UMBC CSEE Seminar

A Neural Circuit Deconvolution Approach to Study Motivated Behavior

Dr. Joseph Cheer
Associate Professor, Deptartment of Anatomy and Neurobiology
and Department of Psychiatry
School of Medicine, University of Maryland Baltimore

11:001am-12:00pm, Wednesday, 3 February 2016, ITE 325b

In order to examine relationships between subsecond dopamine signaling and nucleus accumbens (NAc) cell firing during reward-directed behaviors, the ideal experimental approach is to record postsynaptic neuronal firing from the same electrode used to measure dopamine release. We have demonstrated that these measurements are feasible using cylindrical carbon fiber electrodes that can voltammetrically detect the oxidation potential of dopamine and also measure single-units extracellularly or local field potentials (LFPs). Moreover, we have added iontophoresis barrels to the carbon-fiber microelectrode to allow localized, rapid drug delivery to examine the signal transduction utilized by postsynaptic neurons when dopamine release is detected. The drugs to be ejected out of the iontophoresis barrels are selected on the basis of effects of prior microinjections (such as dopamine receptor antagonists). Once a significant behavioral effect is observed following the microinjection, iontophoresis pipettes with the same compounds are loaded for ejection in other animals. Under these conditions ongoing behavior is unaltered allowing for a detailed neurobiological dissection of the particular microanatomical domain during specific times of the behavioral sequence. Finally we can now provide causality between the two simultaneously recorded measures, by applying the above mentioned to animals amenable to optogenetic interrogation of dopaminergic pathways. We will show that dopamine sculpts cue-related patterned neuronal activity as well as the power of the NAc LFP during reward seeking.

Dr. Joseph Cheer graduated from Universidad de los Andes (Bogota, Colombia) with a B.S in Biology and Mathematics in 1996. He joined the Laboratory of Neurobiology and Experimental Microsurgery at the Colombian Neurology Foundation where he worked for 1 year investigating CNS regeneration using oncogene-tranfected cells and sciatic nerve co-grafts in motor cortex-lesioned animals. Joe received his Ph.D from The University of Nottingham (Neuroscience Section of the School of Biomedical Sciences) under the direction of Profs Charles Marsden and Dave Kendall and Dr Rob Mason. Dr. Cheer’s graduate research focused on the behavioral and electrophysiological effects of cannabinoids.

Dr. Cheer’s first postdoc (2000-2002) was spent in Sam Deadwyler’s laboratory (Wake Forest University School of Medicine) where he conducted research on multiple single-unit electrophysiology in freely moving organisms. Joe joined Mark Wightman’s lab as a post doc in fall 2002 at the University of North Carolina (Chapel Hill). There, he established the use of a microelectrode that allows for the simultaneous measurement of single-unit activity and dopamine release via fast-scan cyclic voltammetry.

Dr. Cheer is currently a tenured associate professor at the University of Maryland School of Medicine, where he directs several NIH and private foundation-funded graduate and undergraduate projects related to several neurophysiological and neurochemical aspects of endogenous cannabinoid signaling in intact systems.

Hosts: Professors Fow-Sen Choa (Sorry, you need javascript to view this email address. ) and Alan T. Sherman (Sorry, you need javascript to view this email address. )

UMBC CSEE Seminar

A Neural Circuit Deconvolution Approach to Study Motivated Behavior

Dr. Joseph Cheer
Associate Professor, Deptartment of Anatomy and Neurobiology
and Department of Psychiatry
School of Medicine, University of Maryland Baltimore

