Ubiquitous Networking Laboratory (UbiNET Lab)

The process of spectrum measurement involves three key steps: (i) spectrum sensing, (ii) data management and (iii) spectrum characterization. The goal of this project is to design algorithms for lightweight, real-time and unsupervised collection (AirSWEEP), management (AirPRESS) and characterization (AirVIEW) of spectrum data to improve the learning outcomes of spectrum sensing. Our work bridges the gap between spectrum algorithms and infrastructures by formalizing and evaluating the effects of heterogeneous infrastructures on spectrum learning outcomes.

TxMiner is a spectrum analytics engine, for unsupervised detection of arbitrary transmitters without prior knowledge of transmitter characteristics. TxMiner leverages the phenomenon that fading of non-line-of-sight wireless signals follows a Rayleigh distribution, while noise follows a Gaussian distribution. Thus, the raw spectrum samples can be modeled as a mixture of Rayleigh and Gaussian distributions. Based on this observation we design a machine learning algorithm that extracts Rayleigh and Gaussian sub-populations from a given RF signal population.

This project designs a socio-technical framework in support of rural emergency preparedness and response. First, the project will develop a heterogeneous network architecture and corresponding protocols that leverage wide-area wireless backhaul over TV white spaces, WiFi and pocket-switching to provide (i) continuous communication to first responders and (ii) delay-tolerant information access to residents. In addition, the project will design a smartphone app which will support the collection of information from different sources and its exchange among first responders, government agencies and residents. Second, the mobility patterns and network availability collected will enable the development of a dynamic probabilistic community network model. Novel graph-theoretic algorithms will identify information-depleted sub-communities and inform optimal information dissemination strategies. Finally, the project will assess adoption and use of the technologies by various community members to maximize the benefits associated with timely, rich and high-quality information, disseminated through technological devices. The framework will be developed in collaboration with the Town of Thurman, NY and the Emergency Service Department in Warren County, NY.

The goal of this project is to design, develop, integrate and deploy an end-to-end system for real-time agricultural data collection, analytics and control. To this end, we employ fundamental knowledge in wide-area wireless networks, digital signal processing, machine learning and control, to design (i) robust control mechanisms for multi-sensor agricultural data collection and fusion, (ii) wide-area, heterogeneous wireless networks for ubiquitous farm connectivity, (iii) algorithms and models for farm data analytics that produce actionable information from the collected agricultural data, and (iv) novel control mechanisms forautonomous, proactive farming.

HybridCell allows coexistence and simultaneous use of commercial and locally-owned cellular networks. It enables low-cost services for local users and organizations, and can also complement commercial cellular networks’ functionality in rural areas by providing mobile data services.

We utilize large-scale real-world traces from cellular and Internet access networks in order to understand network performance and user behavior. We design solutions after careful consideration of actual communication needs in rural communities.

Kwiizya is a cellphone network technology that provides basic voice and text messaging in remote rural areas for free. In the summer of 2012 we deployed an instance of Kwiizya in the remote village of Macha, Zambia.

We develop long distance wireless solutions that utilize white spaces to bring connectivity to and within remote communities. My focus is on resource allocation that is informed by the channel quality as perceived by the communicating parties.

AirLab is designed to be a publicly accessible distributed infrastructure for wireless measurements. It will facilitate meaningful analysis of wireless networks and protocols, by providing consistent and comparable wireless traces. AirLab consists of multiple homogeneous measurement nodes deployed across various sites around the globe. Access to these measurement nodes is controlled by a control center, AirLab Central, located at UCSB. Researchers can schedule experiments on the measurement nodes, which would allow them to gather specific traces from the host networks. All the traces are uploaded to a central repository and are available to the public after sufficient anonymization to protect privacy of the site involved.

Evolutionary Optimization of Residual Neural Network Architectures for Modulation Classification.
Erma Perenda, Sreeraj Rajendran, Gerome Bovet, Sofie Pollin, and Mariya Zheleva.
IEEE Transactions on Cognitive Communications and Networking (IEEE TCCN).

Understanding Drivers and Challenges of Multi-Actor Collaborations at the Local Level.
Qianli Yuan, Karyn Doke, Mila Gasco-Hernandez, J. Ramon Gil-Garcia, Mariya Zheleva, and Petko Bogdanov.
Hawaii International Conference on System Sciences 2022 (HICSS 2022), Best paper nomination.

