Tashfeen is a tinkering computer scientist with a fair bit of intrigue for mathematics. He enjoys teaching, running, drinking coffee, and learning new words in different languages. His PhD advisor is Dr. Qi Cheng and his current research interests include computational learning theory, genetic algorithms, and lattice cryptography. He has recently been dabbling in 3D printing, botany and... et français mais il en sait très peu sur ceux-ci. Albeit not an angel, when he stands next to a window in the dusk's crepuscular light, you can almost see his halo.
Learn more about Tashfeen's work at tashfeen.org
SJ is a PhD candidate and Graduate Teaching Assistant under the supervision of Dr. Anindya Maiti. His research area focuses on revitalizing endangered languages through the innovative use and integration of natural language processing (NLP) and text prediction. By leveraging NLP algorithms, he aims to develop tools that facilitate the restoration and preservation of endangered languages. This would automate translation and predict contextually relevant phrases. This work bridges the gap between traditional linguistic preservation methods and modern technology, fostering a sustainable approach to language revitalization. Thereby, empowering language learners by contributing to the preservation and revival of endangered linguistic and cultural heritage.
Pantia-Marina Alchirch is a Ph.D. Candidate and Graduate Research Assistant under the supervision of Dr. Dimitrios Diochnos at the University of Oklahoma (OU). She holds both a Bachelor's and a Master's degree in Computer Science from the Athens University of Economics and Business (AUEB). Her research focuses on Online Machine Learning, particularly learning from data streams using tree-based models, with a strong emphasis on handling imbalanced datasets in streaming environments. Her broader interests include Explainable AI (XAI), Probably Approximately Correct (PAC) Learning, and Federated Learning.
Learn more about Marina's work on her Website.
Amirhossein Arezoumand is a Ph.D. student in Computer Science at the University of Oklahoma (OU), working under the supervision of Dr. Sina Khanmohammadi in collaboration with the OU Health Sciences Center and the Data Institute for Societal Challenges (DISC). His research focuses on developing machine learning models for the early detection of cardiovascular conditions using ECG signals and the prediction of functional outcomes in ischemic stroke using MRI/CT imaging.
He is especially interested in integrating deep learning, signal processing, and medical imaging to build interpretable and clinically relevant diagnostic tools. His broader interests include biomedical AI, time-series analysis, and model generalizability in healthcare applications.
Aseel Basheer is a Ph.D. Candidate in Computer Science and working as a Graduate Research Assistant at the Data Institute for Societal Challenges (DISC) at the University of Oklahoma. She earned her master's degree in computer science from Oklahoma City University. Advised by Dr. David Ebert, she is researching in visual analytics for One Health data. Her research interests: Visualization, Visual Analytics, and Digital Humanities.
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I’m Averi Bates, a first-year PhD student in the School of Computer Science focusing on machine learning. My work focuses on machine learning applications across diverse areas, including bioinformatics and applied problem-solving. For example, I worked on a project analyzing chest X-ray data using cross-validation techniques to improve diagnostic accuracy. I’m passionate about leveraging machine learning to tackle real-world challenges and enjoy collaborating on projects that drive impactful, data-driven solutions.
Divya Bhatt is a part-time doctoral candidate in the School of Computer Science, working under the advisement of Dr. Le Gruenwald. Divya’s research interests are data mining, data security, machine and federated learning. She works full-time as a lead Electronics Engineer in the Presidential and Executive Aircraft Division at Tinker AFB and holds an M.S. degree in Electrical and Computer Engineering from the University of Missouri. While not working, Divya enjoys travelling, hiking, reading and music.
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Ph.D. student in Computer Science at the University of Oklahoma, working under the supervision of Dr. Dean Hougen. My research focuses on machine learning, deep learning, and reinforcement learning. I bring prior experience as a Machine Learning Engineer at Cowlar Inc (YC’17), where I built scalable AI systems and action recognition models.
Learn more about Ahsan's work on Github and connect on LinkedIn
Sam Bird is a PhD student in Computer Science, researching database management systems. He earned his bachelor's and master's degrees in Computer Science at the University of Oklahoma. Advised by Dr. Le Gruenwald, he is researching quantum data management using machine learning on quantum computers for large-scale database applications. His academic interests include databases, machine learning, and quantum computing.
