معرفی
Jorjeta Jetcheva is an Assistant Professor in the Computer Engineering Department at San José State University, part of the Charles W. Davidson College of Engineering. She brings extensive industry experience from leadership roles at Accenture, Fujitsu Laboratories of America, Itron, and Firetide, where she led innovations in AI, smart grids, and wireless networking.
Her research focuses on Artificial Intelligence-based Personal Assistants, Natural Language Processing, and Knowledge Management. Her work bridges human-centered AI and enterprise applications, with emphasis on intelligent agents, knowledge platforms, and ethical AI systems. She explores how AI can enhance user productivity, decision-making, and system security across domains such as healthcare, energy, and customer service.
The recent publications highlight a strong trend in Natural Language Processing applied to real-world problems like fake health news detection, agent assist systems, and knowledge graph integration. Her research also spans Smart Grid analytics, cybersecurity, and AI ethics, reflecting a multidisciplinary approach grounded in both theoretical rigor and practical deployment.
Scientific Awards:
- Best Application Paper Award at IEEE Big Data Service 2022
- Best Paper Award at SmartGridComm 2014
- Top 10 Finalist, Fujitsu Next Generation Product Idea Contest 2016 ('Robo Butler')
- CSU STEM-NET Faculty Fellow (2023)
Advising and Grants: Professor Jetcheva is the Principal Investigator of a $2.5 million NSF S-STEM grant titled 'Empowering Students to Succeed in Engineering and Computer Science'. She actively mentors graduate students, including Master’s student Garima Chaphekar, with whom she co-authored an award-winning paper on fake health news detection. She serves on the SJSU AI Advisory Committee and leads the AI Research Cluster, fostering interdisciplinary collaboration and student success.
Labs and Teams: She leads the AI Research Cluster at SJSU, promoting innovation in artificial intelligence across departments. Her work involves close collaboration with students, industry partners, and interdisciplinary teams focused on deploying scalable, ethical AI solutions.
