also founding and scaling startups in cloud migration and recruitment tech. Anmol holds an MBA from UC Berkeley Haas and an MS in Computer Science from UC San Diego. His research in neural networks and genetic algorithms has earned him multiple publications and the Best Researcher Award in Computer Science.

Profile

Google Scholar

🎓 Early Academic Pursuits

Anmol Aggarwal’s journey into the world of technology and innovation began with a deep-rooted passion for computer science. He earned his Bachelor of Engineering in Computer Science from Guru Gobind Singh Indraprastha University, where his curiosity for solving complex computational problems flourished. His early academic years were marked by an intensive focus on algorithm design, artificial intelligence, and neural networks, leading to multiple publications in international journals and conferences — a rare achievement at the undergraduate level. He further pursued a Master of Science in Computer Science from the University of California, San Diego, where he honed his expertise in machine learning, distributed systems, and large-scale software engineering. Building on this foundation, Anmol enrolled in the MBA program at UC Berkeley’s Haas School of Business, combining his technical acumen with sharp business instincts. There, he was recognized for his curiosity and commitment to learning, earning the prestigious “Student Always” Award, a distinction given to only one student in the entire cohort.

💼 Professional Endeavors

Anmol’s professional journey is a blend of deep engineering proficiency and strategic product leadership. Starting his career as a Business Technology Associate at ZS Associates, he quickly moved into more technical roles, including Software Engineer at Adobe where he contributed to enterprise-grade tools.

His most transformative phase came with his tenure at Uber, where he progressed from software engineer to Product Manager and led global initiatives impacting millions of users. His work in Courier Pricing, Eater Pricing, and Marketplace Optimization delivered tangible results — from improving courier retention by 7% to generating a surplus of $200M for reinvestment.

🧠 Contributions and Research Focus

Anmol’s passion for research began early, as demonstrated by seven publications during his undergraduate years. His papers span across diverse applications of neural networks, genetic algorithms, and fuzzy logic, solving real-world problems such as the Traveling Salesman Problem, protein structure prediction, and emotion recognition from speech. His work often explored the intersection of bio-inspired computing and machine learning, a forward-thinking approach that earned him the “Best Researcher Award” in Computer Science. Through these contributions, Anmol helped advance early academic thinking on parallel genetic algorithms and adaptive optimization methods.

🏆 Accolades and Recognition

Anmol’s career is dotted with honors that reflect both his intellectual rigor and leadership qualities:

  • Best Researcher Award – Computer Science

  • “Student Always” Award – UC Berkeley Haas

  • Winner of 6 National and International Case Competitions

  • Leadership roles at Uber and Toastmasters, including Chair of the Rider Pricing Social Committee, managing a $40K annual budget.

His ability to lead teams — whether it’s engineers, business stakeholders, or global executives — has made him a highly regarded figure in both corporate and startup ecosystems.

🌍 Impact and Influence

Anmol’s influence extends beyond large tech companies. He has actively contributed to early-stage startups, such as:

  • Jobshine: Revived a blue-collar job marketplace, led the rebuild with a 6-person engineering team, and boosted revenue by 400%.

  • Hoistr.ai: Co-founded a cloud migration tooling startup, secured partnerships with GCP leaders, and drove early design and fundraising efforts.

Through these ventures, Anmol has played a critical role in identifying market gaps, achieving product-market fit, and accelerating revenue growth in nascent businesses. His mentorship, leadership, and analytical approach continue to influence product managers, engineers, and entrepreneurs alike.

🚀 Legacy and Future Contributions

Looking ahead, Anmol Aggarwal is poised to become a thought leader in AI-powered product management. With his rare combination of technical depth, business insight, and a global mindset, he is well-positioned to drive innovation across fintech, edtech, and marketplaces. His future goals likely include contributing to the broader tech-for-good movement, mentoring aspiring technologists, and continuing to publish insights at the intersection of artificial intelligence, ethics, and human-centered design. Whether scaling startups, innovating within tech giants, or contributing to the next wave of academic research, Anmol’s legacy will be defined by impact at scale, deep intellectual curiosity, and a commitment to uplifting others along the way.

