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4th Annual ECE & CS Poster Competition

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Note from the ECE & CS GSA committee members:

The 4th Annual ECE & CS Poster Competition held on April 17, 2009 was a great success!! We thank the poster authors since organizing this event would not have been possible without your participation. We hope all of you enjoyed the experience and quoting Dr. Bhatnagar, 'each of you is a winner'. We also hope that this event will only grow in participation and popularity with each year that passes by. Special thanks to all the judges and the faculty and staff from both the Departments and the College of Engineering for all the help. The CS and ECE GSAs also extend their appreciation to the efforts put in by the volunteers.

Once again, thank you everybody. It is with your help that this event was a grand success.

Regards,
CS GSA & ECE GSA


The Poster Competition organized by the ECE and CS GSAs is an annual feature on the calendars of ECE and CS students. The competition provides students with a unique opportunity to showcase their work to the academic and industrial community in and around Cincinnati. This year, the competition was held on Friday, 17th April 2009. Similar to each year, we had eminent judges for judging the posters, this time from within the University of Cincinnati.


Event Results:

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Prize Winners:

Student Grant Winners ($15 each):


Event pictures:

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2009_04_17 ECE & CS Poster Competition (71)


Event Details:

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Event Schedule:

10:00 AM - 11:00 AM : Participant registration and Poster set-up
11:00 AM - 1:00 PM : Judging of posters ( 2 judges per each poster )
2:00 PM: Pizza outside 427 ERC
2:15 PM - 3:15 PM : Panel discussion + Award Ceremony at 427 ERC

The 6 judges for the event were:

  1. Dr. Raj Bhatnagar, University of Cincinnati
  2. Dr. Karen Davis, University of Cincinnati
  3. Dr. Wen Ben Jone, University of Cincinnati
  4. Dr. Ian Papautsky, University of Cincinnati
  5. Dr. Carla Purdy, University of Cincinnati
  6. Dr. Anca Ralescu, University of Cincinnati

Panel discussion session details:

The CS GSA & the ECE GSA organized a panel discussion session following the poster session. The purpose of this event was to help new students get started with their thesis / research and help older students get tips to graduate soon from others who are in the same boat. We had several senior students who talked about their experiences, providing their perspectives and answering the questions. This was similar to the panel session at the CS GSA & ECE GSA's "Research, Jobs & a Movie" event held on Saturday, April 11th 2009.

The panelists were: Suresh Kumar Alla, Mike Borowczak, Krishnendu Ghosh, Xinda Hu, Almitra Pradhan, and Raghuram Srinivasan


Instructions for the participants:

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The Poster Competition will be held on the 4th floor of ERC (Engineering Research Center) on Friday, April 17, 2009.  Several important pieces of information are listed below.  Please review them carefully.

Instructions for the event day:

Note: The timings are tentative and are subject to change, you will be notified accordingly. If you have any schedule conflicts between 11:00AM and 1:00PM or if you poster size exceeds the recommendations or if you need any special assistance, please let us know ASAP by emailing gsaposter@ececs.uc.edu.

Preparing your posters:

Availing the Student Grant:

Follow these instructions if you were awarded the student grant (check your abstract acceptance email to confirm if you received the grant). This year, we are awarding 10 student grants to partially fund the poster preparation costs (printing charges). The grants were awarded based on a first-come basis and the decisions were made by the CS & ECE GSA committee members.

Students without the grant award:

Those students who were not awarded the student grant but do require them must hold on to their original poster printing receipts and follow all the instructions above.

Grants were awarded on a first come basis. However, if a student who was awarded the grant does not meet the requirement of producing proper reciepts, or if we have surplus funds, other students will be considered for the grant.

Note: Prize money will be credited to your UC billing account within 3 weeks.


Poster Preparation Guidelines:

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Some Best Practices of Poster Design

Remember: The poster, although must convey the gist of your research on its own, is more like a power-point presentation. You will be presenting it to the audience (and the judges). Avoid having a lot of text and a lot of details. You can always mention the details in person.