Learn more about Sam's work at https://sambird.org/
First-year Ph.D student in Computer Science. His dissertation focus will be in the field of pattern of behavior. He graduated with an A.A.S. In intelligence studies in 2018 from the Community College of the Air Force, with a B.S. in Computer Science in 2020 from the University of Central Oklahoma, and with a M.S. in Computer Science with an emphasis in A.I. in 2023 from Oklahoma Christian University. He works for the 76 Software Engineering Group at Tinker AFB. He has done research in RNA sequencing using machine learning and neural networks, investigating the applicability of model fusion in this area. His hobbies include playing the accordion, organ, and violin, spending time with his family and church.
Shane Elliott is a Computer Scientist at 76th Software Engineering Group/Tinker AFB with 10 years of software development experience. He was awarded an APP scholarship in 2023 to fund his PhD pursuit at OU. His research area has a focus of advancing deepfake detection and interpretability techniques.
Ashesh Gaur is a doctoral student in Computer Science at the University of Oklahoma, having joined the program in Spring 2021. He earned his undergraduate degree in Computer Science in 2009, followed by two years of industry experience as a software engineer specializing in Java development. He then pursued a Master’s degree in Information Technology with a specialization in Wireless Communication and Computation from IIIT Prayagraj, India.
Prior to starting his doctoral studies, Ashesh accumulated nine years of industry experience in data analytics and intellectual property analysis. His current research spans packet classification in data networks and the forecasting and optimization of processing loads in data centers. He applies a range of machine learning techniques alongside optimization frameworks such as Mixed-Integer Linear Programming (MILP), convex optimization, and genetic algorithms. His broader research interests lie in algorithm design and computational optimization.
Yonathan Hendrawan is a PhD student working in Visualization Information. Under the supervision of Dr. Chris Weaver, he is researching human movement data visualization using graphic novel structures. He earned his bachelor's degree in electrical engineering at Institut Teknologi Sepuluh Nopember (Indonesia) and master's degree in Information Technology at The University of New South Wales (Australia). His academic interests include Information Visualization, Video Gaming, and Computer Graphics.
Debra Hogue is a Computer Scientist at 76th Software Engineering Group/Tinker AFB with 10 years of experience as a software developer. She was awarded the SMART scholarship in 2021 to fully fund her PhD journey at OU. Her research area resides within computer vision with a focus of advancing camouflage object detection and segmentation techniques.
Connect with Debra on LinkedIn
Vishnu Kadiyala is a PhD Candidate in Computer Science, conducting research aimed at improving weather forecasting accuracy utilizing Deep Learning models. He holds a master’s degree in computer engineering from the University of Oklahoma. Advised by Dr. Andrew Fagg, his research interests include Deep Learning, Atmospheric Sciences, and a passion for solving complex problems.
Zak Kastl is a Computer Scientist with the 76th Software Engineering Group/Tinker AFB with 15 years of experience as a software engineer. He is a Ph.D. Candidate under the supervision of Dr. Dimitrios Diochnos at the University of Oklahoma (OU). He holds a bachelor’s degree in computer science from Oklahoma State, and a master’s degree in computer science from Oklahoma Christian University. His research focuses on tiny machine learning techniques applied to deep learning and model optimization.
William is a Norman native and 2nd year PhD student in Data Science & Analytics. He is advised by Dr. Dimitrios Diochnos and Dr. Sean Crowell and is interested in machine learning and uncertainty quantification applied to problems in Atmospheric and Environmental science. Currently, he works as a research assistant for the NASA GeoCarb mission and holds a research affiliation with the NASA Jet Propulsion Laboratory, bringing machine learning data quality products to operation for the Orbital Carbon Observatory.
Connect with William on LinkedIn
Shyam Sundar Murali Krishnan is a doctoral candidate in the School of Computer Science, where he also completed his Master’s degree. Under the guidance of Dr. Dean Hougen, his research focuses on developing interpretable machine learning techniques, particularly on tree-based ensemble methods such as random forests, to enhance model transparency and enable in-depth behavioral analysis. In addition to his research, Shyam has served as a Graduate Teaching Assistant for nearly five years, supporting a variety of undergraduate and graduate-level courses, including Algorithm Analysis, Machine Learning, Introduction to Robotics, and Discrete Structures.
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Maisha Maliha is a Ph.D. Candidate in Computer Science at the University of Oklahoma, working under the supervision of Dr. Dean Hougen. Her research focuses on explainable artificial intelligence (XAI), deep reinforcement learning, computer vision and multi-agent systems. She is passionate about building intelligent systems that are not only effective but also interpretable and trustworthy. Prior to her Ph.D., Maisha earned her M.Tech in Computer Science and Engineering from IIT Bombay. She is serving and has also served as a lab instructor and teaching assistant for courses in Python programming language and artifical intelligence, with a strong commitment to mentoring and empowering students in STEM.