11:001am-12:00pm, Wednesday, 3 February 2016, ITE 325b

In order to examine relationships between subsecond dopamine signaling and nucleus accumbens (NAc) cell firing during reward-directed behaviors, the ideal experimental approach is to record postsynaptic neuronal firing from the same electrode used to measure dopamine release. We have demonstrated that these measurements are feasible using cylindrical carbon fiber electrodes that can voltammetrically detect the oxidation potential of dopamine and also measure single-units extracellularly or local field potentials (LFPs). Moreover, we have added iontophoresis barrels to the carbon-fiber microelectrode to allow localized, rapid drug delivery to examine the signal transduction utilized by postsynaptic neurons when dopamine release is detected. The drugs to be ejected out of the iontophoresis barrels are selected on the basis of effects of prior microinjections (such as dopamine receptor antagonists). Once a significant behavioral effect is observed following the microinjection, iontophoresis pipettes with the same compounds are loaded for ejection in other animals. Under these conditions ongoing behavior is unaltered allowing for a detailed neurobiological dissection of the particular microanatomical domain during specific times of the behavioral sequence. Finally we can now provide causality between the two simultaneously recorded measures, by applying the above mentioned to animals amenable to optogenetic interrogation of dopaminergic pathways. We will show that dopamine sculpts cue-related patterned neuronal activity as well as the power of the NAc LFP during reward seeking.

Dr. Joseph Cheer graduated from Universidad de los Andes (Bogota, Colombia) with a B.S in Biology and Mathematics in 1996. He joined the Laboratory of Neurobiology and Experimental Microsurgery at the Colombian Neurology Foundation where he worked for 1 year investigating CNS regeneration using oncogene-tranfected cells and sciatic nerve co-grafts in motor cortex-lesioned animals. Joe received his Ph.D from The University of Nottingham (Neuroscience Section of the School of Biomedical Sciences) under the direction of Profs Charles Marsden and Dave Kendall and Dr Rob Mason. Dr. Cheer’s graduate research focused on the behavioral and electrophysiological effects of cannabinoids.

Dr. Cheer’s first postdoc (2000-2002) was spent in Sam Deadwyler’s laboratory (Wake Forest University School of Medicine) where he conducted research on multiple single-unit electrophysiology in freely moving organisms. Joe joined Mark Wightman’s lab as a post doc in fall 2002 at the University of North Carolina (Chapel Hill). There, he established the use of a microelectrode that allows for the simultaneous measurement of single-unit activity and dopamine release via fast-scan cyclic voltammetry.

Dr. Cheer is currently a tenured associate professor at the University of Maryland School of Medicine, where he directs several NIH and private foundation-funded graduate and undergraduate projects related to several neurophysiological and neurochemical aspects of endogenous cannabinoid signaling in intact systems.

Hosts: Professors Fow-Sen Choa (Sorry, you need javascript to view this email address. ) and Alan T. Sherman (Sorry, you need javascript to view this email address. )

Big Data/Data Science Programs at NSF

Chaitan Baru
Senior Advisor for Data Science, NSF CISE Directorate
10-11:00am Thursday 28 January 2016, ITE 459, UMBC
postponed

This talk will provide an overview of current programs and activities related to Big Data and Data Science at NSF, and also highlight NSF’s inter-agency engagements in this topic area. The talk will also discuss future directions for Data Science research, education, and infrastructure. Considering that Data Science is a rapidly emerging, evolving field and discipline, ample time will be provided for Q&A and discussions about where the field ought to be going, given what we know today.
Dr. Chaitan Baru is currently a senior advisor for data science in the Computer and Information Science and Engineering Directorate at the National Science Foundation. He is a Distinguished Scientist and Associate Director of Data Initiatives at the San Diego Supercomputer Center (SDSC), UC San Diego where he works on applied and applications-oriented research problems related to data management and data analytics.

Dr. Baru has participated in a number of “data cyberinfrastructure” initiatives, including as Principal Investigator of the OpenTopography project; Cyberinfrastructure Lead, Tropical Ecology, Assessment and Monitoring network; Co-Investigator of the Cyberinfrastructure for Comparative Effectiveness Research project; Member of the founding Senior Management Team of the National Ecologial Observatory Network and Co-PI of the NEON Cyberinfrastructure Testbed; Co-PI of the CUAHSI Hydrologic Information Systems; Director, NEES Cyberinfrastructure Center; PI/Project Director, Geosciences Network; and member of the How Much Information? project.

