Ms. Pritha Gupta | Information Security – Postdoctoral Researcher at Ruhr University Bochum, Germany
Pritha Gupta is a promising early-career researcher in the field of artificial intelligence, with a focus on security, privacy, and automated decision systems. Her growing academic profile reflects a commitment to research that bridges machine learning with practical challenges in trustworthy AI. Having co-authored multiple peer-reviewed articles and collaborated with well-established researchers across Europe, Gupta is positioning herself as an emerging voice in secure AI systems and interpretable machine learning.
Profile Verified:
Education:
Gupta has pursued a rigorous academic path in computer science and artificial intelligence, culminating in advanced research conducted at Universität Paderborn. Her academic training is complemented by specialized work in machine learning algorithms, statistical modeling, and applied cryptography. Throughout her education, she has maintained a strong theoretical foundation while focusing on problem-driven research that aligns with current industry and academic needs.
Experience:
During her academic and research journey, Gupta has worked alongside leading scientists in computer science and cybersecurity. She has gained practical and research experience through collaborations with senior professors and researchers at Paderborn University, Wuppertal University, and Karlstad University. Her projects span the design of autonomous systems, ranking algorithms, information leakage detection, and AI-based attack modeling. Gupta’s ability to integrate complex AI models with real-world application challenges, such as cryptographic vulnerabilities and privacy breaches, showcases her deep technical expertise and interdisciplinary thinking.
Research Interests:
Her research centers around trustworthy AI, privacy-preserving systems, automated machine learning (AutoML), and explainable AI (XAI). Gupta’s work increasingly emphasizes side-channel attack detection, secure protocol design, and context-dependent learning, making her research highly relevant in today’s AI-driven digital ecosystems. She is particularly drawn to the ethical and technical dimensions of AI, focusing on how to make machine learning both robust and understandable in sensitive applications.
Awards:
Though still early in her career, Gupta’s contributions have been recognized through selection for collaborative international research projects and co-authorship in high-impact workshops and symposia. Her work has garnered citations from both academic and applied communities, reflecting its relevance and originality. With increasing visibility in the AI and cybersecurity research circuits, she is a strong candidate for early-career and emerging researcher recognitions.
Publications 📚:
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🛻 “Design and implementation of autonomous car using Raspberry Pi” – International Journal of Computer Applications, 2015 – Cited by: 115
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🔄 “Pairwise versus pointwise ranking: A case study” – Schedae Informaticae, 2016 – Cited by: 24
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🧠 “Learning Context-Dependent Choice Functions” – International Journal of Approximate Reasoning, 2021 – Cited by: 19
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🔓 “Automated Side-Channel Attacks using Black-Box Neural Architecture Search” – ARES Conference, 2023 – Cited by: 9
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🕵️♀️ “Automated detection of side channels in cryptographic protocols: DROWN the ROBOTs!” – ACM Workshop on AI and Security, 2021 – Cited by: 9
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📊 “Meta-learning for automated selection of anomaly detectors for semi-supervised datasets” – International Symposium on Intelligent Data Analysis, 2023 – Cited by: 3
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🔐 “Information leakage detection through approximate Bayes-optimal prediction” – arXiv preprint, 2024 – Cited by: 1
Conclusion:
Pritha Gupta exemplifies the attributes of an emerging researcher whose academic rigor, innovative research contributions, and commitment to secure and interpretable AI systems make her an ideal nominee for the Best Researcher Award. Her portfolio combines technical depth, collaborative strength, and real-world relevance, backed by peer recognition through citations and impactful publications. While early in her professional journey, Gupta is steadily building a reputation in AI security and machine learning theory, with a trajectory that strongly indicates future leadership in the field. Her contributions not only advance academic understanding but also address critical societal and technological challenges, making her work valuable across disciplines and sectors. In recognition of her growing impact, innovative thinking, and dedication to responsible AI, she is highly deserving of this honor.