Useful Links to help you design and prepare your poster:

  1. A great site that provides evaluation sheets for your poster.
    http://www.ncsu.edu/project/posters/NewSite/
  2. An on-line tutorial on designing effective posters:
    http://www.kumc.edu/SAH/OTEd/jradel/Poster_Presentations/PstrStart.html
  3. Guidelines with a Powerpoint template for preparing posters
    http://www.swarthmore.edu/NatSci/cpurrin1/posteradvice.htm
  4. Using colors effectively in posters:
    http://www.osti.gov/em52/workshop/tips-exhibits.html
  5. General Advice:
    http://www.acm.org/crossroads/xrds3-2/posters.html
  6. Lot of Math involved? Prepare posters using LaTeX:
    http://www.robots.ox.ac.uk/~awf/latex-posters/
  7. More Power-point templates:
    http://www.posterpresentations.com/html/free_poster_templates.html

Need more help? Contact: Aravind Ranganathan, President, CS GSA.


Selected Abstracts

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1. Presenter Name: Chunsheng Fang, Ryan M. Anderson
Department: Computer Science
Program: Computer Science & Engineering: Ph.D.
Advisor Name: Anca Ralescu, Ph.D.

Title: UCbir : Large-Scale Content-Based Web Image Retrieval and Tagging System

Abstract: Web search engines have come a long way in the past ten years. However, the problem of searching the web for a specific image or set of images with certain attributes is still very difficult. We propose a scalable system prototype for web image retrieval and tagging based on image content. The Internet currently has a scale of about 10 billion web pages and images. How to search web images efficiently and effectively remains an important problem in both academia and industry. We mainly explore two problems in large-scale web images: content-based image retrieval (CBIR) and content-based image tagging (CBIT). CBIR turns out to be an excellent tool for searching images based directly on the image content. CBIT is another research problem. Associating text with an image is known as tagging and is usually done manually. We propose a system that enables the efficient tagging of massive amounts of images on the web retrieved using a modified web-based crawler. Inspired by recent research in semi-supervised learning, a probabilistic model for image tagging will be proposed to propagate the limited image tags to a large amount of untagged images.


2. Name: Romana Fernandes
Advisor: Dr.Ranga Vemuri
Department: ECE
Research Area: Leakage power estimation in the presence of process variations

Title: Accurate Estimation of Vector Dependent Leakage Power in the Presence of Process Variations (Abstract is attached)

Abstract: With the increasing importance of run-time leakage power dissipation (55% of the total power), its accurate estimation not only as a function of input vectors but also as a function of process parameters has become a necessity. In this work we address the problem of accurately estimating the maximum run-time leakage power bound in the presence of process variations such as channel length, threshold voltage, gate oxide thickness, doping concentration and gate width. Both sub-threshold and gate leakage current are considered. We propose a heuristic approach to determine the vector
that causes the maximum leakage power under the influence of process variations. This maximum leakage causing vector is then used to estimate the lognormal distribution of the total leakage current of the circuit by summing up the lognormal leakage current distributions of the individual standard cells at their respective input levels. The proposed method has been effective in accurately estimating the PDF, mean and standard deviations of the total leakage current distribution of ISCAS85 benchmark circuits and the average errors when compared with exhaustive random vector testing for mean and standard deviation are 5.84% and 3.5% respectively.


3. Name: Kiran Byadarhaly, Mithun Perdoor, Suresh Vasa
Advisors: Dr.Ali Minai, Dr.Emmanuel Fernandez
Department: Electrical and Computer Engineering
Research Area: Neural model for motor control

Title: Learning Population Coded Sequences

Abstract: Motor control for actions such as writing and drawing involves a hierarchy of processes mediated by several cortical and subcortical regions. In particular, the sequential structure of complex actions seems to be learned at an abstract “cognitive" level in several regions of the frontal cortex, independent of the control of the immediate effectors by the motor system. At this level, actions are represented in terms of kinematic parameters - especially direction of end effector movement - and encoded using population codes. Muscle force signals are generated from this representation by downstream systems in the motor cortex and the spinal cord.

In this poster, we consider the problem of learning population-coded kinematic sequences in an abstract neural network model of the medial frontal cortex. For concreteness, the sequences are represented as line drawings in a two-dimensional workspace. Learning such sequences presents several challenges because of the internal complexity of the individual sequences and extensive overlap between sequences. We show that our model is capable of learning multiple sequences with complex structure and very high cross-sequence similarity.


