interested in all aspects of intelligence, especially from a
I am a founding member of the Tetration Analytics group at Cisco (since 2014), exploring machine
learning/data analytics, almost entirely unsupervised, to make data centers
more intelligent and secure. Previously, in reverse chronological order, I was at Google (ml for YouTube, NLP), at SRI (AI Center), Yahoo! Research, U Alberta,
U Washington, U Houston, Saddleback Community College, and spent my formative years in Iran (Bandar Abbas and Tehran), then Dubai, UAE.
My research has included the following threads:
I am inspired by how our minds might work! In particular, the
type of problems that we solve. An important feature
of our intelligence that perhaps separates us humans from many other animals
is the huge number of inter-related concepts that we (apparently) acquire and
develop and effectively use. Here, by "concept"
I mean a recurring
(and useful) pattern, such as words and phrases uttered in continuous
speech, or visual objects and entities such as books, faces, common
action sequences, etc. What tasks and problems, processes and
algorithms, and representations and data structures, support developing such
complexity? These questions are very broad and provide a starting
point. I hope to contribute to answering some such questions, in
particular from the perspective of
computational learning and
I have worked on mostly AI, and machine learning in particular,
now for more than 2 decades! Key problem properties have revolved
around unsupervised and self-supervised learning, large-scale
learning, multiview learning, online learning, data mining, active
learning, situated/embedded systems (in rich environments),
imperfect/noisy features and labels/feedback, multiple (learning)
systems interacting, and so on.
I have been working on efficient learning algorithms for
supervised learning problems with high input and output
dimensionalities (potentially huge numbers of features and
classes/concepts). The initial focus has been on online algorithms
that can handle dynamic growing sets of classes, possible nonstationarities,
Other related threads in my work include empirical and theoretial
analyses of algorithms (in particular, inspired by AI problems, such
as Markov Decision Processes (MDPs)), exploration of applications, and
discovery of new problems in the applications. Past and future
application areas include information retrieval, text and
natural language processing, game playing, personalization, vision,
and so on.
Please see the following links
for further information on my work.