Professional Interest Communities at IBM Research     


Professional Interest Communities at IBM Research - overview

Below are the "PICs" that encompass key research areas at IBM Research. They represent technical interests that our scientists focus on -- and serve as well to facilitate collaboration with our colleagues in academia.

AI Systems Researching computing systems and platforms for artificial intelligence, including but not limited to systems for machine learning, systems for deep learning, and AI for systems.

Algorithms and Theory Pursuing basic research on a broad range of theoretical topics, including approximation algorithms, combinatorics, complexity theory, computational geometry, distributed systems, learning theory, online algorithms, cryptography and quantum computing.

Cloud Software Developing software platforms and middleware to (1) enable rapid deployment that scales as large as companies want without a huge capital investment, and (2) permit the composition of any applications and services that facilitate rapid improvements in the computing environment. Many challenges exist in achieving this vision.

Computational Biology Understanding biological systems, aided by discoveries in computer science, physics, mathematics, chemistry and biology, with the goal of identifying population-wide diseases and delivering effective treatments and therapies.

Computer Systems Design Developing better system designs and architecture, with an increased focus on across-the-stack integration.

Computer Vision and Multimedia Researching fundamental machine learning algorithms, such as domain transfer, meta-learning, data augmentation, deep embeddings, interpretable AI, for computer vision applications such as classification, object detection, segmentation, facial analysis, captioning, and natural language interactions with images.

Health Informatics Using huge volumes of data to study how computer systems can manage and analyze the complex processes inherent in medical research and practice.

Human Computer Interaction and Data Visualization Creating a deep understanding of the relationships between people and intelligent systems, designing compelling and interactive visual systems to enable exploration of data and algorithms, and providing human insights into the creation of trusted, explainable, and ethical AI.

Internet of Things Researching interconnected technologies -- each one reflecting a degree of behavioural autonomy, adaptiveness, sensing and interaction with the other -- to enable more adaptive real-time processing of information and a high degree of scalability.

Knowledge Researching foundations of storage, representation, retrieval, curation and consumption of knowledge in AI systems.

Knowledge Discovery and Data Mining Extracting useful knowledge from data, notably in the areas of statistics, databases, pattern recognition, machine learning, data visualization, optimization and high-performance computing, to deliver advanced business intelligence and web discovery solutions.

Learning Emphasizing all aspects of machine learning -- including theory, algorithms and applications -- and addressing issues in automated reasoning, computational biology and perception.

Natural Language Processing Performing cutting-edge research on several areas like Information Extraction, Question Answering and Machine Translation and also their application to products.

Operations Research Developing algorithms in the areas of optimization, statistics, queueing theory and agent-based systems that impact many real-world business issues, such as vehicle routing and staffing; supply chain modeling and optimization; manufacturing planning and scheduling; transportation modeling; process industry scheduling; service industry resource planning and scheduling, and airline optimization and forecasting.

Performance Modeling and Analysis Applying theory and analysis to technology models and experimenting with prototype implementations in order to better design, develop and optimize computer and communication systems and applications.

Programming Languages and Software Engineering Participating in programming language design and implementation; performance analysis of multi-tier systems; modeling and designing web-based tools; designing multi-core, hybrid and cluster programming; devekoping software for embedded devices, and studying issues such as software development methodologies and unit testing, continuous integration and deployment.

Quantum Computational Science Covering quantum applications including computational chemistry and science.

Quantum Computing Obtaining integrated insights into algorithm design, error correction or mitigation, software environment and the mapping of real-life applications to quantum or hybrid quantum-classical devices.

Reasoning Covering all aspects of artificial intelligence that touch on decision-making, such as search, heuristics, reasoning, planning and optimization.

Security and Privacy Working with world-class researchers to do research in cryptography, data breaches, cybersecurity network & device analytics and computer vision technologies in order to raise the bar on the security in products and services.

Services Advancing cross-disciplinary research in the related areas of service analytics, service innovation and cognitive services.

Speech Researching the enabling technologies that help computers hear (speech recognition, speaker recognition and verification) and speak (speech synthesis); and to understand and combine these in multimodal ways.

Statistics Employing forecasting, linear modeling, time series analysis and risk analysis (among others) to advance quality assurance, manufacturing, pricing, marketing, business intelligence and delivery of services -- and to work across disciplines on projects associated with speech recognition, software engineering, systems reliability modeling, supply chain management, VLSI design and data and text mining.

Supercomputing Designing and building supercomputers and relevant applications; developing systems software, libraries and programming models; and addressing issues in performance evaluation, performance modeling and benchmarking.

Last updated on November 28, 2018