It is a version of an older template that has been handed down and modified by generations of students since the late 's. Obsolete code has been removed, the tex and sty files have been extensively debugged, and it now conforms to LaTeX2e and all Rackham guidelines. The two zip files below contain all necessary files for installation of LaTeX on a Windows operating system and the dissertation template itself.
My research carries i a purely foundational component and ii a second component driven by important practical challenges. I try to keep these two research lives separate.
However, all stem from the same source. I approach practical problems by "injecting technology" from theory works developed over the years. For example, I am thinking about questions such as: Cryptography over Massively Streamed Data? For instance, part of my contribution in machine learning bridges theory and practice by improving practical heuristics in theory and significantly in experiments and in particular for very multi-class classification tasks.
I am primarily interested in: The technical challenge is that in certain cases it's best not to use that heuristic at all because using it hurts performance or accuracy.
So, how to compare algorithms that occasionally make things worse without making assumptions about the inputs?
Practically relevant theory what's the "right level for doing theory"? This setting works very well for my foundational and applied projects.
Rutgers is a great place for foundational work: At the same time a faculty at MSIS has the privilege of being exposed to important, actual real life problems. This lab was at the frontiers of research in the foundations of computing and related application areas.
In total there are four PhD students graduated under my supervision, two of whom graduated when I was at Tsinghua. I took up the assistant professor position at Tsinghua immediately after my PhD in computer science from the University of Toronto on June Since September I live permanently in Hoboken taking the long commutes to Rutgers.
We also show the necessity of adaptivity when querying one-way permutations to construct pseudorandom generators la Goldreich-Levin; an issue related to streaming models for cryptography.
In the second part we introduce streaming techniques in understanding randomness in efficient computation, proving lower bounds for efficiently computable problems, and in computing cryptographic primitives. We observe [Cook'71] that logarithmic space-bounded Turing Machines, equipped with an unbounded stack, henceforth called Stack Machines, together with an external random tape of polynomial length characterize RP; BPP an so on.
By parametrizing on the number of passes over the random tape we provide a technical perspective bringing together Streaming, Derandomization, and older works in Stack Machines.
Our technical developments relate this new model with previous works in derandomization.In this undergraduate thesis the independence of Goodstein's Theorem from Peano arithmetic (PA) is proved, following the format of the rst proof, by Kirby and Paris.
All the material necessary for its understanding is developed, beginning with the foundations of set theory, followed by ordinal. The study indicates that it is beneficial to use the Information Search Process model as the starting point for studying the student thesis-writing processes.
As the outcome of the study, we ultimately proposed a multi-stage model for Chinese undergraduate students’ thesis-writing process. Research Interests. My research investigates methodologies for secure and reliable embedded systems.
My work toward this goal spans computer engineering topics including formal verification, design automation, VLSI, and hardware security.
Science, Technology, Engineering, and Math (STEM) jobs are a key contributor to economic growth and national competitiveness. Yet STEM workers are perceived to be in short supply. via an oxidative syn thesis, however, these products were only able to be isolated from the rest of the reaction mixture chromatographically, rather than as an individual and usable product .
Frag is a 3D first person shooting game written in Haskell, by Mun Hon Cheong. It is licensed under the GPL. The design and implementation of Frag is described in Mun's undergraduate thesis, Functional Programming and 3D Games.