Bahareh Arghavani Nobar
Ms. in Data science , University of New Haven
Department of Electrical and Computer Engineering and Computer Science
Tagliatela College of Engineering
University of New Haven
👩💻 Biography: I am Bahareh Arghavani Nobar, a dynamic computer scientist and machine learning engineer, currently serving as a Graduate Research Assistant at the University of New Haven’s SAIL Lab. My professional journey has been a fusion of academic excellence, impactful research, and a commitment to making technology more inclusive.
💡 Research Focus: In the realm of intelligent-machine research, my focus lies in creating inclusive Text-to-Speech (TTS) solutions for under-represented languages using advanced Transformer models. My expertise extends to anomaly detection for medical devices, where I’ve demonstrated proficiency in time series analysis and various deep learning models.
🚀 Professional Journey:
In collaboration with Dr. Binesh Kumar, where he served as the first author and I as the co-author, we jointly authored a research paper titled “Comparative Study of Generative Models for Early Detection of Failures in Medical Devices.” This research delves into fault detection methodologies, providing valuable insights at the intersection of technology and healthcare. Our work applied generative models like HMM, VAE, and GAN, showcasing a commitment to advancing intelligent-machine research with a particular focus on the reliability and safety of medical devices.
In addition to our collaborative research efforts, my role as a Graduate Research Assistant at the SAIL Lab involves a multifaceted approach to technology. From fine-tuning advanced Text-To-Speech models to capturing diverse Persian accents with multi-speaker TTS models, my work reflects dedication to linguistic diversity and inclusive technology. This combined experience not only expands the boundaries of technology but also ensures its applicability in real-world scenarios, emphasizing the lab’s commitment to innovation and societal impact.
🎓 Academic Pursuits: Currently pursuing a Master of Data Science at the University of New Haven, my academic journey is complemented by real-world applications. I’ve been honored with the 2023-2024 TCoE Endowed Graduate Fellowship, underscoring my commitment to excellence in data science.