Elaheh Bakhtiari | Computer Science and Artificial Intelligence | Innovative Research Award

Published on by Innovation Technologist

Innovative Research Award

Elaheh Bakhtiari
University of Messina, Italy

Elaheh Bakhtiari
Affiliation University of Messina
Country Italy
Scopus ID 60866885400
Documents 1
Citations 1
h-index 1
Subject Area Computer Science and Artificial Intelligence
Event Global Innovation Technologist Awards
ORCID 0009-0009-1571-355X

Elaheh Bakhtiari is a researcher affiliated with the University of Messina, Italy, whose documented research profile is situated within Computer Science and Artificial Intelligence. Available bibliographic information records one indexed document, one citation, and an h-index of 1. Her documented publication activity includes research examining an AI-assisted framework for anxiety support among university students, connecting computational methods with an applied behavioral-health context.

Abstract

Bakhtiari’s documented research includes the September 2026 journal article A Hybrid AI-Assisted Framework for Anxiety Support: System Description and Exploratory Findings Among University Students, published in Behavioral Sciences. The work describes an AI-assisted framework addressing anxiety-support needs among university students and represents an interdisciplinary intersection of artificial intelligence, computational systems, and behavioral science. The publication provides the principal documented basis for assessing the researcher’s current scholarly profile. [1]

Keywords

  • Artificial intelligence
  • AI-assisted systems
  • Anxiety support
  • University students
  • Behavioral science

Introduction

Artificial intelligence is increasingly being investigated as a component of digital systems designed to support complex human-centered needs. Within this context, Bakhtiari’s reported publication addresses an AI-assisted framework for anxiety support among university students. The study is notable for positioning computational assistance within a behavioral-science application rather than treating artificial intelligence solely as a technical research problem. [1]

Research Profile

The available Scopus profile records one document, one citation, and an h-index of 1. These indicators describe an early or limited indexed publication record and should be interpreted in relation to the documented size and maturity of the profile. The stated subject area, Computer Science and Artificial Intelligence, provides the primary disciplinary classification for the researcher’s current recognition profile. [2]

Research Contributions

The principal documented contribution is the exploration of a hybrid AI-assisted framework for anxiety support. By combining artificial intelligence with a student-centered behavioral application, the work contributes to discussion around how computational systems may be incorporated into supportive environments. Its exploratory character also provides a basis for further investigation, validation, and development of AI-enabled support approaches. [1]

Publications

A Hybrid AI-Assisted Framework for Anxiety Support: System Description and Exploratory Findings Among University Students. Published in Behavioral Sciences in September 2026. The article is available through the publisher’s website. [1]

Research Impact

The currently documented bibliometric impact is modest, with one citation and an h-index of 1. Nevertheless, the publication’s interdisciplinary focus places the work at the intersection of artificial intelligence and behavioral support, an area in which continued research could contribute to the development and evaluation of human-centered computational systems. Impact should be reassessed as additional publications and citations become available. [2]

Award Suitability

For the Global Innovation Technologist Awards, the documented profile demonstrates a relevant connection between artificial intelligence research and an applied human-centered problem. The publication provides evidence of current scholarly activity and an interdisciplinary research direction. Award consideration should be based on the documented publication, research relevance, originality, methodological contribution, and the broader evidence available during formal evaluation.

Conclusion

Elaheh Bakhtiari’s documented research profile reflects an emerging contribution in Computer Science and Artificial Intelligence, with a particular interdisciplinary application to AI-assisted anxiety support. The 2026 publication provides a clear basis for recognizing research activity while the limited bibliometric record indicates that longer-term impact remains to be established through subsequent scholarly output and citation development.

References

  1. Bakhtiari, E. (2026). A Hybrid AI-Assisted Framework for Anxiety Support: System Description and Exploratory Findings Among University Students. Behavioral Sciences, 16(10), 1781.
    https://doi.org/10.3390/bs16101781
  2. Elsevier. (n.d.). Scopus author details: Elaheh Bakhtiari, Author ID 60866885400. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=60866885400
  3. MDPI. (2026). Behavioral Sciences, Volume 16, Issue 10, Article 1781.
  4. ORCID. (n.d.). Elaheh Bakhtiari, ORCID record.
    https://orcid.org/0009-0009-1571-355X
  5. Global Innovation Technologist Awards. (n.d.). Official award website.
    innovationtechnologist.com

Ibéria Medeiros | Computer Science | Best Researcher Award

Published on by Innovation Technologist

Best Researcher Award

Ibéria Medeiros
Faculty of Sciences of the University of Lisbon, Portugal

Ibéria Medeiros
Affiliation Faculty of Sciences of the University of Lisbon
Country Portugal
Scopus ID 55949734600
Documents 59
Citations 735
h-index 14
Subject Area Computer Science
Event Global Innovation Technologist Awards
ORCID 0000-0003-4478-8680

Ibéria Medeiros is a computer science researcher affiliated with the Faculty of Sciences of the University of Lisbon. The available bibliometric profile records 59 documents, 735 citations, and an h-index of 14. Her listed research output includes work addressing software security, vulnerability detection, binary analysis, privacy-preserving code analysis, honeypots, and cloud-based security information and event management. These areas form a coherent research profile within dependable and secure computing.