4. Name: Aravind Ranganathan
Department: CS
Advisor: Dr. Kenneth Berman

Title: Efficient Data Gather in Wireless Sensor Networks

Abstract: Wireless Sensor Networks (WSN) have become popular owing to their wide range of applications such as battlefield surveillance, micro-surgery, precision agriculture, habitat monitoring, disaster recovery, and home and office automation. WSNs consist of a number of low-power sensor nodes randomly deployed over the area of study and have one or more high power sink nodes that accumulates the sensed data and manages the network. Data gather is one of the fundamental operations of a WSN as all sensed data is routed from the source nodes to the sink. We have developed efficient routing protocols for data gather in a WSN by utilizing dynamic network structures to maximize the network lifetime by means of load balancing the sensor nodes. Although the WSN architecture usually imposes restrictions on the network topology, utilizing dynamic network structures allows for better load-balancing than could be achieved by any particular static structure. Our preliminary simulations have established that our routing protocols perform better when compared with other existing data gather protocols used in real-world testbeds and sensor network applications. We are currently implementing the protocols in MoteLab, a real world sensor network testbed developed at the Harvard University.


5. Name: Laxmi R Iyer and Divyachapan Padur
Research Area: Intelligent Systems/Complex Systems Modeling
Advisor: Dr. Ali Minai

Title: Connectionist Models of Individual and Group Brain Storming

Abstract: The generation of ideas is a characteristic of human cognition, and understanding the mechanisms underlying this process is important from both theoretical and practical standpoints. In this poster, we present preliminary computational models for the generation of ideas by individuals and groups.

In the individual model, ideas are modeled as conceptual combinations, i.e., juxtapositions of elementary concepts. The quality of these ideas is determined by the context in which they are generated, and depends on whether they are admissible (i.e., make sense in the given context), useful, novel, etc. In familiar contexts, it is often sufficient to just recall previously generated ideas. This is termed exploitation. In novel contexts, ideas must be generated by exploration of the semantic space configured by experience. We present a biologically inspired neural network model whose natural dynamics searches for and generates ideas based on prior knowledge, the given context, and real-time evaluative feedback.

The group model uses a multi-agent approach, where each agent is represented by a dynamical neural network that is a simplified version of the individual model. The agents can embody different styles of thinking and different organizations of semantic information, representing the diversity found in typical human groups. They generate ideas through their internal dynamics and communicate them as cues to other agents. Various protocols for communication and cuing are investigated for this model.

The goal of both models is to elucidate the dynamics of the creative process, and to explore ways in which the quality of brainstorming in individuals and groups can be improved.


6. Name: Faris Alqadah
Department: Computer Science
Research Area: Data Mining
Advisor: Dr. Raj Bhatnagar

Title: Mining Maximally Banded Subspace Clusters in Binary Data

Abstract: A binary matrix is fully banded if both rows and columns can be permutated such that the non-zero entries exhibit a staircase pattern of overlapping rows. Originally studied in numerical analysis, the problem of discovering a banded structure in binary matrices has been shown to be relevant to data analysis. Previous work has focused on the algorithmic problem of computing how far a matrix is from being banded, and on finding a good submatrix of the original data that exhibits approximate bandedness. However, the previous research has approached the problem from an approximation point of view and solved the problem only for a fixed column permutation. Moreover, only one approximate submatrix is mined. In our work, we show how the banded matrix problem can be directly related to the previously studied data mining problems of subspace clustering and closed itemsets. Furthermore, we present an algorithm to discover k maximally banded submatrices by formulating the problem in terms of subspace clustering problem.


7. Name: Jung Hyun Jun
Department: Computer Science
Research Area: Wireless Networks
Advisor: Dr. Dharma Agrawal

Title : Optimum Detection Probability with Partially Controlled Random Deployment of Wireless Sensors with Mobile Base Stations

Abstract :We analyzed the problem of covering widely expanded field with wireless sensors where many of the known deployment and data aggregation methods become impractical. We deploy the wireless sensors in partially controlled manner such that they are randomly placed on the lines of grid and the mobile base stations like the UAVs could be used to collect the data from the wireless sensors. Our objective is to maximize the detection probability of an event without overly deploying the sensors on the field. We have defined the detection probability to be the product of probability of an event been sensed and that data being collected by an UAV. Under this model, we analytically obtain a relationship between the grid spacing and number of available UAVs which can maximize detection probability when two collaborative and independent strategies for UAVs and obtain some useful relationship in guiding design specification.


