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[text] "Terran Lane"
[comment] "
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// "
[TAG=tbody]
[TAG=img] ALT="The University of New Mexico" SRC="pics/unm_web_logo.jpg"
[text] "Terran Lane"
[TAG=img] ALT="Great Literature of the English Language" SRC="pics/chess.jpg"
[TAG=tbody]
[text] "Assistant Professor"
[TAG=br]
[text] "The University of New Mexico"
[TAG=br]
[text] "Department of "
[text] "Computer Science"
[TAG=br]
[text] "Farris Engineering Bldg. 325"
[TAG=br]
[text] "Albuquerque, NM 87131-1386"
[TAG=br]
[text] "505-277-9609 (phone)"
[TAG=br]
[text] "505-277-6927 (fax)"
[TAG=br]
[text] "terran"
[TAG=img] ALT=" at " SRC="pics/atb.png"
[text] " cs.unm.edu"
[text] " "
[text] "As you can see from the above, I'm an assistant professor of computer science at UNM. My primary (academic) interests are in machine learning; reinforcement learning, behavior, and control; and artificial intelligence in general. I'm also interested in computer/information security/privacy and in bioinformatics. As you can probably also tell from the layout of this page, I'm not an expert on web layout or graphical design. I can discuss the statistical and graph-theoretic properties of the web with you, though, if you like."
[TAG=hr]
[text] "Hiring"
[text] "The "
[text] "postdoctoral researcher"
[text] " position has been filled. Thank you to all who applied."
[TAG=hr]
[text] "CLASSES"
[comment] " 
"
[text] "Fall 2002:"
[text] " "
[text] "CS591-005"
[text] " Introduction to Machine Learning"
[text] "Spring 2003:"
[text] " "
[text] "CS427/527"
[text] " Introduction to Artificial Intelligence"
[text] "Fall 2003:"
[text] " "
[text] "CS591-001"
[text] " Introduction to Machine Learning"
[text] "Spring 2004:"
[text] " "
[text] "CS351 -- Design of large programs"
[text] " (Java)."
[text] "Fall 2004:"
[text] " "
[text] "CS491/591 -- Introduction to Machine Learning"
[text] "Spring 2005:"
[text] " "
[text] "CS351 -- Design of large programs"
[text] " (Java)."
[TAG=hr]
[text] "Schedule"
[text] "My schedule for F'05 is coming soon. No, really, I promise..."
[comment] "
"
[TAG=hr]
[text] "RESEARCH"
[text] "Machine learning is simultaneously a pragmatic discipline, concerned with the analysis of complex data from a variety of fields, and a theoretical one, concerned with the principles of what is learnable, how to represent acquired knowledge, how to deal with complexity/dimensionality, the interactions between learned knowledge and behavior, how to measure acquired knowledge, and so on. The tools we use include statistics, algorithms, knowledge representation, database theory, linear algebra, and (in recent developments) topology. My personal research interests include behavioral modeling and learning to act/behave (i.e., reinforcement learning), scalability, representation, and the tradeoff between stochastic and deterministic modeling. All of these represent different facets of my overall interest in scaling learning methods to large, complex spaces and using them to learn to perform lengthy, complicated tasks and to generalize over behaviors. While I attempt to understand the core learning issues involved, I often situate my work in domain studies in practical (well, ok, semi-practical anyway) problems. Doing so both elucidates important issues and problems for the learning community and provides useful techniques to other disciplines."
[text] "Publications"
[text] "Scaling Techniques for Planning and Learning in MDPs and POMDPs"
[text] "The reinforcement learning paradigm rests on the foundation of the theory of Markov decision processes (MDPs) and their bigger, badder cousins, partially observable MDPs (POMDPs). While tractable methods for optimal planning in small MDPs have been understood for decades now, we still hit a wall when we try to scale to larger domains. In this project, I'm working on techniques for performing approximate planning and learning in large (e.g., 2^500 states or more) models."
[text] "Anomaly detection for computer security"
[text] "A number of critical problems in computer security can be viewed as distinguishing some "normal" circumstance from "anomalous" or "abnormal" circumstances. For example, we can think of computer viruses as being (syntactic and begavioral) abnormal modifications to normal programs."