Baru leads the Advanced Cyberinfrastructure Development Group at SDSC and is also Director of the Center for Large-scale Data Systems research. Prior to joining SDSC in 1996, Baru was at IBM, where he led one of the development teams for DB2 Parallel Edition Version 1 and at the University of Michigan, where he served on the faculty of the EECS Department. He received his B.Tech in Electronics Engineering from the Indian Institute of Technology, Madras, and M.E. and Ph.D. in Electrical Engineering from the University of Florida, Gainesville.

Cyber Defense Lab
University of Maryland, Baltimore County

cMix: Anonymization by High-Performance Scalable Mixing

Farid Javani
Cyber Defense Lab, CSEE Dept., UMBC

11:15am-12:30pm Friday, 29 January 2016, ITE 231

cMix is a cryptographic protocol for mix networks that uses pre-computations of a group-homomorphic encryption function to avoid all real-time public-key operations by the senders, mix nodes, and receivers. Like other mix network protocols, cMix can enable an anonymity service that accepts inputs from senders and delivers them to an output buffer, in a way that the outputs are unlinkable to the inputs. cMix’s high-performance scalable architecture, which results from its unique pre-computation approach, makes it suitable for smartphone-to-smartphone use while maintaining full anonymity sets independently per round.

Each sender establishes a shared key separately with each of the mix nodes, which is used as a seed to a cryptographic pseudorandom number generator to generate a sequence of message keys. Each sender encrypts its input to cMix with modular multiplication by message keys. cMix works by replacing the message keys, which are not known in the pre-computation, in real time with a precomputed random value.

Our presentation includes a detailed specification of cMix and simulation-based security arguments. We also give performance analysis, both modeled and measured, of our working prototype currently running in the cloud.

cMix is the core technology underlying our larger PrivaTegrity system that allows smart devices to carry out a variety of applications anonymously (including sending and receiving chat messages), with little extra bandwidth or battery usage. This talk focuses on cMix.

Joint work with David Chaum (Voting Systems Institute), Aniket Kate (Purdue Univ.), Anna Krasnova (Radboud Univ.), Joeri de Ruiter (Univ. of Birmingham), Alan T. Sherman (UMBC).  See and recent articles in Wired and Fortune for discussion.

Favid Javani is a PhD student working with Dr. Sherman. He earned a MS from the Middle Eastern Technical University, Turkey, with a thesis on lattice-based cryptography.

Host: Alan T. Sherman, Sorry, you need javascript to view this email address.

Cyber Defense Lab
University of Maryland, Baltimore County

cMix: Anonymization by High-Performance Scalable Mixing

Farid Javani
Cyber Defense Lab, CSEE Dept., UMBC

11:15am-12:30pm Friday, 29 January 2016, ITE 231

cMix is a cryptographic protocol for mix networks that uses pre-computations of a group-homomorphic encryption function to avoid all real-time public-key operations by the senders, mix nodes, and receivers. Like other mix network protocols, cMix can enable an anonymity service that accepts inputs from senders and delivers them to an output buffer, in a way that the outputs are unlinkable to the inputs. cMix’s high-performance scalable architecture, which results from its unique pre-computation approach, makes it suitable for smartphone-to-smartphone use while maintaining full anonymity sets independently per round.

Each sender establishes a shared key separately with each of the mix nodes, which is used as a seed to a cryptographic pseudorandom number generator to generate a sequence of message keys. Each sender encrypts its input to cMix with modular multiplication by message keys. cMix works by replacing the message keys, which are not known in the pre-computation, in real time with a precomputed random value.

Our presentation includes a detailed specification of cMix and simulation-based security arguments. We also give performance analysis, both modeled and measured, of our working prototype currently running in the cloud.

cMix is the core technology underlying our larger PrivaTegrity system that allows smart devices to carry out a variety of applications anonymously (including sending and receiving chat messages), with little extra bandwidth or battery usage. This talk focuses on cMix.

