Team

Dr. Shruti Rajendra Kshirsagar

Assistant Professor, School of Computing

Dr. Shruti Rajendra Kshirsagar is an Assistant Professor and graduate coordinator for the MS in data science program at the School of Computing at Wichita State University. She specializes in Data Science, Deep Learning, Machine Learning, and Speech Signal Processing. Dr. Kshirsagar's research interests extend to Affective Computing, Healthcare and AI, Medical Image Processing, Assistive Technology, human-machine interface, Artificial Intelligence, and Sound Recognition. She earned her PhD in Telecommunications from Institut National de la recherche scientifique (INRS) in Montreal, Canada, where she specialized in Speech & Deep Learning, and data science. She holds a Master's and Bachelor's degree in Electronics & Telecommunication Engineering from the University of Mumbai, with a focus on Communication, statistics, and Signal Processing. At Wichita State University, Dr. Kshirsagar is responsible for teaching and mentoring graduate students, developing and implementing advanced curricula in Deep Learning and Machine Learning. She has significant industry experience, having worked as an Audio R&D Scientist at EERS Global Technologies Inc. in Montreal and as a Machine Learning for Audio Analytics Intern at Robert Bosch Inc. in Mississauga, Canada. Dr. Kshirsagar's exemplary contributions to research have been recognized with several prestigious awards, including the Best Doctoral Thesis Award from INRS. She has also been awarded multiple research grants. Her professional memberships include IEEE Signal Processing Society, IEEE Young Professionals, IEEE Women in Engineering, and the International Speech Communication Association (ISCA), among others. Dr. Kshirsagar's work is widely published in renowned journals and conferences, reflecting her commitment to advancing the fields of Affective computing, deep learning, and signal processing.

Faculty Profile  

Elmira Salari

PhD Student

Elmira is a PhD student in Computer Science at Wichita State University, working under the supervision of Dr. Kshirsagar. She develops AI systems based on Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) for healthcare applications, integrating external knowledge to improve reliability, reasoning, and domain adaptation in medical contexts, including sleep-stage classification, ECG classification, and other clinical tasks.

She has also collaborated with linguistics researchers to develop RAG systems that incorporate discourse and linguistic information to improve the quality and trustworthiness of AI-generated responses in healthcare.

Elmira holds a master's degree in IT Management from the University of Tehran and a bachelor's degree in IT Engineering from Azad University of Mashhad. Before starting her PhD, she worked as an SEO Specialist for seven years, bringing industry experience that complements her academic research.

Aishwarya Fursule

PhD Student

Aishwarya is a PhD researcher working on audio deepfake detection and trustworthy AI. Her research focuses on studying fairness and gender bias in detection models using different audio features and deep learning approaches. She also investigates how different speech synthesizers affect detection across genders and their fairness. In addition, she works on phoneme-level analysis for audio deepfake detection, including creating phoneme-based datasets to study how manipulations affect speech patterns. Her broader interests include deepfake localization, multilingual datasets, and multimodal deepfake detection. 

Vamshi Nallaguntla

PhD Student

Vamshi Nallaguntla is a PhD student in Electrical Engineering and Computer Science at Wichita State University and a member of the Soundmind Neurovision Innovation Lab. His research focuses on audio deepfake detection, speech processing, and the naturalness analysis of synthetic speech. He is particularly interested in phoneme-level analysis to better understand the differences between real and synthetic speech. His work also involves creating synthetic audio datasets to study the behavior of generative speech models and to develop deepfake detection systems that are robust and generalize across different synthesis technologies. Outside of research, Vamshi enjoys exploring emerging AI technologies, watching science fiction movies, and thinking about ambitious engineering ideas related to space technology and aviation.

Gurinder Kaur Sandhu

PhD Student

Gurinder is a Ph.D. student in Computer Science and a Graduate Research Assistant at Wichita State University, working under the supervision of Dr. Shruti Kshirsagar. Her research focuses on applying artificial intelligence and deep learning techniques to sleep analysis using physiological signals from polysomnography (PSG), with the goal of improving automated sleep stage classification and developing explainable AI approaches for physiological signal analysis. During her PhD, she also completed a summer internship focused on healthcare data analytics and business intelligence, where she worked on developing automated dashboards and data workflows for sleep-related clinical data. Her work integrates machine learning, signal processing, and healthcare analytics to support data-driven insights in sleep research.