Improving Emergency Preparedness and Response in Rural Areas.
Karyn Doke, Habib Affinih, Qianli Yuan, Mila Gasco-Hernandez, J. Ramon Gil-Garcia, Petko Bogdanov, and Mariya Zheleva.
ACM SIGCAS Conference on Computing and Sustainable Societies (ACM COMPASS 2021).

CORE: Connectivity Optimization via REinforcement Learning in WANETs.
Alexander Gorovitz, Karyn Doke, Lin Zhang, Mariya Zheleva, and Petko Bogdanov.
IEEE International Conference on Sensing, Communication and Networking (IEEE SECON 2021).

MODELESS: MODulation rEcognition with LimitEd SuperviSion.
Wei Xiong, Petko Bogdanov, and Mariya Zheleva.
IEEE International Conference on Sensing, Communication and Networking (IEEE SECON 2021).

SYMMeTRy: Exploiting Self-Similarity for Under-Determined MIMO Modulation Recognition.
Wei Xiong, Lin Zhang, Maxwel McNeil, Petko Bogdanov, and Mariya Zheleva.
IEEE Transactions on Mobile Computing (IEEE TMC 2021).

Learning the unknown: Improving modulation classification performance in unseen scenarios.
Erma Perenda, Sreeraj Rajendran, Gerome Bovet, Sofie Pollin, and Mariya Zheleva.
IEEE International Conference on Computer Communications (IEEE INFOCOM 2021).

Understanding the Determinants of Adoption and Use of Information and Communication Technologies for Emergency Management: Proposing a Research Agenda based on Existing Academic Literature.
Qianli Yuan, Yenisel Gulatee, Mila Gasco-Hernandez, Mariya Zheleva, Petko Bogdanov, and J. Ramon Gil-Garcia.
Hawaii International Conference on System Sciences 2021 (HICSS 2021), Best paper nomination.

Exploiting Self-Similarity for Under-Determined MIMO Modulation Recognition.
Wei Xiong, Lin Zhang, Maxwel McNeil, Petko Bogdanov, and Mariya Zheleva.
IEEE International Conference on Computer Communications (IEEE INFOCOM 2020).

Protecting location privacy from untrusted wireless service providers.
Keen Sung, Brian Neil Levine, and Mariya Zheleva.
13th ACM Conference on Security and Privacy in Wireless and Mobile Networks (ACM WiSec'20).

Towards scalable zero-shot modulation recognition.
Wei Xiong, Petko Bogdanov, and Mariya Zheleva.
The 2020 IEEE 92nd Vehicular Technology Conference (IEEE VTC-Fall'20).

LinksIQ: Robust and Efficient Modulation Recognition with Imperfect Spectrum Scans.
Wei Xiong, Karyn Doke, Petko Bogdanov, and Mariya Zheleva.
arXiv preprint arXiv:2005.04149.

Supporting Resilience in Rural Emergency Preparedness and Response Through Improved Information Access.
Karyn Doke, Qianli Yuan, Mila Gasco-Hernandez, Megan Sutherland-Mitzer, J. Ramon Gil-Garcia, Petko Bogdanov, and Mariya Zheleva.
SIGMOBILE GetMobile: Mobile Computing and Communications, September 2020.

Robust and Efficient Modulation Recognition Based on Local Sequential IQ Features.
Wei Xiong, Petko Bogdanov, and Mariya Zheleva.
IEEE International Conference on Computer Communications (IEEE INFOCOM 2019).

Third-Party Cellular Congestion Detection and Augmentation.
Paul Schmitt, Daniel Iland, Mariya Zheleva, and Elizabeth Belding.
IEEE Transactions on Mobile Computing (IEEE TMC).

Towards a Socio-Technical Framework for Bridging the Digital Divide in Rural Emergency Preparedness and Response: Integrating User Adoption, Heterogeneous Wide Area Networks, and Advanced Data Science.
Mila Gasco-Hernandez, Mariya Zheleva, Petko Bogdanov, and J. Ramon Gil-Garcia.
Proceedings of the 20th Annual International Conference on Digital Government Research (dg.o 2019).

AirPRESS: Efficient Spectrum Summarization Using Compressed Spectrum Scans.
Mariya Zheleva, Timothy Larock, Paul Schmitt, and Petko Bogdanov.
IEEE International Symposium on Dynamic Spectrum Access Networks (IEEE DySPAN 2018).