Publication Top Notes

A novel method for medical disease diagnosis using artificial neural networks based on backpropagation algorithm

Author: JS Bhalla, A Aggarwal

Journal:  The Next Generation Information Technology Summit

Year: 2013

Using Adaboost Algorithm along with Artificial neural networks for efficient human emotion recognition from speech

Author: A Aggarwal, JS Bhalla

Journal: International Conference on Control, Automation, Robotics and Embedded

Year: 2013

Prediction of Protein Structure using Parallel Genetic Algorithm

Author: JS Bhalla, A Aggarwal

Journal: International Journal of Computer Applications

Year: 2013

Yunxia Chen | Data Science | Best Researcher Award | 13362

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Prof. Yunxia Chen | Data Science | Best Researcher Award 

Prof. Yunxia Chen, School of Reliability and Systems Engineering, Beihang University, China

Prof. Yunxia Chen is a distinguished researcher and professor at the School of Reliability and Systems Engineering, Beihang University, China. Her pioneering work in system reliability has led to significant advancements in failure mechanism modeling, life prediction, and high-reliability design. With over 57 SCI publications, 43 patents, and leadership in multiple national projects, she has shaped both academic and industrial practices. Prof. Chen’s collaborations with top international researchers and her leadership roles in global conferences reflect her influence in the field. Her contributions have earned her two prestigious National Defense Science and Technology Progress Awards.

Profile

Scopus

🌱 Early Academic Pursuits

Prof. Yunxia Chen’s academic journey began with a deep-rooted interest in systems engineering and mechanical reliability—fields that demand both precision and vision. Her early education laid a strong foundation in engineering principles, which she further solidified through her pursuit of a doctoral degree. Earning her Ph.D. equipped her with advanced knowledge and skills to tackle the complexities of system reliability. These formative years were marked by curiosity, discipline, and a relentless pursuit of knowledge—traits that would define her future contributions to engineering science.

🏛️ Professional Endeavors

Prof. Chen currently serves as a Professor and Research Dean at the School of Reliability and Systems Engineering, Beihang University, one of China’s premier research institutions. Over the years, she has built a robust portfolio of leadership roles in research and academia. Her professional scope extends beyond traditional academic duties to include shaping national and international engineering standards, managing high-impact research projects, mentoring emerging scholars, and fostering interdisciplinary collaborations.

Her commitment to innovation and academic excellence is evidenced by her role in the development of two national industry standards, showcasing her impact on policy as well as practice. Moreover, her ability to balance administrative, teaching, and research responsibilities highlights her dynamic and multifaceted academic persona.

🔬 Contributions and Research Focus

Prof. Chen has made groundbreaking contributions in the domain of complex system reliability, particularly in understanding failure mechanism evolution, failure behavior propagation, and data-physics-driven prognostics. Her research interests span:

  • Reliability modeling and simulation of complex systems

  • High-reliability and long-lifetime design techniques

  • Experimental methodologies for small-sample evaluation

  • Fault-physics based verification systems

  • Advanced prognostics and health management systems (PHM)

Notably, she has authored over 57 SCI-indexed journal papers, published a monograph, and holds 43 authorized invention patents. Her research has had over 1200 citations, including 31 publications in top-tier journals and one highly cited paper, demonstrating her work’s relevance and influence.

Prof. Chen’s research portfolio includes 12 major projects, 35 consultancy assignments, and numerous editorial responsibilities. Her active involvement as an Area Editor, Program Committee Member, and Organizing Chair for prestigious international conferences further underscores her commitment to the global scientific community.

🏆 Accolades and Recognition

Prof. Chen’s scholarly achievements have been recognized with two First Prizes in the National Defense Science and Technology Progress Awards—one of the highest honors in China’s scientific community. These awards celebrate her pioneering work in system reliability research and her impactful role in advancing national defense technologies.

In addition, she holds several editorial and leadership positions in major technical journals and societies, including:

  • Executive Committee Member, Reliability Engineering Branch (CSME)

  • Vice Chairman, Reliability Branch of the China Electronics Society

Her leadership and expertise are widely acknowledged within both academic and industrial circles, further validating her status as a thought leader in her field.

🌍 Impact and Influence

Prof. Chen’s influence extends beyond borders. She has engaged in high-impact collaborations with renowned scholars such as Professor Frank Lam, Professor Terje Haukaas, and Professor Gadala Mohamed S. at the University of British Columbia, Canada. These collaborations explore reliability system modeling based on fault physics, facilitating knowledge exchange and co-development of innovative solutions.

Her work has shaped engineering practices, industry standards, and higher education curricula, setting benchmarks for excellence in system reliability engineering. As a mentor, she has inspired and guided numerous young researchers who are now making their own contributions to the field.

