People

Biography: Ahmed Imteaj is an Assistant Professor in the School of Computing at Southern Illinois University, Carbondale. He received his Ph.D. in Computer Science from Florida International University in 2022, where he received his M.Sc. degree with recognition of the Outstanding Master’s Degree Graduate Award. His research interests span distributed machine learning, Internet of Things (IoT), cybersecurity, and blockchain. 

Ahmed significantly contributed to the area of privacy-preserving distributed machine learning and internet-of-things and published his research in top-tier conferences and peer-reviewed journals. Ahmed's research has been recognized several times. Ahmed was recognized with the 2022 FIU Real Triumph Graduate Award at FIU Summer-2022 Commencement Ceremony for his outstanding academic, professional and personal achievements. Ahmed is also the recipient of the “2022 Outstanding Student Life Award: the Graduate Scholar of the Year Award" from the Division of Academic and Student Affairs at FIU, “2021 Best Graduate Student in Research Award” from the KFSCIS at FIU, Best Paper Award from the 2019 IEEE CSCI’19 conference, recipient of 4 travel scholarships, and also one of the two winners at 2021 FlU GSAW Scholarly Forum. Ahmed is also the lead author of the book, “Foundations of Blockchain: Theory and Applications” and published more than 45 peer-reviewed journals and conference papers.

Contact: imteaj[at]cs[dot]siu[dot]edu

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Biography: MD. Zarif Hossain is currently a Ph.D. student and Graduate Research Assistant of SPEED Lab at the School of Computing at Southern Illinois University. He is doing his PhD under the supervision of  Dr. Ahmed Imteaj. Prior to that, Zarif worked as a Lecturer at the Department of CSE & CSIT of Shanto-Mariam University of Creative Technology, and conducted various courses, i.e., Object Oriented Programming, Web Programming, Cloud Computing and conducted labs of these courses. Prior to that job, he was a Software Engineering intern at Brainstation23, a renowned software company in Bangladesh. As a Software Engineering Intern, he worked on both frontend and backend. His fascination and curiosity towards AI and machine learning ignited a spark inside him to explore more beyond the horizon. His research explores the interplay between Federated Learning, Computer Vision, and Cyber Security. He is proficient in Python, C++, Java, SQL, NoSQL Frameworks like Pytorch, Tensorflow & React.

Biography: Wasimuddin Salar Fathimullah is currently a MS student at the School of Computing at Southern Illinois University and a research member of SPEED Lab. His academic pursuits are focused on cutting-edge research in the domain of Machine Learning, AI, and and Cybersecurity. Before embarking on his academic journey, Wasimuddin gained valuable industry experience working at TCS for a year. During his tenure there, he honed his skills in ServiceNow, application development using PEGA, problem-solving, and project management. He worked on a range of projects and developed an understanding of how technology can be leveraged to solve real-world problems. Currently, Wasimuddin is working on his MS thesis under the guidance of Dr. Ahmed Imteaj. His research focuses on Federated Learning and Cybersecurity, exploring the potential of federated learning techniques to improve the security of machine learning models in distributed systems. Wasimuddin believes that his research will contribute to advancing the state of the art in this field and pave the way for new applications and technologies.

Biography: Saika Zaman is an enthusiastic MS student currently pursuing her degree at the School of Computing in Southern Illinois University. She is a highly motivated individual and a member of SPEED Lab. Saika's educational background includes a Bachelor's degree in Computer Science and Engineering from Chittagong University Engineering and Technology. Saika has worked on several machine learning and data science projects and has developed a keen interest in working with data. Her research interests are centered around Machine Learning, Data Science, Federated Learning, and Cybersecurity. She has a strong desire to contribute to the field and is committed to advancing the state of the art in this area. Saika has published four research papers and is currently working on several research projects. She believes that her research will have a significant impact on the field of Machine Learning and Data Science, paving the way for new applications and technologies. Overall, Saika is a highly motivated and dedicated team player with a passion for data science and machine learning. 

Biography: Dasika Madhu Nimeshika is a graduate student at Southern Illinois University. She works as a Graduate Assistant (Network Engineer) in the Office of Information Technology and is a research member of SPEED Lab. As part of her internship at Deloitte Touche Tohmatsu as a Business Analyst, she worked on Robotic Process Automation (BluePrism and UIPath). Post undergrad from Swami Vivekananda Institute of Technology, she worked as an Engineer at Virtusa Pvt Ltd. for three years. While working full-time, Madhu gained project experience in Core Java, Advanced Java, Java Frameworks (Spring MVC, Hibernate, and Maven), Databases (MySQL, Oracle), and SharePoint Online. She holds five Amazon Web Services certifications - Solutions Architect (Associate, Professional), System Administrator (Associate), DevOps Engineer (Professional), Machine Learning (Specialty), and 1Z0-808 Oracle Java certification. She works on proofs-of-concept projects and has written articles on cloud-based application development. Her research areas of interest comprise application development, load balancing, scalability, and performance in Cloud Computing, Machine Learning, Federated Learning, firewall and centralized, secure data storage in Cybersecurity, and Network Engineering.

Biography: Gireesh Nadh Mekala is currently a MS student at the School of Computing at Southern Illinois University and a research member of SPEED Lab. Prior to commencing his academic pursuit, Gireesh acquired significant industry experience by working at Accenture as a Data Engineer. With a background as a Data Engineer, Gireesh has hands-on experience in designing efficient ETL pipelines for data ingestion from diverse sources using Python, PySpark, and SQL. Additionally, Gireesh is well-versed in working with cloud platforms, further enhancing his expertise in modern data engineering practices. Currently his research focuses are Machine Learning and MLOPS. With a passion for using machine learning to solve real-world problems, He is committed to advancing the field of machine learning and contributing to the development of privacy-preserving technologies.

Biography: Oleksandr Jockusch, a Computer Science senior at SIUC, holds a keen interest in machine learning and AI, particularly in the domains of computer audition and computer vision. He is also enthusiastic about creating applications for both Android and iOS platforms. He joined SPEED lab in Summer'23.

Biography: Thomas Boyd is a Senior Computer Science Student at SIUC, and currently, working as an undergrad researcher at SPEED Lab under the supervision of Dr. Ahmed Imteaj. Thomas is from North Chicago, Illinois. He is also the Program Chair of National Society of Black Engineers and the President of Omega Delta Phi Fraternity Beta Upsilon Inc. His research focuses are Machine Learning, Artificial Intelligence and Software Engineering. He is currently working on a project focusing on optimizing the performance of Federated Learning algorithms in an unreliable environment. He plans to use his knowledge and skillsets to dive into the health care field. 

Biography: Thomas Zemen is a Senior Computer Science Student at SIUC, and currently, working as an undergrad researcher at SPEED Lab under the supervision of Dr. Ahmed Imteaj. Thomas is from Chicago, Illinois, and he has Software Engineering Internship experience at BP. He is an incoming Software Engineer at Mastercard. He is currently working on a project focusing on optimizing the performance of Federated Learning algorithms in an aim to prevent adversarial attacks. He plans to use his knowledge and experience to improve upon existing fraud detection systems.