AirVIEW: Unsupervised transmitter detection for next generation spectrum sensing.
Mariya Zheleva, Tim Larock, Paul Schmitt, and Petko Bogdanov.
IEEE International Conference on Computer Communications (IEEE INFOCOM 2018).

Smallholder agriculture in the information age: Limits and opportunities.
Mariya Zheleva, Petko Bogdanov, Daphney-Stravoula Zois, Wei Xiong, Ranveer Chandra, and Mark Kimball.
Proceedings of ACM Third Workshop on Computing within Limits (LIMITS 2017).

Enabling a Nationwide Radio Frequency Inventory Using the Spectrum Observatory.
Mariya Zheleva, Ranveer Chandra, Aakanksha Chowdhery, Paul Garnett, Anoop Gupta, Ashish Kapoor, and Matt Valerio.
IEEE Transactions on Mobile Computing (IEEE TMC).

Smart City Sensing and Communication Sub-Infrastructure.
M Habibzadeh, W Xiong, M Zheleva, EK Stern, BH Nussbaum, and T Soyata.
IEEE Midwest Symposium on Circuits and Systems, Boston, MA.

HybridCell: Cellular connectivity on the fringes with demand-driven local cells.
Paul Schmitt, Daniel Iland, Mariya Zheleva, and Elizabeth Belding.
IEEE International Conference on Computer Communications (IEEE INFOCOM 2016).

Phonehome: Robust extension of cellular coverage.
Paul Schmitt, Daniel Iland, Elizabeth Belding, and Mariya Zheleva.
2016 25th International Conference on Computer Communication and Networks (IEEE ICCCN 2016).

Internet bandwidth upgrade: implications on performance and usage in rural zambia.
Mariya Zheleva, Paul Schmitt, Morgan Vigil, and Elizabeth Belding.
Information Technologies and International Development (ITID) 11(2).

Power-Aware Relay Selection and Routing Scheme for Multi-Interface Sensor Networks.
Mariya Zheleva and HyungJune Lee.
International Journal of Computers Communications and Control (IJCCC) 10(3).

Txminer: Identifying transmitters in real-world spectrum measurements.
Mariya Zheleva, Ranveer Chandra, Aakanksha Chowdhery, Ashish Kapoor, and Paul Garnett.
2015 IEEE International Symposium on Dynamic Spectrum Access Networks (IEEE DySPAN 2015).

Villagelink: Wide-area wireless coverage.
Veljko Pejovic, David L Johnson, Mariya Zheleva, Elizabeth M Belding, and Albert Lysko.
2014 Sixth International Conference on Communication Systems and Networks (COMSNETS 2014).

Kwiizya: Local cellular network services in remote areas.
Mariya Zheleva, Arghyadip Paul, David L Johnson, and Elizabeth Belding.
Proceeding of the 11th annual international conference on Mobile systems, applications, and services (MobiSys 2013).

Bringing visibility to rural users in Cote d'Ivoire.
Mariya Zheleva, Paul Schmitt, Morgan Vigil, and Elizabeth Belding.
Proceedings of the Sixth International Conference on Information and Communications Technologies and Development: Notes-Volume 2 (ICTD 2013).

Community detection in cellular network traces.
Mariya Zheleva, Paul Schmitt, Morgan Vigil, and Elizabeth Belding.
Proceedings of the Sixth International Conference on Information and Communications Technologies and Development: Notes-Volume 2 (ICTD 2013).

The increased bandwidth fallacy: performance and usage in rural Zambia.
Mariya Zheleva, Paul Schmitt, Morgan Vigil, and Elizabeth Belding.
Proceedings of the 4th Annual Symposium on Computing for Development (ACM DEV4 2013).

The Bandwidth Divide: Obstacles to Efficient Broadband Adoption in Rural Sub-Saharan Africa.
Veljko Pejovic, David L Johnson, Mariya Zheleva, Elizabeth Belding, Lisa Parks, and Gertjan Stam.
International Journal of Communication (IJoC).

AirLab: consistency, fidelity and privacy in wireless measurements.
Vinod Kone, Mariya Zheleva, Mile Wittie, Ben Y Zhao, Elizabeth M Belding, Haitao Zheng, and Kevin Almeroth.
ACM SIGCOMM Computer Communication Review (ACM SIGCOMM CCR) 41(1).