8. Name : Lei Deng
Department : ECE
Advisor: Dr. Ali Minai

Title: Machine learning methods for mining and modeling in genomics/proteomics

Abstract: Large-scale high-throughput genomic and proteomic data have been available with the development of new experimental technologies and they are coming more and more, however, it is very difficult for human to derive information from so many different types of data. Machine learning approaches have been used in many areas such as computer vision, search engines, medical diagnosis and marketing to automatically produce rules and patterns from data.  In our research, based on the proteomic data of P. aeruginosa, we implemented advanced algorithms such SVM and ANN to detect the important features of the essential genes and protein interaction pairs. In our results, some features are significant different between positive sets and negative sets, which also indicate the implicit mechanics of gene in the long evolution. Moreover, using these features we predict new essential genes and valuable interaction pairs. These genes and protein pairs will be candidate for the drug targets for the diseases caused by P. aeruginosa. On the other hand, the machine learning methods can also improve the experimental technologies by integrating expert data to reduce false rates.


9. Name: Minlu Zhang
Department: Computer Science
Advisors: Dr. Raj Bhatnagar, Dr. Long (Jason) Lu

Title: MultiNets: a Web server for integrative analysis of multiple networks from multiple datasets

Abstract: In the post-genomics era of computational biology, high-throughput experimental data and corresponding molecular network integration becomes one of the main themes. One challenge for current molecular network visualization and analysis tools is the automatic representation of complex relationships and corresponding integrative analysis among multiple datasets from possibly multiple data sources. As an initial attempt to address these issues, we have developed a Web server, MultiNets, to provide researchers with a set of tools to perform complex network integration and analysis with great ease. The system provides four main types of functionality: integration of heterogeneous datasets with pre-defined edge ontology for each type of interactions, network navigation and visualization, network characterization with statistics calculation, and network comparison with complex logic operations. MultiNets allows users to upload, integrate, analyze, visualize, retrieve, save and download molecular networks. We show the novelty and effectiveness of MultiNets in two case studies that might be difficult or inconvenient for currently available network tools. In case study 1, MultiNets performs a Naïve Bayes integration of five protein-protein interaction datasets to better predict physical protein interactions of RNA polymerase II. In case study 2, MultiNets discerns complex relationships among four human signaling pathways.


10. Name: Zhen Hu
Department: Computer Science

Title:Reverse KNN Methods Based Density Clustering Algorithm

Abstract: Density-based clustering algorithms have been studied during last decade but most of these algorithms rely significantly on pre-defined density values or related parameters. Performance of these algorithms is very sensitive to these parameters. Reverse K-NN based distance methods have been presented in literature but have not been used for clustering.
We present a clustering algorithm that incoporates reverse KNN based distances into clustering procedures and significantly improves the clustering of datasets with widely varying densities. We present the results of this algorithm, compare it to the other well-known algorithms and list the applictions for which our algorithm will be suitable and better than all other algorithms.


11. Name: Weiya Yue
Department : Computer Science

Title: Navigation in Unknown Environment

Abstract: This problem is mainly coming from robot's navigation in an unknown or changing environment. I.e., given a source and a destination in a map changing with time (or a set of sources and destinations), the robot initialized at source needs to go to the destination along a path with a weight as low as possible.  So the map can be abstracted as a weighted digraph and the problem is modeled as the navigation on this changing graph. Currently, the most successful algorithm for solving it is D* Lite, which is a dynamic, incremental search algorithm.  The improved performance of the D* Lite algorithm is largely due to updating terrain cost estimates rather than recalculating them between robot movements when a changing occurs. However, the D* Lite algorithm performs some recalculation every time a change in terrain is discovered. In this paper, it is shown that recalculation is often not necessary, particularly when several optimal solutions (shortest paths) exist, and an efficient test for determining this is presented.  These ideas are packaged in a modified version of D* Lite which called ID* Lite for Improved D* Lite.  We present experimental results that show the speedups possible for a variety of benchmarks.


12. Name: Jacob Wachtman and Ping Chen.
Advisor: Dr. P. Boolchand.
Department: Electrical and Computer Engineering

Molecular structure of the solid electrolyte (Ag2Se)x (AsSe)1-x bulk glasses. A potential material for phase change memory.

Titled material systems have attracted interest as active elements of memory devices. For this application, it is crucial to understand how their ionic conductivity evolves with solid electrolyte additive. As a first step towards this goal, here we address the issue of their molecular structure. AsSe, the base glass (x = 0) in the titled ternary, is an interesting example of a chalcogenide that is partially de-mixed into As4Se4 and As4Se3 molecules segregated from a connected AsSe network, with the latter determining glass network properties. Raman scattering reveals sharp modes of the Realgar molecules that are superimposed on broad modes coming from of the backbone. Upon Tg cycling virgin samples (as quenched melts), the concentration of de-mixed molecules decreases, suggesting that thermally induced polymerization occurs; molecules break up to form part of the connective tissue. Modulated DSC experiments reveal a broad exotherm near 140 oC in virgin samples, which becomes nearly extinct in Tg cycled samples. The exotherm may represent Realgar molecules nano-crystallizing as the temperature approaches Tg. Compositional trends in thermal parameters such as Tg(x), ΔCp(x), and the ΔHnr(x) as a function of Ag2Se content ‘x’ of the glasses will be reported.