[text] "Computational modeling of RNAi"
[text] "RNA interference is a recently discovered biological mechanism that appears to be a widespread and highly evolutionarily conserved (i.e., ancient) genetic immune mechanism. Research in the past five years or so has shown that it is involved in defense against some classes of viruses and transposons, as well as in certain cellular regulatory mechanisms. The exciting feature of this mechanism is that it can be exploited mechanistically to target some viruses, offering hints of the first possible direct treatment for viral infections, as well as to selectively knock down the expression of specific genes (via posttranscriptional disruption of the corresponding mRNA), greatly simplifying gene function studies."
[text] "Unfortunately, while a reasonable qualitative picture of the mechanics of RNAi has emerged, we are still far from a quantitative and predictive understanding. Currently, activating sequences (siRNA or dsRNA) are hand-picked employing rough "rules of thumb". Our group is attempting to build more quantitative and predictive models by applying machine learning-based bioinformatic techniques to genome and RNAi data sets. Our goals are to produce high-accuracy predictions of the activity of specific sequences and, hopefully, to shed light on some of the mechanical and evolutionary details of RNAi. Along the way, we hope to answer pragmatic questions such as the expected false positive rate (i.e., rate of knockdown of untargeted genes) and minimal covering sets for gene families."
[text] "Students"
[text] "I'm fortunate enough to have the chance to work with a number of excellent students here at UNM who're deeply involved in various interesting ML projects including analysis of fMRI (neuroimaging) data, bioinformatics, and reinforcement learning. Check in with each of them to find out what they're up to!"
[text] "Noorus Sahar Abubucker"
[text] " (MS): Reinforcement learning for streaming media rate control"
[text] "John Burge"
[text] " (PhD): Bayesian structure search for analysis of fMRI data"
[text] "Avani Gadani"
[text] " (MS): Network inference from neuronal activity data"
[text] "Hamilton Link (PhD): User modeling; modeling of security protocols"
[text] "Rory McGuire"
[text] " (Undergrad): Privacy protecting data mining"
[text] "Jong Park"
[text] " (PhD): Intrusion and anomaly detection"
[text] "Shibin Qiu (PhD): Quantitative modeling of RNA silencing (a.k.a., RNA interference; Posttranscriptional gene silencing) processes"
[text] "Wenzhong Zhao (PostDoc): Quantitative modeling of RNA silencing (a.k.a., RNA interference; Posttranscriptional gene silencing) processes"
[comment] " out of date or graduated "
[comment] " Leigh Fanning (PhD):
Quantitative modeling of RNA silencing (a.k.a., RNA interference;
Posttranscriptional gene silencing) processes "
[comment] " Daniel Force (MS): Inverse reinforcement learning and preference
elicitation "
[text] "Alumni"
[text] "Here are some of the students who have graduated from my lab and gone on to (hopefully illustrious) endeavors elsewhere:"
[text] "Kavan Puranik"
[text] " (MS): Protocols for secure, low bandwidth, wireless communications"
[TAG=hr]
[text] "Other (Academic) Activities"
[TAG=tbody]
[TAG=img] ALT="Center for Evolutionary and
Theoretical Immunology (CETI)" SRC="pics/ceti_logo-small.png"
[text] "I am a member of the UNM Center for Evolutionary and Theoretical Immunology (CETI)."
[TAG=tbody]
[text] "Machine Learning Reading Group"
[text] ": The "
[text] "Machine Learning Reading Group"
[text] " will meet Fri 3:30-5:00 during the Summer, 2004 semester."
[text] "RNA Interference Reading Group/Journal Club"
[text] ": The "
[text] "RNAi Reading Group"
[text] " will meet on alternate Wednesdays from 1:00-2:30 during the Summer, 2004 semester."
[text] "I was the Proceedings Chair for the "
[text] "Twentieth International Conference on Machine Learning (ICML-2003)"
[text] " held in Washington D.C., August 21-24, 2003."
[TAG=tbody]
[TAG=img] ALT="Workshop logo image." SRC="pics/small_timed_logo_no_bg.png"
[text] "I was also a co-chair of a workshop held in conjunction with ICML-2003 on "
[text] ""Machine Learning Technologies for Autonomous Space Applications"."
[text] " The workshop was excellent, and we all learned a lot about the various open problems, practical issues, and directions for future work. A summary of the day should be available online soon."
[TAG=tbody]
[text] "I am the faculty advisor for the "
[text] "UNM Student ACM Chapter"
[text] ". This chapter has had a somewhat rocky history, but we're working to really get it off the ground this year!"
[comment] "
MIT homepage.
My GPG public key is available.
"
[TAG=hr]
[text] "Last Modified on Monday, 24-Jan-2005 13:03:52 MST"
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