The Baskin School of Engineering welcomes nine new faculty members this year, bringing the total faculty count to 115. These new faculty bring expertise in a wide range of subjects to the school of engineering, including statistical computing, computer security, human-robot interaction, wireless communications, serious games, artificial intelligence, and more.
Marcela Alfaro Córdoba, Assistant Teaching Professor
Statistics
Research interests: Statistics education, statistical computing, functional data analysis, reproducible science, spatial statistics
Marcela Alfaro Córdoba is interested in developing novel statistical methods to address scientific questions related to natural sciences while providing computational solutions for reproducible scientific work. Her focus is not only on the statistical practice but also on modern pedagogical approaches in the statistics curriculum.
Advice for students: “College is all about opening your mind and learning different perspectives. Search for mentors, not only on campus but also in industry. Having different mentors can help you build a stronger network, and can also help you learn and understand areas of knowledge from different perspectives. Reach out and collaborate with people from different backgrounds: other majors, other contexts. Doing this for your projects inside and outside the classroom will improve your communication skills, and expose you to different points of view.”
Ioannis Demertzis, Assistant Professor
Computer Science and Engineering
Research interests: Applied cryptography, computer security and privacy, cloud computing security, secure databases and systems
Ioannis Demertzis focuses on building simultaneously practical and provable secure cryptographic solutions with applications to cloud computing security, encrypted systems, and databases. He is interested in efficient and secure real-world privacy-preserving systems. Some of his recent projects include I/O efficient secure schemes, private query processing on relational/graph encrypted databases, mitigating leakage abuse attacks on searchable encryption, and scalable oblivious indexing techniques.
Advice for students: “Be passionate. This is the time to explore, study and be curious about the different groundbreaking fields in Computer Science and Engineering. Through this process you will learn a lot, and this will create more job opportunities for you in the future and make you adaptive to challenges and changes. But most importantly, this process will help you discover your true passion. Whether it is coding complicated systems, developing new algorithms and models, or solving hard problems, it all boils down to finding which subject makes you want to put that extra effort that will make you the best at it. Finding that subject will be the key to achieving your personal goals and happiness.”
Zehang “Richard” Li, Assistant Professor
Statistics
Research interests: Bayesian statistics, latent variable models, spatial-temporal models, causal inference, global health, applications in epidemiology and social sciences
Zehang Li is interested in statistical methods and tools to address scientific questions in demography, epidemiology, and global health. He is currently working on latent variable modeling in messy, high-dimensional data, space-time models, causal inference, and applications in health data science.
Advice for students: “Explore areas you are passionate about. The study of data science is much more than just learning technical tools. The more challenging and fun part is to utilize your skills and perspectives to advance human society by tackling issues in natural and social sciences, health, business, and so many other disciplines. Learn about the fields you are interested in, communicate with experts in these areas, and explore complex real-world problems. You can make a broad impact on people’s lives in many different ways.”
Steve McGuire, Assistant Professor
Electrical and Computer Engineering
Research interests: Field robotics, perception, human/robot interaction, psychophysiology, supervisory control, human-in-the-loop decision making, high-risk environments
Steve McGuire develops techniques to help robotic systems better understand the world around them, particularly in difficult-to-understand and hazardous environments. His work includes not only onboard sensing and perception, but also the human operators and personnel forming the complete system. One key component of his work is the idea of mutual adaptation, or enabling robots to alter their behaviors based on their operators’ experiences and physiological signals of opportunity. His principal application involves systems performing the dull, dirty, and dangerous tasks particularly suited to human-robot teams.
Advice for students: “In school, you’ll learn a lot of theory. Get involved with a project (perhaps through a student club or your own) that you’re passionate about, that resonates with your interests, as a means of applying what you’ve learned to solve real-world problems that you personally care about.”
