Special Topics Classes

Machine listening is the study of algorithms for the machine understanding of audio. It is the auditory sibling of computer vision.

This course will provide an overview of topics in the field of machine listening, focusing on the machine understanding of music and environmental sound. Lectures will cover the fundamental problems and classical approaches of the field, as well as the discussion of the field’s recent advances. Assignments in the course will be Python programming assignments on the fundamentals of the course. During the semester, each student will be tasked with presenting one of the field’s recent papers to the class.

This new course offers a broad framework for understanding the entrepreneurial mindset and the startup process and exposes students to some of the common challenges  faced by founders who start new technology ventures. This course explores some of the latest frameworks such as Lean Startup, Design Thinking, Agile process and the challenges and opportunities involved with technology-intensive startups. We will explore strategies on how to deal with some of the common issues associated with technology ventures such as finding good ideas, dealing with risk and uncertainty, finding co-founders, raising seed capital, and designing, testing and validating a product with real customers, and developing a viable business model.

Recommended prerequisite: IT 266. This course introduces the core concepts and skills necessary for the development of games utilizing 3D graphics. Students will learn how to set up and program their own 3D graphics-based game engine using industry standard graphics libraries. Students will learn how to load and display custom 3D models created using existing 3D modeling tools. Students are expected to create fully functional 3D games and associated tools to work with them.

Machine listening is the study of algorithms for the machine understanding of audio. It's the auditory sibling of computer vision. It has diverse applications such as automatic music transcription, music recommendation, audio search, smart home acoustic sensing, machine condition monitoring, audio captioning, urban noise monitoring, and wildlife monitoring. This course will provide an overview of topics in the field, focusing on the machine understanding of music and environmental sound. Lectures will cover the fundamental problems in the field and both classical and modern approaches to solving these problems. Students will complete weekly Python-based assignments, present machine-listening research papers to the class, and complete a semester-long project of their choosing.

This course introduces a wide range of research in the area of mobile sensing with applications for smart cities, smart homes and digital health. Topics will introduce fundamentals of sensing and analytics as applicable to smartphones, personal wearables, edge processors, AR/VR systems and mobile robots, and will cover a range of techniques pertinent to indoor/outdoor localization, activity and physiological sensing for mobile health, deep learning under resource constraints, and collaborative processing. Students will critique mobile systems research papers through reviews and in-class presentations, work on a semester-long project, and appreciate design choices and performance trade-offs in the context of mobile sensing.

Advances in Cyberpsychology will focus on the psychological processes related to, and underlying, all aspects and features of technologically interconnected human behavior. Cyberpsychology is an interdisciplinary area which includes disciplines such as psychology, human-computer interaction, computer science, engineering, sociology, and communications. With the growth of new technologies and an increasingly interconnected world, the field of cyberpsychology has emerged as a unique discipline. This includes the effects of the internet and cyberspace on individuals and groups as well as the impact of human beings on cyberspace.This course will cover key themes and trends in the field such as online persona, social media use and well-being, misinformation, and digital accessibility. We will dive into research on fundamental psychological processes such as emotion and personality in order to understand the strengths and limitations of technological approaches such as machine learning and AI. In addition, we will explore applications and future directions of cyberpsychology to real-world challenges. This Special Topics, seminar style, course will provide opportunities to think critically about the discipline of Cyberspychology and applications to their own research and career aspirations.