Joint work with David Chaum (Voting Systems Institute), Aniket Kate (Purdue Univ.), Anna Krasnova (Radboud Univ.), Joeri de Ruiter (Univ. of Birmingham), Alan T. Sherman (UMBC).  See and recent articles in Wired and Fortune for discussion.

Favid Javani is a PhD student working with Dr. Sherman. He earned a MS from the Middle Eastern Technical University, Turkey, with a thesis on lattice-based cryptography.

Host: Alan T. Sherman, Sorry, you need javascript to view this email address.

Big Data/Data Science Programs at NSF

Chaitan Baru
Senior Advisor for Data Science, NSF CISE Directorate
10-11:00am Thursday 28 January 2016, ITE 459, UMBC
postponed

This talk will provide an overview of current programs and activities related to Big Data and Data Science at NSF, and also highlight NSF’s inter-agency engagements in this topic area. The talk will also discuss future directions for Data Science research, education, and infrastructure. Considering that Data Science is a rapidly emerging, evolving field and discipline, ample time will be provided for Q&A and discussions about where the field ought to be going, given what we know today.
Dr. Chaitan Baru is currently a senior advisor for data science in the Computer and Information Science and Engineering Directorate at the National Science Foundation. He is a Distinguished Scientist and Associate Director of Data Initiatives at the San Diego Supercomputer Center (SDSC), UC San Diego where he works on applied and applications-oriented research problems related to data management and data analytics.

Dr. Baru has participated in a number of “data cyberinfrastructure” initiatives, including as Principal Investigator of the OpenTopography project; Cyberinfrastructure Lead, Tropical Ecology, Assessment and Monitoring network; Co-Investigator of the Cyberinfrastructure for Comparative Effectiveness Research project; Member of the founding Senior Management Team of the National Ecologial Observatory Network and Co-PI of the NEON Cyberinfrastructure Testbed; Co-PI of the CUAHSI Hydrologic Information Systems; Director, NEES Cyberinfrastructure Center; PI/Project Director, Geosciences Network; and member of the How Much Information? project.

Baru leads the Advanced Cyberinfrastructure Development Group at SDSC and is also Director of the Center for Large-scale Data Systems research. Prior to joining SDSC in 1996, Baru was at IBM, where he led one of the development teams for DB2 Parallel Edition Version 1 and at the University of Michigan, where he served on the faculty of the EECS Department. He received his B.Tech in Electronics Engineering from the Indian Institute of Technology, Madras, and M.E. and Ph.D. in Electrical Engineering from the University of Florida, Gainesville.

The UMBC Cyber Defense Lab presents

Engineering Notes on Homomorphic
Private Information Retrieval

Russ Fink
Johns Hopkins University Applied Physics Lab

11:15am-12:30pm, Friday, 4 December 4 2015, ITE 231

For two years, we have been investigating applications of private information retrieval (PIR) using the additive homomorphic scheme designed by Paillier that forms the basis of a space efficient PIR system by Ostrovsky, Skeith, and Bethencourt. We have implemented a working prototype and gained some insights about the technique, and identified improvements to make it practical to real-world privacy problems. I will present an overview of the technique, present a real world use case, and discuss our technical contributions and ongoing challenges.

Dr. Russ Fink is Chief Engineer of the Enterprise Security Group at APL. He earned the PhD from UMBC with a dissertation on applying trustworthy computing to voting.

Host: Alan T. Sherman, Sorry, you need javascript to view this email address.