🌟 Legacy and Future Contributions

As she continues to lead cutting-edge research and influence future generations, Prof. Chen’s legacy lies in her integrative approach to engineering challenges—combining theory, practice, data, and innovation. She envisions a future where smart, self-healing systems proactively adapt to environmental and operational stresses, thus minimizing failure and maximizing safety and efficiency.

In the coming years, her focus will include:

  • Enhancing AI-integrated reliability prediction systems

  • Developing intelligent, adaptive maintenance strategies

  • Expanding international research networks for collaborative problem-solving

Publication Top Notes

Causal graph-based spatial–temporal attention network for RUL prediction of complex systems

Author: S., Zheng, Shuwen, J., Liu, Jie, Y., Chen, Yunxia, Y., FAN, Yu, D., Xu, Dan
Journal: Computers and Industrial Engineering, 
Year: 2025

Meta-learning collaborative optimization for lifetime prediction of lithium-ion batteries considering label noise

Author: G., Wang, Guisong, C., Wang, Cong, Y., Chen, Yunxia, J., Liu, Jie

Journal: Energy Storage,

Year: 2025

Unsupervised dynamic prognostics for abnormal degradation of lithium-ion battery

Author: C., Wang, Cong, Y., Chen, Yunxia

Journal: Applied Energy,

Year: 2024

 

 

Mohamed Reda Shoeib | Artificial Intelligence | Best Researcher Award

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Dr. Mohamed Reda Shoeib | Artificial Intelligence | Best Researcher Award

Nanyang Technological University at School of Computer Science and Engineering, Nanyang Technological University, Singapore.

Mohamed R. Shoaib is a dedicated Machine Learning and Data Scientist Engineer with extensive expertise in AI and its applications. He holds a Master’s degree in Engineering Science from Menoufia University and is currently pursuing a PhD at Nanyang Technological University. Mohamed has received certifications from Udacity, DataCamp, IBM, and Udemy, demonstrating proficiency in machine learning, deep learning, NLP, and AI. He has a rich professional background, including his role at Shgardi Company where he works on recommendation systems, fraud detection, and user interaction analysis. His research interests span the utilization of AI in biomedical applications, smart agriculture, and global food security. Mohamed’s skills encompass machine learning, deep learning, computer vision, NLP, and embedded systems, making him a valuable asset in the AI and data science community.

Professional Profiles:

Education 🎓

Mohamed R. Shoaib is currently pursuing his Doctor of Philosophy at Nanyang Technological University (NTU), Singapore, within the School of Computer Science and Engineering (SCSE). He began this journey in January 2023, focusing his research on Machine Learning, Data Science, and Artificial Intelligence, particularly their applications in Biomedical, Agriculture, and communication sectors. Prior to this, Mohamed completed his Master’s Degree in Engineering Science from the Faculty of Engineering, Menoufia University, from October 2019 to March 2022. His thesis centered on the Utilization of Artificial Intelligence Techniques in Healthcare Applications, earning a Pre-Master GPA of 3.46/4. Additionally, Mohamed holds a Diploma in Artificial Intelligence from the Information Technology Institute (ITI), which he completed in collaboration with EPITA School of Engineering and Computer Science, between April 2021 and January 2022.

Professional Experience 💼

Mohamed R. Shoaib is currently working as a full-time Machine Learning Engineer and Data Scientist at Shgardi Company, a position he has held since February 2022. In this role, he leverages Amazon Personalized tools and time-series data to enhance recommendation systems. He is also involved in developing solutions to detect fraud and fake user interactions. Alongside his professional role, Mohamed is a full-time researcher at Nanyang Technological University (NTU), Singapore, where he focuses on applying AI in Biomedical, Agriculture, and communication applications. His academic and professional endeavors demonstrate a robust integration of advanced AI techniques to address practical challenges in various fields.

Research Interest 🔍

Mohamed R. Shoaib’s research interests lie at the intersection of machine learning, data science, and artificial intelligence, with a specific focus on their applications in healthcare and environmental fields. He is particularly interested in utilizing artificial intelligence techniques for critical environmental applications, including smart agriculture and satellite imagery analysis. His work also extends to developing deep learning models for biomedical applications, such as brain tumor diagnosis, and enhancing recommendation systems using advanced AI tools. Mohamed is dedicated to advancing the practical applications of AI to solve real-world problems, improve healthcare outcomes, and contribute to sustainable environmental practices.