Learn more about Maisha's work on Google Scholar and connect on LinkedIn
Haron Mungiria is a Ph.D. student and Graduate Teaching Assistant in the School of Computer Science, advised and supervised by Dr. Mansoor Abdulhak. He holds a Master of Science in Computer Science from the University of Central Oklahoma. His research interests lie in Software Engineering.
Braden Roper is a PhD student in Computer Science, specializing in Data Visualization and Analysis. He is interested in high dimensional data visualization and reduction techniques, data literacy and education, and data storytelling. He has worked with the K20 Center on the research campus developing educational games, applications, and resources that are used by teachers and students around the world.
Jay Rothenberger is a Graduate Research Assistant to Dr. Dimitrios Diochnos in the school of Computer Science here at OU. Jay's research is funded by the NSF AI Institute for Research on Trustworthy AI in Weather, Climate, and Coastal Oceanography. Jay's primary areas of interest include developing deep learning models that can be deployed with limited computational resources and developing models that are robust to adversarial conditions.
Learn more about Jay's work at jayrothenberger.com and connect on GitHub
Jalal Saidi is a Ph.D. candidate in Computer Science at the University of Oklahoma, working under the supervision of Dr. Dean Hougen. He holds a master's degree in Data Science and Analytics from the same university. His research focuses on the application and interpretability of deep learning models, particularly the Transformer architecture, in the fields of computer vision and natural language processing.
I have a strong background in bio-inspired optimization algorithms, with expertise in their application to feature engineering, dimensionality reduction, recommender systems, and complex machine learning tasks. With a bachelor's in Computer Engineering (Software) and a master's in Artificial Intelligence and Robotics, my research has explored multi-objective ant colony optimization for community detection and trust-based recommender systems. Currently, I focus on enhancing classification performance and robustness through advanced bio-inspired and randomized algorithms, driven by a passion for developing practical solutions to real-world data challenges.
Shejuti Silvia is a Sr. Data Science Manager at Baker Hughes with 19 years of experience in Artificial Intelligence, software engineering, digital product development and management. In her current role, she leads a cross functional team to research and develop new AI/ML solutions and products to drive automation and efficiency in oilfield services at Baker Hughes. She is a Ph.D. Candidate in Computer Science at the University of Oklahoma, under the supervision of Dr. Mohammed Atiquzzaman and Dr. Dean Hougen. Her research focuses on AI drive predictive maintenance and asset performance management in Oil & Gas. She holds a bachelor’s degree in computer science and a master’s degree in data science and analytics from the University of Oklahoma.
Dr. Omkar Chekuri is a computer scientist specializing in Information Visualization, with broader interests in human-computer interaction, visual analytics, and applied data science. He earned his Ph.D. in Computer Science from the University of Oklahoma under the supervision of Dr. Chris Weaver. His dissertation focused on augmenting hierarchical visualizations through topology-centric representations and interactions, advancing how complex data structures are explored and understood.
Dr. Chekuri also holds a Master’s degree in Data Science and Analytics from the University of Oklahoma. Before moving to the U.S., he worked in Doha, Qatar, as a CMMS Analyst, where he led data automation and analytics projects for large-scale engineering operations.
His academic and professional background spans interactive tool development, virtual reality environments, and full-stack web applications. He has presented his work at leading conferences such as IEEE VIS and IVAPP. In addition to research, he has taught Python programming, mentored graduate students, and contributed to projects in education, weather communication, and medical imaging.
Learn more about Dr. Chekuri’s work on Github and connect on LinkedIn
Dr. Keerti Banweer is a recent Ph.D. graduate from the School of Computer Science at the University of Oklahoma. Her research focuses on computer science education, with particular interest in code review, debugging, software engineering, and programming practices. Her dissertation work centers on the design, development, and evaluation of an in-class active learning framework aimed at improving learning outcomes in entry-level CS courses.
Keerti also holds a master’s degree in Data Science and Analytics from the University of Oklahoma. Since Fall 2018, she has served as an instructor of record, teaching courses such as Java for Programmers and Introduction to Programming. Over the past eight years, she has been recognized for her teaching excellence, having received the Provost’s Certificate of Distinction in Teaching twice, an award presented to outstanding graduate instructors based on student evaluations.
Her professional focus lies in enhancing essential programming skills, such as code review and debugging, through innovative, student-centered teaching practices. Keerti is committed to advancing pedagogical strategies that support learners at all levels of a CS program. Looking ahead, she aspires to continue her career in academia, where she can mentor students and contribute to impactful research in CS education.
Learn more about Dr. Banweer's work at keertibanweer.com
