Mandar Parab Appointed as Judge for 2026 Global Recognition Awards

Mandar Parab joins the Global Recognition Awards judging panel, leveraging machine learning expertise at Levi Strauss & Co., Epic for Kids, and NIO. His background in artificial intelligence enables rigorous evaluation of innovative achievements.

New York, NY, United States, February 16, 2026 — Mandar Parab, a machine learning engineer at a major technology company, has been appointed as a judge for the 2026 Global Recognition Awards, bringing over a decade of expertise in artificial intelligence and machine learning to the evaluation panel. The appointment recognizes Parab’s distinguished career developing innovative solutions across multiple industries and his demonstrated ability to assess technical excellence at the highest levels. His specialized competencies in supervised learning, deep learning, computer vision, natural language processing, and robotics provide him with a comprehensive understanding of emerging technologies, positioning him uniquely to evaluate exceptional achievements across diverse sectors.

Photo Courtesy of Mandar Parab

Parab’s career across major technology companies and innovative startups has equipped him with the multifaceted perspective necessary to judge innovations. His hands-on experience in architecting production-level systems serving millions of users demonstrates his practical understanding of how theoretical concepts translate into real-world impact. His work has consistently bridged the gap between cutting-edge research and scalable implementation, which makes him particularly well-suited to evaluate whether award submissions represent genuine advancement or merely incremental improvements. His experience across healthcare applications, autonomous systems, consumer technology platforms, and enterprise solutions enables him to assess innovations across virtually any industry sector with equal competence.

Technical Leadership Across Industry Sectors

Parab’s qualifications as a judge stem from his proven track record of architecting production-level systems that have fundamentally altered how organizations leverage artificial intelligence to drive business outcomes. In June 2024, he advanced sophisticated machine learning infrastructure at a leading technology company, while his prior role at Levi Strauss & Co. demonstrated his ability to translate complex algorithms into tangible business value through forecast models that drive monthly and annual planning decisions for global apparel operations. His development of traditional machine learning and deep learning solutions required collaboration with cross-functional teams, which gave him insight into how precision improvements impact business outcomes across entire organizations rather than isolated technical metrics.

His implementation of automated pipelines using Apache Airflow and expertise with Google Cloud Platform’s machine learning stack showcase the breadth of technical knowledge he brings to evaluating innovation. His work on generative AI-based, personalized email marketing applications leveraging Vertex AI demonstrates a forward-thinking approach to emerging technologies. His creation of general-purpose machine learning frameworks and feature stores shared across multiple developers at Levi Strauss & Co. reveals his understanding of how innovation scales within organizations, enabling him to assess whether proposed solutions can move beyond prototype stages to achieve meaningful adoption.

Innovation in Machine Learning Architectures and Systems

Parab’s three-year tenure at Epic for Kids exemplifies his ability to innovate by combining multiple artificial intelligence disciplines to create systems that measurably improve user outcomes through the thoughtful application of recommendation models, speech recognition, natural language processing, and graph-based algorithms. He architected collaborative filtering systems and implemented novel deep learning architectures, including RippleNet, WideandDeep, and DeepandCross, for book recommendations, which serve 30 percent of the platform’s browse functionality. His knowledge graph infrastructure powers 40 percent of the core features that millions of young readers use daily. His work with text-to-speech systems showcases the technical versatility crucial for evaluating diverse innovations, as training state-of-the-art architectures such as Tacotron2 and FastPitch required him to master acoustic modeling, neural vocoding, and prosody generation simultaneously.

Parab’s research background in healthcare artificial intelligence adds a critical perspective to his judging capabilities, as he developed deep learning solutions for ankle fracture detection from X-ray images at Penn State University, achieving a 0.25 increase in performance through convolutional neural networks and transfer learning approaches that addressed the high false-positive rates in radiologist diagnoses. During his tenure at NIO, he designed end-to-end behavior models for autonomous vehicle simulations while optimizing featurization code to run 800 times faster, which enabled real-time simulation of complex traffic scenarios with 100 agents that previously would have required impractical computational resources. His experience building data-distributed training jobs leveraging multi-GPU configurations in PyTorch provides technical depth for assessing computational efficiency claims. The development of Flask APIs with Docker containerization and deployment via Kubernetes demonstrates his understanding of the whole machine learning lifecycle, from research through production deployment.

Final Words

Alex Sterling from the Global Recognition Awards stated, “Mandar Parab’s appointment as a judge brings invaluable expertise to the evaluation process because his hands-on experience developing solutions that have served millions of users across multiple industries provides the practical perspective necessary to identify truly exceptional innovations.” Sterling noted that Parab’s rare combination of deep technical expertise, production implementation experience, and understanding of business impact distinguishes him from purely academic evaluators who may lack insight into real-world constraints and deployment challenges. The organization is confident that his contributions will elevate the quality and rigor of award selections by ensuring that recognized innovations represent genuine advancement rather than incremental improvements or theoretical concepts without practical application.

Sterling added that what makes Parab particularly well-suited for this judging role is his career in the full spectrum of artificial intelligence applications, from autonomous vehicle simulations to children’s educational platforms, and from healthcare diagnostics to fashion industry forecasting. His ability to create shared frameworks that enable entire teams reflects the collaborative mindset the organization values in its judging panel because exceptional innovation rarely emerges from isolated efforts but rather from systematic approaches that can be replicated and scaled across organizations. The Global Recognition Awards expect that Parab’s technical acumen, combined with his practical experience, will help identify innovations that demonstrate technical excellence and deliver measurable impact in their respective industries.

About Global Recognition Awards

Global Recognition Awards is an international organization that recognizes exceptional companies and individuals who have made significant contributions to their industries.

Contact Info:
Name: Alexander Sterling
Email: Send Email
Organization: Global Recognition Awards
Website: https://globalrecognitionawards.org

Release ID: 89183561

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