Unaza Tallal

PhD Student

Unaza Tallal is a PhD student in Computer Science at Wichita State University and a Graduate Research Assistant. Her research focuses on computational modeling, biomedical signal analysis, and intelligent healthcare systems, with the aim of extracting clinically meaningful insights from complex physiological data. She is highly motivated and passionate about research, particularly in developing data-driven solutions for healthcare applications.

She holds a Master’s degree in Computer Science from Bahria University, Lahore, Pakistan. With several years of academic experience as a university lecturer and researcher, she brings a strong foundation of teaching, research, and practical application to her work in machine learning and intelligent healthcare systems.

Her current research focuses on sleep analysis using deep learning techniques. She is exploring methods to improve sleep data analysis across heterogeneous datasets and investigating wearable-device–based sleep monitoring using physiological signals.

Parisa Rostami

PhD Student

Parisa Rostami is a direct Ph.D. student in the School of Computing at Wichita State University, advised by Dr. Shruti Kshirsagar. Her research interests lie at the intersection of machine learning, natural language processing, large language models, and healthcare AI. She is currently working on projects involving tumor segmentation and interpretable AI. Her broader goal is to develop AI systems that are both explainable and socially impactful, particularly for healthcare applications.

Asmae Mouradi

PhD Student

My name is Asmae Mouradi, I am a Graduate Research Assistant conducting research on deep learning for damage assessment using satellite imagery. My work centers on designing supervised and unsupervised domain adaptation approaches, alongside augmentation techniques, to improve generalization across different locations, sensors, and imaging conditions. I have developed supervised domain adaptation methods to detect damage from satellite images and classify damage severity levels. At present, I am investigating unsupervised domain adaptation methods and augmentation strategies to enhance reliable damage-level classification with limited or no labeled target-domain data.

 S M Asif Hossain

PhD Student

Asif is a Ph.D. student in Computer Science at Wichita State University (WSU). His research focuses on the intersection of Natural Language Processing (NLP) and Computer Vision (CV), specifically applying these combined techniques to solve critical, real-world problems, particularly within the Healthcare sector. A primary goal of his work is to develop trustworthy and explainable AI solutions that maintain effectiveness using fewer parameters, making them viable for resource-constrained environments. Under the supervision of Dr. Kshirsagar, Asif is currently developing state-of-the-art deep learning models for diverse applications, including structural damage detection and the challenging task of converting brain signals into accessible text or voice outputs. Prior to his Ph.D. studies, Asif earned his Bachelor of Science in Computer Science and Engineering from American International University-Bangladesh. He also brings valuable industry experience, having previously served as a Software Engineer at Samsung and a Team Lead at Endure Robotics.

Ruksat Khan Shayoni

PhD Student

Ruksat Khan Shayoni is a Ph.D. student in Computer Science at Wichita State University. Her research focuses on machine learning, computer vision, and natural language processing, with an interest in analyzing complex real-world data. She is currently working on a systematic literature review on deepfake detection and exploring research directions in tornado detection using visual data. Her broader research vision focuses on developing AI-driven methods that support decision-making in domains such as healthcare, environmental monitoring, and security, with an emphasis on trustworthy and privacy-preserving machine learning systems.

Fatemeh Karji

Master's Student

Fatemeh (Sara) Karji is a master's student in Computer Science at Wichita State University, currently working on her thesis under the guidance of Dr. Shruti Kshirsagar. Her research focuses on brain tumor segmentation, utilizing advanced Deep learning and machine learning techniques to improve diagnostic accuracy.

Parupati Bharath Chandra Reddy

Master's Student

Bharath Chandra Reddy is a computer science master's thesis student at WSU. He graduated with a bachelor's degree in electronic and communication engineering from Jawaharlal Nehru Technological University (JNTU), Hyderabad. He is currently employed by DRAC as a graduate research assistant on a project involving disaster damage assessment. Creating computer vision and deep learning systems for audio event identification is one of his research interests.