Assistant Professor

Dr. Afanasyev is currently an Assistant Professor in the Knight Foundation School of Computing and Information Sciences at Florida International University. Prior joining FIU, he was an Adjunct Assistant Professor in the Computer Science Department at the University of California, Los Angeles (UCLA) and before that a postdoctoral scholar in UCLA. His main research focus is on the next generation Internet architecture as part of the Named Data Networking (NDN) project; and his research interests include a variety of topics that are vital for the success of NDN, including scalability of name-based routing, auto-configuration, distributed data synchronization, application and network security. Dr. Afanasyev’s postdoctoral achievements have been recognized by the UCLA Chancellor’s Award for Postdoctoral Research. He is also leading the development effort of the overall NDN codebase.

Dr. Afanasyev’s particular interest currently is application of Information-Centric Networking (ICN) to Internet-of-Things (IoT), specifically realizing the vision of IoT where applications securely communicate with and about “things” without being concerned about specific details of the devices/controllers that represent things.

Hadi Amini is an Assistant Professor at the Knight Foundation School of Computing and Information Sciences at Florida International University. He is the director of Sustainability, Optimization, and Learning for InterDependent networks laboratory (www.solidlab.network). He received his Ph.D. in Electrical and Computer Engineering from Carnegie Mellon University in 2019, where he received his M.Sc. degree in 2015. He also holds a doctoral degree in Computer Science and Technology. Prior to that, he received M.Sc. degree from Tarbiat Modares University in 2013, and the B.Sc. degree from Sharif University of Technology in 2011. His research interests include machine learning and optimization algorithms, distributed computing and intelligence, sensor networks, interdependent networks, and cyber-physical resilience. Application domains include robotics, smart cities, energy systems, intelligent transportation networks, and healthcare.

He is a life member of IEEE-Eta Kappa Nu (IEEE-HKN), the honor society of IEEE. He served as President of Carnegie Mellon University Energy Science and Innovation Club; as technical program committee of several IEEE and ACM conferences; and as the lead editor for a book series on ‘‘Sustainable Interdependent Networks’’ since 2017. He also serves as Associate Editor of SN Operations Research Forum and International Transactions on Electrical Energy Systems. He has published more than 90 refereed journal and conference papers, and book chapters. He edited/authored six books. He is the recipient of the best paper award from “2019 IEEE Conference on Computational Science & Computational Intelligence”, best reviewer award from four IEEE Transactions, the best journal paper award in “Journal of Modern Power Systems and Clean Energy”, and the dean’s honorary award from the President of Sharif University of Technology. (Homepage: www.hadiamini.com)

Janki Bhimani’s primary research focus revolves around Flash-Based Storage Systems, Big Data Processing, Cloud Computing, High-Performance Computing, and Parallel and Distributed Computing. Her research interest also includes Performance Modeling, Resource Management, and Capacity Planning for various emerging inter-disciplinary research domains. With her extraordinary expertise and extensive experience in the field of new emerging flash-based storage systems and devices, she has made significant contributions to the data storage management community. She is the recipient of the Outstanding Graduate Research Award of 2019 from Northeastern University. She also received Best Paper Awards from flagship conferences. Her work is published in highly selective conferences and journals. She is also the main inventor of top graded patents. Hand-in-hand with her research, she is very passionate about teaching and mentoring. Prior to joining at Florida International University, she previously served Northeastern University as an instructor. She also closely worked with research scientists at Samsung Semiconductor Research Labs towards evolving flash-based SSDs. In her free time, Janki is a creative visual artist. Far from home, amidst nature, she finds her inspiration to paint. She enjoys understanding the impact of art on human psychology, and she can painterly bring motivation, healing, and encouragement through the canvas.

Wenqian Dong is an assistant professor of KFSICS department of Florida International University. She studied her Ph.D. in Computer Science and Engineering at the University of California, Merced. Her research focuses on high performance computing system (HPC). She is particularly interested in using machine learning techniques to improve performance of scientific applications. During her Ph.D., she has published a set of papers in various top HPC conferences, including two published in the prestigious Supercomputing Conference (SC), the flagship conference in the HPC field. She also received the UCM Bobcat Fellowship in 2018 and 2020. Wenqian was a research intern in the HP labs and is a research intern in the Pacific Northwest National Lab. Her work on power grid simulation was highlighted at the DOE science news and PNNL media.

