Machine learning uses computational, theoretical, and statistical principles to develop algorithms that model data from real-world phenomena and make accurate predictions about the phenomena. Machine learning operates in supervised, unsupervised and semi-supervised settings to perform classification, regression, visualization, clustering, dimensionality reduction, network modeling, graphical modeling, inference and structured prediction.
Computer engineering research includes computer architecture; VLSI design; hardware security; power- and energy-efficient architectures; interconnection networks; support for emerging technologies and applications; design and optimization of asynchronous and mixed-timing digital circuits and systems; computer-aided design (CAD) tools including system-level design, communication synthesis and logic synthesis; embedded software and distributed embedded systems; and domain-specific language design and compilation.
Our systems research includes a broad range of topics encompassing architecture-sensitive database system design, cloud computing, collaborative work, computer and network privacy and security, concurrent and parallel systems, database systems, data warehousing, deterministic multithreading, distributed systems, information extraction and management, file systems, mobile computing, multicore systems, multimedia systems, operating systems, performance evaluation, programming languages and compilers, quantum computing, query languages and processing, social media mining, software development environments and tools, software engineering, software reliability, software testing, thin-client computing virtualization, web search, and web technologies.
Computational biology and bioinformatics involve development and application of analysis methods for high throughput experimental data in molecular biology to facilitate biomedical research. Active topics of investigation in Columbia involve systems biology, biological networks, massively parallel (“next generation”) DNA sequencing, RNA sequencing, ChIP sequencing, analysis of transcription factor binding sites, single nucleotide polymorphisms, population genetics, molecular evolution, personalized medicine, tumor genomics.
Security and privacy research includes intrusion detection systems, cryptology, privacy-preserving computation and search, usability of security interfaces, self-healing systems, denial of service, system hardening, information accountability, hardware enabled security, and insider threats.
Natural Language Processing and Spoken Language Processing involves computational approaches to the analysis and generation of text and speech. At Columbia these include text and speech summarization, question answering, machine translation, syntax and parsing, language generation, spoken dialogue systems, semantic representation and analysis, and the study of emotional and deceptive speech, in English, Arabic, and Mandarin, inter alia.
Theory research includes computational complexity, algorithms and data structures, cryptography, quantum computing, computational geometry, approximation algorithms, computational game theory, algorithmic graph theory and combinatorics, online algorithms, computational learning theory, algebraic computation, optimization, randomness in computing, parallel and distributed computing, algorithmic coding theory, and theoretical aspects of areas such as networks, privacy, information retrieval, computational biology, and databases.