ICS Tutorial Series -Bioinformatics: Machine Learning Approach

FOR IMMEDIATE RELEASE
Contact: Michelle Williams
(949) 824-1562, micwilli@uci.edu
April 30, 2002

MEDIA ADVISORY

ICS Schedules Tutorial Series Aimed at Working Researchers, Industry Enthusiasts

EVENT: The Department of Information and Computer Science announces its first professional-level instructional series for information technology professionals, academic researchers and graduate students. This tutorial series highlights the latest research initiatives underway by ICS experts. Topics scheduled for the first year include: bio/medical informatics, data mining and embedded systems. Each three-hour session will include a lecture by the presenting faculty member and an open forum for questions.

DATES: Wednesdays - May 29, July 17 and October 30

TIME: 4-7 p.m.

COST: $35/session; $90/all three

LOCATION: UC Irvine University Club Library

RESERVATIONS: www.ics.uci.edu/tutorial

ABOUT ICS: The Department of Information and Computer Science was founded in 1968 in recognition of the emerging importance of this field. Its mission is to produce an educated workforce that can adapt to the rapidly changing discipline and which serves as an economic engine for the advancement of technology. With 41 faculty members, 1,750 undergraduates and 250 graduate students, ICS is the largest computing program within the University of California system as well as the fastest growing major at UC Irvine. ICS is a Top 15 Public Computer Science Graduate Program.

SESSION DETAILS

May 29, 2002
Pierre Baldi, "Bioinformatics: Machine Learning Approach"
Abstract: The tutorial will provide an overview of fundamental problems in bioinformatics, including: (a) DNA sequence analysis; (b) protein structure and function prediction; (c) DNA microarray data analysis and gene regulation; and (d) reverse engineering of biological systems. It will also provide a broad introduction to state-of-the-art computational methods to address these problems and machine learning approaches that can automatically extract information from large repositories of data produced by high-throughput technologies such as DNA sequencing and DNA microarrays.

Biography: Professor Baldi is Director of the Institute for Genomics and Bioinformatics, layer leader of Digitally Enabled Genomic Medicine in the California Institute for Telecommunications and Information Technology [Calit²] and holds joint appointments in the Department of Information and Computer Science and the College of Medicine's Department of Biological Chemistry. He also is conducting research Author of "The Shattered-Self: The End of Natural Evolution", Baldi's research focuses on several areas of data mining, machine learning, bioinformatics and communication networks. Projects in his group include understanding and predicting protein structures, analyzing and modeling gene expression data and regulatory networks, analyzing and designing communication networks (Internet, Ultra Wide Band Radio) and quantifying information.

July 17, 2002
Padhraic Smyth, "Data Mining: Concepts and Applications"
Abstract: Technology improvements in sensors, data storage and computational power have led to the accumulation of massive digital data archives across a wide variety of fields in engineering, business, medicine and science. Data mining is the application of techniques from both computer science and
statistics to extract useful information from massive data. We will begin by briefly reviewing some of the basic concepts in data mining, covering key ideas in pattern-finding, clustering, classification and related topics. The main focus of the tutorial will be on how these techniques are being use to solve large-scale
data-rich problems across a variety of applications areas, such as fraud detection in telecommunications and credit-card services, credit-scoring technologies for banking, adaptive personalization for retail and marketing applications, automated classification and parsing of documents such as Web pages, and so forth.

Biography: Professor Smyth, a researcher in the Interfaces and Software Systems layer of the California Institute for Telecommunications and Information Technology [Calit²] balances theory and application in his research projects. Theoretical models provide a framework for principled and sound analysis of techniques and algorithms for inferring patterns from data. But data analysis is fundamentally a practical problem: the investigation of ideas and application of algorithms to real-world data sets is a very important component of his work.

October 30, 2002
Nikil Dutt, "Architectural Exploration for Programmable Embedded Systems"
Abstract: Advances in System-on-Chip (SoC) technology make it possible to utilize customizable embedded processor cores, together with a variety of novel on-chip/off-chip memory hierarchies, allowing customization of SoC architectures for specific embedded applications and tasks. System architects thus critically need a methodology that allows them to explore programmable architectural alternatives, comparatively evaluate candidate architectures, and complete the entire design flow, including both the hardware and software concurrently. Furthermore, the methodology must address validation and verification issues up front, so that the entire design flow can be reliably completed within the desired schedule and budget. This talk presents a methodology for architectural exploration of programmable embedded systems using an Architecture Description Language (ADL) formalism. Using this ADL-based approach, system designers can explore alternatives, rapidly generate the entire software toolchain (including compilers, simulators, and debuggers) and can use the ADL description as a golden reference model against which the ensuing design implementations can be verified. The talk will present some case studies undertaken with the EXPRESSION ADL developed at UC Irvine, and will conclude with a summary of future directions.

Biography: In the past, Professor Dutt has studied the use of hardware description languages (HDLs) for design specification in the context of synthesis, simulation and verification. He has developed new languages for design specification, and has researched the role of standard HDLs (e.g., VHDL) in accelerating the design cycle. His work in this area has led to two consecutive Best Paper Awards at the International Symposium on Computer Hardware Description Languages (CHDL89 and CHDL91). He is currently researching CAD tools for embedded systems-on-silicon that have large amounts of software and hardware and is an active participant in research taking place at the the California Institute for Telecommunications and Information Technology [Calit²].

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ICS Tutorial Series -Bioinformatics: Machine Learning Approach