Dr. Amin Kharraz research focuses on building systems to facilitate a data-driven approach to security. The primary goal of Dr. Amin is to apply this methodology to rigorously analyze the behavior of online attacks and facilitate developing platforms to discover and mitigate these attacks in a scalable and reliable manner. The problems that Dr. Amin tackles often involve the intersection of society, technology, and security.

Dr. Dongsheng Luo is currently an Assistant Professor in the Knight Foundation School of Computing and Information Sciences at Florida International University. He obtained his doctoral degree from the College of Information Science and Technology, Pennsylvania State University in 2022. Before that, he received B.Eng. degree from Beihang University in 2017. His research focuses on data mining, deep learning, and natural language processing. He is particularly interested in developing robust, integrative, and explainable tools that extract clean and human-understandable knowledge from noisy and heterogeneous network data, with applications in neuroscience, system management, and biomedicine.

Dr. Ananda Mohan Mondal is currently an Assistant Professor in the Knight Foundation School of Computing and Information Sciences at Florida International University (FIU). His research interests include Big Data Analytics, Machine Learning with Special Interest in Deep Learning, and Bioinformatics.

Prior to joining FIU, Dr. Mondal was an Assistant Professor (2012-2018) of Computer Science in the Department of Mathematics and Computer Science at Claflin University, South Carolina. At Claflin University, a liberal arts and primarily undergraduate teaching institute, Dr. Mondal was a strong proponent of bringing research to undergraduate classes he taught. He developed four courses to introduce his research in Big Data and Bioinformatics to undergraduate students at Claflin University. Students mentored by Dr. Mondal graduated with refereed publications in IEEE BIBE, IEEE BIBM, and BIOCOMP. As the culmination of his career at Claflin, Dr. Mondal received the prestigious NSF CAREER Award in 2017. He was tenured and promoted to Associate Professor at Claflin University in August 2018. In Bangladesh, Dr. Mondal served as a Lecturer and then as an Assistant Professor in the Department of Chemical Engineering at Bangladesh University of Engineering and Technology (BUET). He received his Ph.D. in Computer Science and Engineering from the University of South Carolina in 2011.

Dr. Mondal has served as the session chairs for the IEEE BIBM, IEEE BIBE, and BIOCOMP. He is a peer reviewer for Bioinformatics and IEEE BIBM. He is a member of ACM, IEEE, and ISCB.

Dr. Mondal received the Research Excellence Award twice (2015 and 2017) from the School of Natural Sciences and Mathematics at Claflin University. He also received The Attorney William H. and Annette B. Johnson Endowed Annual Faculty Award for Innovative Scientific Research Award at Claflin University (2017). Dr. Mondal is a recipient of the prestigious NSF CAREER Award (2017).

Cuong Nguyen is an Assistant Professor of the Knight Foundation School of Computing and Information Sciences, Florida International University. Before joining FIU, he was an Applied Scientist at Amazon Web Services (AWS) from 2018-2021, working on machine learning with applications to computer vision and natural language processing. Before AWS, he was a postdoc at the Department of Industrial Systems Engineering, National University of Singapore from 2015-2016 and then at the Department of Engineering, Cambridge University from 2016-2018. He received Bachelor and PhD degrees in Computer Science from the School of Computing, National University of Singapore in 2010 and 2015 respectively. His research interests include probabilistic machine learning and artificial intelligence, with applications to real-world problems in computer vision and natural language processing. He has regularly published at top conferences and journals in machine learning and artificial intelligence, including the Conference on Neural Information Processing Systems (NeurIPS), the International Conference on Machine Learning (ICML), the AAAI Conference on Artificial Intelligence (AAAI), and the Journal of Machine Learning Research.