13. Name: Kuheli Louha, Jung Hyun Jun, Talmai Oliveira
Department: CS
Advisor: Dharma P. Agrawal

Title: Exploring Load balancing in Heterogeneous Networks by Rate Distribution

Abstract: Heterogeneous wireless networks (HWN) are conceived with the idea of heterogeneity in which a mobile user will be able to simultaneously
connect to multiple wireless networks (e.g., WLAN, cellular, WMAN). It has been referred as a new frontier in the future wireless communications technology and there has been a growing interest on this topic. In this kind of network, similar traffic is distributed primarily by grouping through a particular Access Point (AP). In our work, we introduce an effective but none-cooperative traffic load balancing of different APs for maximizing expected throughput in a HWN. A single client is modelled with access to multiple APs of a HWN as a cascade of independent M/M/1 queues. The expected number of packets in the system is formulated as a convex optimization problem analyzed using a Lagrange Multiplier method. A recursive algorithm is used in distributing the traffic to different APs. Numerical analysis show improvement when optimally distributing the traffic when compared to traditional methods and extensive simulations demonstrate the effectiveness in case of multiple clients.


14. Name:   Mike Borowczak
Advisor: Dr. Ranga Vemuri
Department of Electrical and Computer Engineering

Title: Side Channel Attack Resistance Toolbox: A Foundation for Automated Design of Secure Hardware Devices

Abstract: Side channel attacks are a relatively new method (circa late 1990's) to determine some internal function of a device. In particular, side-channel attacks (such as side-channel differential power analysis attacks DPA) can be used to determine cryptographic keys stored within hardware devices. Recently researchers have broken a cryptographic algorithm (Keeloq(R)) used in many car key fobs and garage door openers. Based off of previously published work, we have begun the development of a C++ based toolbox for modeling and implementing side-channel attacks. While implementation details of previous DPA attacks on Keeloq are non-existant we show how our C++ implemenation perfoms faster and is more scalable than a Matlab/C++ flow.

While this research is in its foundational stages, and results are not novel,  we will showcase how the development of this toolbox will enable us to quickly analyze, develop, prototype and deploy more secure  hardware implementations. Our ultimate goal of is to create a new standard tool flow option/metric for automated designs - currently power, size, speed etc are metrics of standard tool flows - we wish to  introduce Side-Channel Attack Resistance as a metric.


15. Name: Kandasamy Vignarooban
Department: Electrical and Computer Engineering
Research Area: Oxide Glasses
Advisor: Professor Punit Boolchand

Title: Reactivity of Water with B2O3 Glass and its Consequences on Physical Properties of B2O3 Glass

Abstract: B2O3 glass is an essential component of industrial glasses and it is used as an additive in SiO2 based bulk glasses, fibers and thin films for a variety of applications. But it is also hygroscopic and presence of water, most likely, plays a role in altering the physical behavior of the glass including aging. In this work, samples of Aesar Puratronic B2O3 were vacuum (10 -6 Torr) melted in a Pt crucible at 520°C for 3 days and slow cooled to room temperature to obtain a glass. All sample manipulations were performed in a N 2 gas purged glove box. Tg of the sample were established from the reversing heat flow scan in an mDSC experiment, and gave a value of Tg (mDSC) = 308 (1)°C. A traditional DSC experiment, using a scan rate of 10°C/min, gave a value of Tg (DSC) = 309(2)°C. Our Tg (DSC) values are at least 10°C higher than previous reports 1 using the same scan rate. Vibrational features in IR reflectance in the 1200-1600 cm -1 range, and in the 3200-3600 cm -1 range (free and bonded water) evolve as transparent platelets are exposed to laboratory environment, providing evidence for water reactivity of dry samples. Raman scattering 2 results for wet sample shows a mode at 881 cm -1 which is related to the Boric acid [B(OH) 3 ] . We confirm 1 density of dry samples (1.805 (4) gms/cm 3 ) to be somewhat less than wet ones(1.815(4) gms/cm 3 ). These experiments all suggest that water reacts with B 2 O 3 altering its physical properties.

