Predictive models, machine learning, probability knowledge

ANH TRUONG

University of Illinois at Urbana-Champaign.

Mailing address: 307 Birch St, Apt 2, Champaign, IL, 61820. Email: *******@********.***

Cell: 217-***-****

ACADEMIC RECORDS

• PhD student, 2011 – present Expected graduation: February 2016 University of Illinois at Urbana-Champaign (UIUC)

Department of Industrial and Enterprise Systems Engineering (ISE) Advisor: Negar Kiyavash

• MS. Electrical and Computer Engineering, 08/2011 University of Illinois at Urbana-Champaign (UIUC)

Advisor: P. R. Kumar, Negar Kiyavash

• Bachelor of Engineering. Telecommunications, 10/2005 Program for High Quality Engineer Training (PFIEV) University of Technology, HoChiMinh City, Vietnam

PROFESSIONAL EXPERIENCES

5/2013–8/2013: Internship, Bosch Research and Technology Center, Data Mining Group

• Investigate manufacture datasets (automatic control devices) with noisy labels and high imbalance

• Apply combinations of classifiers, LDA, Naïve Bayes, Decision Tree, k-NN, SVM, to identify mislabeled instances

• Feature extraction and selection; dimensionality reduction using PCA

• Data visualization, clustering to see the separation of dataset

• Programmed in: Python

5/2012 – 8/2012: Internship, Research In Motion (RIM), Advanced Technology Group

• 3D gesture recognition using electric field

• Modify a hardware system with 8 receivers, 2 transmitters, MCU Atmega168

• Analyze/learn patterns from the electric field distortions by receiving real-time signal from the hardware

• Able to recognize some hand movements and simple shapes

• Programmed in: Python (for PC) and C (for hardware) 5/2011 – 8/2011: Google Summer of Code (GSoC), Organization: Freifunk

• Implement a modified TSF (Time Synchronization Function) mechanism for ath9k to use power efficiently

• Programmed in: C. Write patches on compat-wireless-3.0-2 package CODING SKILLS

Python: proficient; C++, Matlab: expert; C, Java: prior experience (from course projects and interns) Tools: GitHub, MongoDB

RESEARCH EXPERIENCES

2011 – Present: Research Assistant, University of Illinois at Urbana-Champaign Learning with expert advice, with the application on rating systems, online recommendation systems, weather, stock forecasting.

• Propose weight update rules for experts based on their performance and the average, under the sleeping experts framework

• Define the best expert by his availability and accuracy

• Analytical result: convergence of the proposed algorithm to the best expert(s) under stochastic setting; and upper bound of the regret under adversarial setting

• Find the best ranking of experts in sleeping bandit setting using upper confidence bound (UCB)

• Optimal attacking strategy for adversarial experts: threshold policy for absolute loss, and greedy policy for logarithmic and square losses

• Efficient (selective) labeling of objects by considering the disagreement of experts advice, with or without prior knowledge of the datasets.

• Programmed in: Matlab, Python, for both synthetic and real datasets (Netflix) Project done

• Topic Initiator discovery in DBLP, Programmed in: Java, Spring 2013.

• Semantic Textual Similarity using LLM (Lexical Level Matching), SRL (Semantic Role Labeling), Parse Tree, Part of Speech, Name Entity, Programmed in: Java, Spring 2012 SELECTED PUBLICATIONS

Anh Truong, Negar Kiyavash, Learning From Sleeping Experts: Rewarding Informative, Available and Accurate Experts, IEEE Transaction on Neural Networks and Learning Systems

(submitted).

Anh Truong, Negar Kiyavash, Optimal Adversarial Strategy in Learning with Expert Advice, 52th IEEE Conference on Decision and Control, December 10-13, 2013, Florence, Italy. Anh Truong, Negar Kiyavash, and Vivek Borkar, Convergence analysis for an online recommendation system, 50th IEEE Conference on Decision and Control and European Control Conference, December 12-15, 2011, Orlando, Florida, US. COURSES IN UIUC

• Machine Learning, Topics in Machine Learning Theory, Machine Learning in NLP, Inference in Graphical Models, Data Mining Principles, Statistical Learning Theory.

• Decision Analysis, Optimization, Real analysis.

• Probability theory, Control system theory and design, Stochastic control, Computational complexity. SUPPLEMENTARY INFORMATIONS

Computer skills VB, VC, Assembly, NS-2, Opnet.

Languages English, French.

Activities Member of Vietnamese Student Community (VSC) board, UIUC, 2010-2011. Secretary of Union of Student and Staff, Department of Electrical-Electronic Engineering, University of Technology, HoChiMinh City, Vietnam, 2006-2008.

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