Sagnik Nath, Assistant Teaching Professor
Computer Science and Engineering
Research interests: Computer architecture, FPGA/ASIC design, chip design (VLSI), low power computing, physical design, machine learning
Sagnik Nath has worked on the development and design of asynchronous cells for Single Flux Quantum (SFQ) technology that allows it to be compatible with commercial design flow approaches in industry. The asynchronous cell design approach has demonstrated potential to implement power efficient high performance computing as opposed to the exponential power expenditure with respect to performance of traditional semiconductor based computing.
Advice for students: “It is common for us as adults to distance ourselves from all traits typically associated with childhood. However, one such trait that we should hold on to as students of engineering is the sense of childhood wonder and curiosity. The small toys and action figures that captivated us as children have been supplanted by real world tech that we have an opportunity to study and innovate upon when we access the relevant resources at the university and later industry. A sense of childlike curiosity can also be very effective fuel on study nights prior to exams and later in industry/postgraduate research. It will help you to be very flexible in quickly latching on to new technology no matter your age. Being a good communicator also helps as does the practice of not overthinking and over analyzing every problem you encounter. Sometimes, a calm mind is all you need to resolve such a situation.”
Zouheir Rezki, Assistant Professor
Electrical and Computer Engineering
Research interests: Wireless communications and networking, network security and privacy, information theory, machine-learning applied to communication systems, optical communications, communication as an enabling technology for smart grids
Zouheir Reiki’s research in wireless communications and networking includes security and privacy of data networks, applying machine-learning techniques to design and optimize modern communication systems, information theory, optical communication, and application of communication technology for smart grids. He is the recipient of a 2020 NSF CAREER Award. He is an IEEE Senior Member and served as an editor of IEEE Wireless Communications Letters.
Advice for students: “A lesson I learnt from wise people which I proudly convey to my students: The 3P rule: patience, perseverance, and practice. Hard work always pays off, it’s only a matter of time!”
Magy Seif El-Nasr, Professor
Computational Media
Research interests: Modeling the player experience, game ai, plan recognition and player behaviors; interactive narrative; open player and open learner models; games for learning; games for health
Magy Seif El-Nasr’s research focuses on (a) developing automated tools and techniques for authoring, adapting, and personalizing virtual environments, and (b) developing evidence-based methodologies to measure the effectiveness of game environments. She published the first book on game analytics, Game Analytics: Maximizing the Value of Player Data. Her work is internationally known. She is a HEVGA (Higher Education Video Game Alliance) Fellow and serves as an associate editor for IEEE Transactions on Games and IEEE Transactions on Affective Computing.
Advice for students: “One thing that you will learn as you progress through your career is how to effectively manage your time. This is not easy. Do not hesitate to ask your colleagues, not just about the technical or discipline-specific problems, but also about how to deal with time, schedules, constraints, etc.”
Xin Wang, Assistant Professor
Computer Science and Engineering
Research interests: Embodied AI, natural language processing, computer vision, machine learning
Xin Wang’s research interests include natural language processing, computer vision, and machine learning, with an emphasis on building embodied AI agents that can communicate with humans using natural language to perform real-world tasks. In the realm of NLP, he is interested in natural language grounding, knowledge-based reasoning, and multilingual understanding. His interest in computer visions includes vision and language, visual navigation and robotics, and activity understanding. The areas of machine learning he is particularly interested in are deep learning, self-supervised learning, reinforcement learning, and multimodal machine learning.
Advice for students: “Aim high and stay grounded. Always set a high bar for the long run. Never settle and keep learning. Meanwhile, computer science is a very practical major, so keep your hands dirty and make progress step by step.”
Cihang Xie, Assistant Professor
Computer Science and Engineering
Research interests: Artificial intelligence, machine learning, deep learning, computer vision
Cihang Xie is a computer vision and machine learning researcher. His research goals include building human-level computer vision systems, particularly in securing model performance under the worst-case scenario and endowing models with interpretability. Cihang is also interested in deep learning and its applications, such as autonomous vehicles.
Advice for (computer science) students: “As a computer science student, you should (1) put enough effort into mastering at least one programming language–this is your tool to communicate with computers; (2) be open to new techniques and challenges, as our community is moving pretty fast in the last few years.”