1 Ramos et al. JNCS 221, 170 (1997)
2 F. Galeener et al. 22, 3983 (1980)


16. Name: Annie Avakian, Jon Nafziger, and Amayika Panda 
Advisor: Dr. Ranga Vemuri 
Department: ECE

Title: A Reconfigurable Hybrid Architecture for Multicore Processors 
 
Abstract:  According to David House's extension of Moore's Law, computing power demands double approximately every 20 months.  As the industry continuously reacts to meet this growing demand, new and novel ideas must be explored as a means of satisfying this need.  Traditionally this has been met by increasing the clock speed of individual processors.  Unfortunately, the diminishing returns in increasing processing speed after passing the 3 Ghz plateau have forced developed to find alternatives.  This has lead to a new trend increasing the total number of cores in a single processor.  In September of 2006, Intel announced the development of a single processor design containing eighty total cores.  While simply increasing the total number of cores on a chip is a simple task, connecting them together to provide a harmonious system is proving to be among the most critical design tasks.  Existing designs simplify this need by allowing for different cores to communicate with each other using a shared bus. Each core maintains a unique L1 cache while all cores share a single L2 cache. However experiments have shown that the communication delay between the L2 cache and the individual cores increases significantly with as the number of cores increases. Therefore this is not a viable method of developing a system with more than a handful of cores. An alternative receiving extensive research is the idea of a Network-on-Chip (NoC).  In this design the cores are connected to routers and communication between cores is done using protocols similar to a computer network. A distributed L2 cache is used and is shared among all the cores. But as the number of cores increases, network delays will become unacceptable as well. Therefore we propose having a Hybrid Architecture where between 4 and 8 cores are connected to a each bus, and these buses are connected to the routers. The routers are then finally connected as a mesh network. Preliminary results show that the hybrid method significantly reduces wait time when accessing L2 caches. Furthermore, we propose having a reconfigurable architecture where the number of cores connected together to a single bus is variable such that the operating system controls the configuration based upon system process demands.


Call for abstracts

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All graduate students in the EE, CE and CS departments are welcome to submit an entry to the competition. The poster should pertain to your research interests and/or be on any of the research areas of the ECE or CS Departments.

Submit a 200 word abstract in text, word or PDF formats to gsaposter@ececs.uc.edu (include the words "ECECS Poster Competition" in the subject line). The abstract should clearly indicate the problem addressed and the proposed solutions. The deadline for submitting abstracts is March 27, 2009  April 3, 2009April 10, 2009. Early submissions have an increased chance of availing the student grants.

Prizes:

All participants will receive participation certificates. In addition, we have cash prizes for the top three winners:

Highlights:

Poster competition participants enjoy the following benefits:

Student Grant Eligibility and Rules:

  1. Abstracts MUST be submitted before the specified deadline.
  2. The submission email should have the following information:
    • Name
    • Department
    • M# (UCID)
    • Email
    • Research Area
    • Student Grant Requested? (Yes / No)
    • Poster Title and Abstract
  3. The original receipts for the poster printing charges must be available.
  4. The number of student grants is limited.  Abstracts will be reviewed and accepted abstracts will be given the grant on a first come basis.  Only one grant will be available per poster. 

Please contact the ECE or CS GSA or email gsaposter@ececs.uc.edu for any questions.  

Important Dates

Do make the most use of this opportunity and submit your abstracts at the earliest. Abstracts must be 200 words or less and must be emailed to gsaposter@ececs.uc.edu

Update (4/5/09):

1. Feedback and Notification of Acceptance:

Since the Poster Abstract Acceptance deadline has been extended, notification of selected abstracts along with the feedback will be sent to the participants within 2 - 3 days of submission. If you have already submitted your abstracts you should be receiving the notifications shortly.

2. Additional Incentive to participate:

As additional incentive to participate in the Poster Competition, professor Marc Cahay has pledged to give the winner another $250 as long as he/she presents a paper in a future conference! See below for more info (from Prof. Cahay's email dated 4/2/09):

Dear All:
As an incentive to more submissions, I pledge to organize a small internal competition where the students would make double use of their presentation. A memorial fund was set in the memory of my wife Maureen in the college. The winner of the competition would get a check for $250 should he/she presents a paper at a conference to be organized in the near future. The rules for the competition will be set soon but I hope this can trigger more interest from our graduate students,
Get those abstracts flowing. Records are always made to be broken and 22 is my favorite number,. Let's go for it

Thank you for your consideration.

M.Cahay