Funded by NSF Award #2132700

Award Information:

Award number: 2132700
Duration: 9/21-9/26

Short Summary:

This award funds the establishment of the first national center for wireless spectrum research, SpectrumX. The vision for SpectrumX is to be an inclusive multidisciplinary and increasingly interdisciplinary center that applies convergence research and team science to promote coexistence among disparate use cases in the radio spectrum, particularly including “public good” use cases for science and defense. In particular, SpectrumX will pursue its initial research strategy in scientific receiver hardware with interference measurement and mitigation capabilities; instrumentation of the radio spectrum in terms of advanced sensing networks; collecting and sharing accurate regulatory, usage, and economic data; flexible use rights that align incentives with efficient outcomes; and distributed, data-rich, and cloud-ready system designs for more efficient spectrum management and utilization.

Mariya Zheleva, Key Personnel
Assistant Professor
Dept. of Computer Science
1215 Western Ave., UAB 418,
Albany, NY 12222
University at Albany, SUNY
PH: 518-437-4941
FX: 518-437-4949
Email: [email protected]
SII-Center Project website

Funded by NSF Award #1845858 

Award Information:

Award number: 1845858
Duration: 5/19-5/24

Short Summary:

A growing number of domains that drive economic growth and humanity’s well-being, including healthcare, emergency management and national defense, hinge on wireless network connectivity. This has created a market potential of $640.9 billion, which cannot be realized as existing networks operate at capacity. Despite this potential, only 8% of the radio spectrum is allocated to wireless communication technologies. This minimal allocation creates artificial scarcity of frequency resources, whereby popular bands are saturated, while others are under-utilized. In response, wireless technologies have begun to incorporate new hardware and software to boost their spectrum efficiency through opportunistic frequency reuse. While promising, this trajectory of innovation cannot be sustained unless we establish a framework for principled spectrum measurement and management that can embrace unforeseen network and sensor capabilities in support of future spectrum policy, policing and technology. This project develops a long-term, integrated program of research, education and outreach to (i) establish a scientific and technological framework for automated spectrum measurement in support of shared-spectrum access, and (ii) to train the next generation of wireless specialists at the intersection of networks, digital communications and machine learning. The project will work closely with industry and standardization efforts to ensure broader adoption.

Mariya Zheleva, PI
Assistant Professor
Dept. of Computer Science
1215 Western Ave., UAB 418,
Albany, NY 12222
University at Albany, SUNY
PH: 518-437-4941
FX: 518-437-4949
Email: [email protected]
CAREER Project website

Recently supported students:
Andrew Okoro, PhD
Timothy Warren, REU Fellow
Habib Affinnih, REU Fellow

Funded by NSF Award #1831547

Award Information:

Award number: 1831547
Duration: 9/18-9/22

Short Summary:

The goal of this project is to develop, implement, and systematically analyze a comprehensive framework and a multi-layer platform for timely information collection, integration, exchange and dissemination to support emergency preparedness and response (EPR) in rural communities. This goal will be met through three primary activities. First, the project will develop a heterogeneous network architecture and corresponding protocols that leverage wide-area wireless backhaul over TV white spaces, WiFi and pocket-switching to provide (i) continuous communication to first responders and (ii) delay-tolerant information access to residents. In addition, the project will design a smartphone app which will support the collection of information from different sources and its exchange among first responders, government agencies and residents. Second, the mobility patterns and network availability collected will enable the development of a dynamic probabilistic community network model. Novel graph-theoretic algorithms will identify information-depleted sub-communities and inform optimal information dissemination strategies. Finally, the project will assess adoption and use of the technologies by various community members to maximize the benefits associated with timely, rich and high-quality information, disseminated through technological devices. Continuous community engagement activities for data provisioning, app design, impact co-evaluation and path to sustainability of the project are key factors for success. The framework will be co-designed and piloted in collaboration with the Town of Thurman, NY. Transferability to the broader rural context will be assessed by engaging two additional rural communities in coordination with the AirBand initiative.

