Tufts provides computer science majors with a solid grounding in theoretical computer science and algorithmic knowledge, applied computer science, and software engineering skills enabling them to pursue professional careers in computing or software. Students also go on to graduate work in computer science and related disciplines.Faculty research areas include algorithms and theory of computation, artificial intelligence, computational biology, computational geometry, computational systems biology, cognitive science, digital humanities, educational technologies, Electronic Design Automation (EDA) and VLSI design, human computer interaction, image processing, machine learning and data mining, network and system administration/autonomic network management, numerical linear algebra, programming languages and systems, robotics and human-robot interaction, and visualization and graphics. The department sponsors a colloquium each semester on leading-edge topics within the field such as anatomy and animation, computer security, 3-D interaction techniques, and devices for gaming.Tufts provides computer science majors with a solid grounding in theoretical computer science and algorithmic knowledge, applied computer science, and software engineering skills enabling them to pursue professional careers in computing or software. Students also go on to graduate work in computer science and related disciplines. Students can major in Computer Science through the School of Engineering or the School of Arts & Sciences.The Computer Science major includes ten courses: eight in computer science and two in mathematics. Students in the Bachelor of Science in Computer Science program in Engineering must earn a C- or better in 75% of concentration courses. They also must have a C- or better in two-thirds of their 120 credit hours.<br><br>Bioinformatics applies computer science techniques to analyze and interpret biological data. At Tufts, bioinformatics research and education span several key topics including computational biology, systems biology, bioengineering, and biomedical informatics. Key underlying techniques include machine learning, statistical science, and algorithms. Built on a strong computer science foundation, this focus area provides breadth and depth in bioinformatics to prepare students for careers or graduate school in fields at the intersection of biology and computer science. This focus area applies equally well for Arts and Sciences (A&S) and School of Engineering (SoE) students, and for both Computer Science and Data Science majors.