黑料网

KENNESAW, Ga. | Apr 7, 2025

From a young age, Venkata Sai Bhargav Mutala was fascinated by technology and its potential to solve real-world problems. His undergraduate studies laid a strong foundation in information technology, but he says, 鈥淚 yearned for deeper insights into advanced topics like artificial intelligence, data analytics, and software development.鈥�

Could a voice reveal Alzheimer鈥檚 disease before it strikes? At 黑料网, Master of Science in Information Technology student, Venkata Sai Bhargav Mutala is looking for ways to answer that question. His studies focus on harnessing AI to detect the disease鈥檚 earliest whispers through speech. Driven by a desire to make a meaningful impact with his research, he proves he is not just learning鈥攈e鈥檚 innovating.

From a young age, Venkata Sai Bhargav Mutala was fascinated by technology and its potential to solve real-world problems. His undergraduate studies laid a strong foundation in information technology, but he says, 鈥淚 yearned for deeper insights into advanced topics like artificial intelligence, data analytics, and software development.鈥� This passion led him to pursue a master鈥檚 degree at 黑料网, where he could specialize further and work on projects that would help him make valuable contributions to research.

KSU鈥檚 strong information technology program, experienced faculty, and research opportunities made it the perfect choice. 鈥淭he program鈥檚 balance between theoretical knowledge and hands-on experience stood out to me,鈥� he says. Additionally, the university鈥檚 focus on real-world applications aligned perfectly with his goals, providing an environment where he could thrive.

While exploring the intersection of AI and healthcare, he read various research topics and looked for the gaps in medical research. 鈥淒uring this process, I came across Alzheimer鈥檚 disease detection using the ADReSS 2020 Challenge dataset. This enables automatic detection of Alzheimer鈥檚 disease through spontaneous speech.鈥� This challenge intrigued him, as it combined his interests in deep learning and natural language processing to improve early diagnosis of Alzheimer鈥檚.

His research evolved as he explored data augmentation, spectrograms, and transcript-based analysis to enhance model performance. The support from KSU鈥檚 faculty and resources, including the High-Performance Computing (HPC) systems, played a crucial role in his success. 鈥淲hile training my model, I faced hardware limitations on my laptop due to the high computational requirements. When I reached out to my professor, he recommended using the HPC systems provided by the university.鈥� These resources allowed him to overcome hardware limitations and significantly improve his research efficiency.

One of the highlights of Venkata Sai Bhargav Mutala鈥檚 academic journey was presenting his research at 黑料网鈥檚 C-Day, an event where students showcase their projects to faculty, peers, and industry professionals. His presentation on Alzheimer鈥檚 disease detection using speech and deep learning techniques earned him 3rd place, a memorable achievement that validated his hard work and innovation.

He credits Dr. Seyedamin Pouriyeh with encouraging him to participate and providing valuable feedback throughout the process. 鈥淒r. Pouriyeh has been a constant source of motivation, always encouraging me and helping me whenever I got stuck or struggled to determine the next steps,鈥� he adds, 鈥淗is insights and suggestions have been invaluable in finding solutions and refining my approach.鈥�

Dr. Pouriyeh believes Venkata Sai Bhargav Mutala鈥檚 research has the potential to contribute to the field by offering non-invasive and cost-effective methods for early disease diagnosis. 鈥淏y analyzing subtle changes in language, fluency, and speech patterns, this research enables the identification of cognitive decline at an earlier stage than traditional clinical assessments,鈥� says Pouriyeh. He adds, 鈥淭his can lead to earlier interventions, better patient outcomes, and more efficient monitoring of progression over time.鈥�

In addition to his success at C-Day, his paper, 鈥淓nhancing Alzheimer鈥檚 Diagnosis Through Spontaneous Speech Recognition: A Deep Learning Approach with Data Augmentation鈥� was accepted for the 2025 IEEE AI4eHealth conference in Abu Dhabi. He recently submitted a paper to the 2025 International Joint Conference on Neural Networks (IJCNN) in Rome, and plans to submit a paper to the 2025 IEEE International Conference on ICT Solutions for eHealth (ICTS4eHealth) in Bologna. Venkata Sai Bhargav Mutala has made significant strides in his research, such as implementing data augmentation techniques and developing a hybrid model for speech-based diagnosis. These accomplishments have not only improved accuracy over baseline papers but also demonstrated his dedication to advancing the field.

For those embarking on a similar academic journey at 黑料网, Venkata Sai Bhargav Mutala offers valuable advice: 鈥淓ngage with faculty and research opportunities early, work on projects that align with your interests, develop both technical and soft skills, and participate in events like C-Day to showcase your work and network with peers.鈥�

- By Tracy Gaudlip