Abstract

This academic recognition profile summarizes the research record of Ibéria Medeiros in computer science, with emphasis on cybersecurity and dependable software systems. The documented portfolio combines scholarly productivity with research addressing practical security problems, including buffer overflow mitigation, encrypted-code vulnerability detection, high-interaction honeypots, and cloud-based SIEM correlation. Bibliometric indicators and identified publications provide the basis for evaluating research visibility and award suitability.

Keywords

Computer Science; Cybersecurity; Software Security; Binary Analysis; Vulnerability Detection; Privacy-Preserving Analysis; Honeypots; eBPF; SIEM; Dependable Computing.

Introduction

Cybersecurity research increasingly requires methods capable of identifying software weaknesses while preserving operational reliability and data confidentiality. Medeiros’s documented publications address several of these challenges across binary analysis, encrypted software, intrusion deception, and cloud security. The research therefore sits at the intersection of software engineering, systems security, and dependable computing.

Research Profile

The recorded Scopus profile reports 59 documents, 735 citations, and an h-index of 14. These indicators provide quantitative evidence of an established scholarly publication record and citation presence within the research literature. The profile is complemented by ORCID identification, supporting persistent attribution of scholarly work. [1] [2]

Research Contributions

  • Binary analysis and stack-integrity approaches for mitigating buffer overflow vulnerabilities.
  • Privacy-conscious vulnerability detection in encrypted software code.
  • Evaluation of eBPF for high-interaction honeypot implementation.
  • Cloud-based SIEM correlation using serverless functions.

Publications

BASICS: Binary Analysis and Stack Integrity Checker System for Buffer Overflow Mitigation, Computers & Security, January 2027. [3]

Detecting Vulnerabilities in Encrypted Software Code While Ensuring Code Privacy, IEEE Transactions on Dependable and Secure Computing, July 2026. [4]

Evaluating eBPF as an Alternative to Virtual Machine Introspection for High-Interaction Honeypot Implementation, book chapter, 2026. [5]

CCE: A Cloud-Based SIEM Correlation Engine Built on Serverless Functions, International Symposium on Reliable Distributed Systems (SRDS), October 2025. [6]

Research Impact

The combination of 735 recorded citations and an h-index of 14 indicates measurable scholarly visibility. The publication portfolio also demonstrates continuity across multiple security problems rather than concentration on a single application. Research addressing secure software analysis, privacy, deception technologies, and cloud security reflects the practical scope of contemporary cybersecurity research.

Award Suitability

Based on the supplied bibliometric indicators, institutional affiliation, and documented research outputs, the profile demonstrates characteristics relevant to consideration for a Best Researcher Award. The assessment is grounded in observable publication and citation information and should be interpreted alongside the complete nomination and verification process.

Conclusion

Ibéria Medeiros’s research profile presents an established contribution to computer science, particularly cybersecurity and dependable software systems. The documented indicators and recent publications provide a substantive basis for academic recognition within the Global Innovation Technologist Awards framework.

References

  1. Elsevier. (n.d.). Scopus author details: Ibéria Medeiros, Author ID 55949734600. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=55949734600
  2. ORCID. (n.d.). Ibéria Medeiros, ORCID 0000-0003-4478-8680.
    https://orcid.org/0000-0003-4478-8680
  3. Elsevier. (2026). BASICS: Binary Analysis and Stack Integrity Checker System for Buffer Overflow Mitigation. Computers & Security.
    https://doi.org/10.1016/j.cose.2026.105165
  4. IEEE. (2026). Detecting Vulnerabilities in Encrypted Software Code While Ensuring Code Privacy. IEEE Transactions on Dependable and Secure Computing.
    https://doi.org/10.1109/TDSC.2026.3688318
  5. Springer. (2026). Evaluating eBPF as an Alternative to Virtual Machine Introspection for High-Interaction Honeypot Implementation.
    https://doi.org/10.1007/978-3-032-11539-3_14
  6. IEEE. (2025). CCE: A Cloud-Based SIEM Correlation Engine Built on Serverless Functions. International Symposium on Reliable Distributed Systems (SRDS).
    https://doi.org/10.1109/SRDS69199.2025.00022