Dr. Agoritsa Polyzou is an Assistant Professor of Computer Science in the Knight Foundation School of Computing and Information Sciences at Florida International University (FIU). Before joining FIU, she was a postdoctoral Fritz family fellow in the Massive Data Institute (MDI) of McCourt School of Public Policy at Georgetown University. She received her Ph.D. in Computer Science and Engineering from the University of Minnesota in 2020, and her Bachelor in Computer Engineering and Informatics from the University of Patras, Greece. She is engaging in projects at the intersection of big data, machine learning, ethics, and fairness. Her research interests include data mining, recommender systems, the application of machine learning techniques within educational contexts, and the fairness concerns that arise from their use. Her goal is to help students succeed using data and machine learning models. At the same time, she is interested in ensuring that such models will be fair and responsibl

Monique Ross earned a doctoral degree in Engineering Education from Purdue University. She has a Bachelor’s degree in Computer Engineering from Elizabethtown College, a Master’s degree in Computer Science and Software Engineering from Auburn University, eleven years of experience in the industry as a software engineer, and five years as a full-time faculty in the departments of computer science and engineering. Her interests focus on broadening participation in computer science through the exploration of: 1) race, gender, and identity; 2) discipline-based education research (with a focus on computer science courses) in order to better inform pedagogical practices that garner interest and retain women and minorities in computer-related fields. She is the PI on three National Science Foundation grants, one foundation grant, and co-PI on two large scale grants. Dr. Monique Ross is committed to the expansion of rigorous computer science education research at FIU and nationally.

Dr. Farhad Shirani received his Ph.D. from University of Michigan, Ann Arbor, in 2016. He was a Research Assistant Professor at New York University in 2016-2020. His research focuses in the areas of privacy and security, wireless communications, and machine learning.

Dr. Ruimin Sun graduated from University of Florida in 2019 (under Dr. Daniela Oliveira) and worked as a Postdoctoral Research Associate in the Khoury College of Computer Sciences (working with Dr. Long Lu) at Northeastern University. Her research aims at securing ubiquitous systems (desktop, mobile, IoT/CPS) and protect end users from cyber-attacks through enhanced security mechanisms with intelligent defense strategies. Her research focuses on cyber physical system security, mobile device information privacy, real-time anomaly detection, and system security and reliability.

Dr. Xuyu Wang is an Assistant Professor in the Knight Foundation School of Computing and Information Sciences at Florida International University. Before joining FIU, he was an Assistant Professor in the Department of Computer Science at California State University, Sacramento. He received his Ph.D. from the Department of Electrical and Computer Engineering at Auburn University in 2018. His research interests include wireless sensing, Internet of Things, wireless localization, smart health, wireless networks, and AI security. He received the NSF CRII Award in 2021. He was a co-recipient of the Second Prize of the Natural Scientific Award of the Ministry of Education, China, in 2013, the IEEE INFOCOM 2022 Best Demo Award, the IEEE ICC 2022 Best Paper Award, the IEEE Vehicular Technology Society 2020 Jack Neubauer Memorial Award, the IEEE GLOBECOM 2019 Best Paper Award, the IEEE ComSoc MMTC Best Journal Paper Award in 2018, the IEEE PIMRC 2017 Best Student Paper Award, and the IEEE SECON 2017 Best Demo Award. He was invited to organize AI health tutorials at CVPR 2020, ICC 2022, and CVPR 2022, a special session at IEEE BHI 2021, and give a keynote speech at CVPM 2020. He is an editor of Elsevier Book titled “Contactless Vital Signs Monitoring”. He is also an associate editor of Elsevier Digital Communications and Networks and a guest editor of ACM Transactions on Sensor Networks.

Dr. Yanzhao Wu is an Assistant Professor in the Knight Foundation School of Computing and Information Sciences at Florida International University. He obtained his bachelor’s degree from University of Science and Technology of China in 2017 and then received his Ph.D. degree in Computer Science from Georgia Institute of Technology in 2022. His research interests are primarily centered on the intersection of machine learning and computing systems, including machine learning algorithm and system optimizations, deep learning, edge AI, and big data analytics. His work has been published in top venues, including CVPR, ICSE, IEEE ICDCS, IEEE ICDM, IEEE TSC, and ACM TOIS, and won the IEEE CIC 2021 best paper award. He also serves as a reviewer for top conferences and journals, such as ICDE, WWW, CVPR, ECCV, AAAI, IEEE ICDCS, IEEE TKDE, and ACM TOIT.