Awards and Honors 🏆

Mohamed R. Shoaib has received several prestigious awards and honors recognizing his contributions to the fields of machine learning, data science, and artificial intelligence. His outstanding academic and research performance has earned him the Global Health Impact Award 2024 for his innovative work in applying AI to healthcare. He was also recognized by Udacity with a Nanodegree certification in AWS Machine Learning Foundations in 2021, demonstrating his expertise in leveraging cloud-based tools for AI applications. Additionally, Mohamed has been honored by DataCamp and IBM for his proficiency in data science, machine learning, and natural language processing, having completed extensive certification programs in these areas. These accolades reflect his commitment to advancing the field of AI and his exceptional skills in utilizing AI techniques for impactful and transformative solutions.

Research Skills 🧠

Mohamed R. Shoaib is highly skilled in machine learning, deep learning, and AI, specializing in areas such as transfer learning, object detection, and time series forecasting. He excels in computer vision, image processing, NLP, and recommender systems, with additional strengths in reinforcement learning and embedded systems. Proficient in C, Python, and MATLAB, Mohamed is also adept at using AI frameworks like TensorFlow, Keras, and Scikit-learn, as well as Big Data tools like Spark. His problem-solving abilities and expertise in data visualization and dashboard creation with Plotly enhance his capability to develop innovative solutions. Mohamed’s broad skill set equips him to address complex AI challenges and contribute significantly to the field.

Publications

  1. Efficient Framework for Brain Tumor Detection Using Different Deep Learning Techniques
    • Authors: F Taher, M Shoaib, HM Emara, KM Abdelwahab, A El-Samie, E Fathi, …
    • Journal: Frontiers in Public Health
    • Year: 2022
    • Citations: 22
  2. Deep convolutional neural networks for COVID‐19 automatic diagnosis
    • Authors: Emara HM, Shoaib MR, Elwekeil M, El‐Shafai W, Taha TE, …
    • Journal: Microscopy Research and Technique
    • Year: 2021
    • Citations: 22
  3. Hybrid classification structures for automatic COVID-19 detection
    • Authors: MR Shoaib, HM Emara, M Elwekeil, W El-Shafai, TE Taha, AS El-Fishawy, …
    • Journal: Journal of Ambient Intelligence and Humanized Computing
    • Year: 2022
    • Citations: 16
  4. Deepfakes, misinformation, and disinformation in the era of frontier AI, generative AI, and large AI models
    • Authors: MR Shoaib, Z Wang, MT Ahvanooey, J Zhao
    • Conference: 2023 International Conference on Computer and Applications (ICCA)
    • Year: 2023
    • Citations: 13
  5. Simultaneous super-resolution and classification of lung disease scans
    • Authors: HM Emara, MR Shoaib, W El-Shafai, M Elwekeil, EED Hemdan, …
    • Journal: Diagnostics
    • Year: 2023
    • Citations: 13
  6. Efficient deep learning models for brain tumor detection with segmentation and data augmentation techniques
    • Authors: MR Shoaib, MR Elshamy, TE Taha, AS El‐Fishawy, FE Abd El‐Samie
    • Journal: Concurrency and Computation: Practice and Experience
    • Year: 2022
    • Citations: 13
  7. Efficient brain tumor detection based on deep learning models
    • Authors: MR Shoaib, MR Elshamy, TE Taha, AS El-Fishawy, FE Abd El-Samie
    • Journal: Journal of Physics: Conference Series
    • Year: 2021
    • Citations: 13
  8. Automatic modulation classification with 2D transforms and convolutional neural network
    • Authors: HS Ghanem, MR Shoaib, S El‐Gazar, H Emara, W El‐Shafai, …
    • Journal: Transactions on Emerging Telecommunications Technologies
    • Year: 2022
    • Citations: 9
  9. Automated diagnosis of EEG abnormalities with different classification techniques
    • Authors: E Abdellatef, HM Emara, MR Shoaib, FE Ibrahim, M Elwekeil, W El-Shafai, …
    • Journal: Medical & Biological Engineering & Computing
    • Year: 2023
    • Citations: 4
  10. A survey on the applications of frontier AI, foundation models, and large language models to intelligent transportation systems
    • Authors: MR Shoaib, HM Emara, J Zhao
    • Conference: 2023 International Conference on Computer and Applications (ICCA)
    • Year: 2023
    • Citations: 4