The UMBC Cyber Defense Lab presents

Engineering Notes on Homomorphic
Private Information Retrieval

Russ Fink
Johns Hopkins University Applied Physics Lab

11:15am-12:30pm, Friday, 4 December 4 2015, ITE 231

For two years, we have been investigating applications of private information retrieval (PIR) using the additive homomorphic scheme designed by Paillier that forms the basis of a space efficient PIR system by Ostrovsky, Skeith, and Bethencourt. We have implemented a working prototype and gained some insights about the technique, and identified improvements to make it practical to real-world privacy problems. I will present an overview of the technique, present a real world use case, and discuss our technical contributions and ongoing challenges.

Dr. Russ Fink is Chief Engineer of the Enterprise Security Group at APL. He earned the PhD from UMBC with a dissertation on applying trustworthy computing to voting.

Host: Alan T. Sherman, Sorry, you need javascript to view this email address.

The UMBC CSEE Seminar Series Presents

Addressing Energy and Big Data
Challenges in Microgrids

Prof. Ting Zhu, UMBC

1-2pm Friday, Dec 4, 2015, ITE 325B

Buildings account for over 75% of the electricity consumption in the United States. To reduce electricity usage and peak demand, many utility companies are introducing market-based time-of-use (TOU) pricing models. In parallel, government programs that increase the fraction of renewable energy are incentivizing residential consumers to adopt on-site renewables and energy storage. Connecting on-site renewables and energy storage between homes forms a sustainable microgrid that is capable of generating, storing, and sharing electricity to balance local generation and consumption in residential areas. In this talk, I will present two pieces of our work in this area. The first work targets at minimizing the electricity cost from a utility company for a microgrid under different market-based TOU pricing models. This work is selected as the best paper runners up at BuildSys 2014. The goals of the second work are real-time energy data gathering, compression, and recovery based on unique features in the energy consumption patterns. In the end of the talk, I will also briefly introduce some of my latest work in indoor localization, networking, and smart health.

Ting Zhu is an assistant professor in the CSEE at UMBC. He received the Computing Innovation Fellowship in 2010. His papers have been selected in the best paper award finalist in multiple conferences (i.e., SenSys ’10, e-Energy ’13, and BuildSys ’14). He has a broad research interest in areas such as internet of things, energy, networking, systems, big data, and security. He is looking for undergraduate, Master and PhD students to work in the above areas.

Hosts: Professors Fow-Sen Choa (Sorry, you need javascript to view this email address. ) and Alan T. Sherman (Sorry, you need javascript to view this email address. )

The UMBC CSEE Seminar Series Presents

Addressing Energy and Big Data
Challenges in Microgrids

Prof. Ting Zhu, UMBC

1-2pm Friday, Dec 4, 2015, ITE 325B

Buildings account for over 75% of the electricity consumption in the United States. To reduce electricity usage and peak demand, many utility companies are introducing market-based time-of-use (TOU) pricing models. In parallel, government programs that increase the fraction of renewable energy are incentivizing residential consumers to adopt on-site renewables and energy storage. Connecting on-site renewables and energy storage between homes forms a sustainable microgrid that is capable of generating, storing, and sharing electricity to balance local generation and consumption in residential areas. In this talk, I will present two pieces of our work in this area. The first work targets at minimizing the electricity cost from a utility company for a microgrid under different market-based TOU pricing models. This work is selected as the best paper runners up at BuildSys 2014. The goals of the second work are real-time energy data gathering, compression, and recovery based on unique features in the energy consumption patterns. In the end of the talk, I will also briefly introduce some of my latest work in indoor localization, networking, and smart health.

Ting Zhu is an assistant professor in the CSEE at UMBC. He received the Computing Innovation Fellowship in 2010. His papers have been selected in the best paper award finalist in multiple conferences (i.e., SenSys ’10, e-Energy ’13, and BuildSys ’14). He has a broad research interest in areas such as internet of things, energy, networking, systems, big data, and security. He is looking for undergraduate, Master and PhD students to work in the above areas.

Hosts: Professors Fow-Sen Choa (Sorry, you need javascript to view this email address. ) and Alan T. Sherman (Sorry, you need javascript to view this email address. )