Mariya Zheleva, PI
Assistant Professor
Dept. of Computer Science
1215 Western Ave., UAB 418,
Albany, NY 12222
University at Albany, SUNY
PH: 518-437-4941
FX: 518-437-4949
Email: [email protected]
SCC Project website

Co-PIs:
Petko Bogdanov, Computer Science, UAlbany
Mila Gasco, Center for Technology and Government, UAlbany
Ramon Gil-Garcia, Center for Technology and Government, UAlbany

Recently supported students:
Vaasu Taneja, PhD
Karyn Doke, PhD
Omkar Kulkarni, PhD
Tony Comanzo, REU Fellow
Habib Affinnih, Undergraduate
Jason Viviano, Undergraduate
Ayman Salloum, Undergraduate
Matthew Jacobs, Undergraduate
Domenic Recchia, Undergraduate

Funded by NSF Award #1657476

Award Information:

Award number: 1657476
Duration: 2/17-2/20

Short Summary:

The current paradigm of exclusive spectrum allocation is creating artificial scarcity of spectrum resources that has a dramatic impact on network performance and user experience. Underutilized bands provide an opportunity for more efficient, shared spectrum access that has recently brought together policymakers, industry leaders and academic researchers to set an agenda for next-generation spectrum management. A critical enabler of such advances is deep understanding of spectrum use. This award will support research seeking to impact the scientific community, the policy domain and the public, by providing methods and informing system designs for efficient spectrum measurement and characterization, and informing the design of future mobile wireless networks and spectrum policy. Products from this research will be included in the PI’s undergraduate and graduate courses, demonstrating the positive policy and societal impact of computer science and promoting the discipline to diverse groups of students.

Mariya Zheleva, PI
Assistant Professor
Dept. of Computer Science
1215 Western Ave., UAB 418,
Albany, NY 12222
University at Albany, SUNY
PH: 518-437-4941
FX: 518-437-4949
Email: [email protected]

Recently supported students:
Wooseok Kim, PhD
Wei Xiong, PhD
Karyn Doke, PhD
Eman Shah, REU Fellow
Jason Viviano, REU Fellow

Funded by University at Albany, SUNY

Award Information:

Duration: 01/17-05/19

Short Summary:

This project employs fundamental knowledge in signal processing and propagation, machine learning, and large-scale measurement to devise fast and robust algorithms for adaptive spectrum sensing, spectrum data management, and scan characterization. In conjunction with novel algorithms, we will also explore the cost and mobility tradeoffs in sensing infrastructure to inform efficient end-to-end infrastructure design that minimizes cost while maximizing the learning outcomes of spectrum sensing. The proposed research will bridge the gap between algorithm design and measurement infrastructures and will introduce the first holistic framework for spectrum measurement and characterization to facilitate next generation spectrum management.

Mariya Zheleva, PI
Assistant Professor
Dept. of Computer Science
1215 Western Ave., UAB 418,
Albany, NY 12222
University at Albany, SUNY
PH: 518-437-4941
FX: 518-437-4949
Email: [email protected]

Recently supported students:
Wei Xiong, PhD

Position Description

The UbiNET Lab at the University at Albany is looking to hire a full-time PhD student to carry out research on autonomous spectrum measurement and management in support of coexistence of disparate spectrum stakeholders. The position will provide full tuition coverage and a bi-weekly stipend to cover living expenses. The position is funded through the U.S. National Science Foundation award #2132700 SII-Center: SpectrumX – An NSF Spectrum Innovation Center.

The research will focus on the design of machine learning algorithms for spectrum cognizance, integration of these algorithm into next generation resource allocation mechanisms, and testing of the developed solutions in lab-scale testbeds and real-world dynamic spectrum access deployments. The work will be conducted in a collaborative and interdisciplinary research setting with strong background in wireless networks design, measurement and deployment, machine learning and data mining.

Candidates will be expected to perform research through a combination of analytical modeling, simulation and system-based experimentation. Candidates should be able to work independently and overcome a steep and interdisciplinary learning curve at the intersection of wireless networks, signal processing, digital signal communications and machine learning. It is thus, required that the candidates have excellent programming and system administration skills as well as substantial expertise in at least one of the core areas of the project: wireless networks, digital communications or machine learning. Candidates should have excellent English communication skills and team work abilities. Collaboration with academic and industrial partners is expected.

Eligibility and required qualifications

Candidates for this position must have completed a BS or MS degree in computer science, electrical and computer engineering or a closely related field prior to applying to our program.

Expected candidate qualifications:
- Expert in wireless networks and systems with working knowledge in machine learning OR
- Expert in machine learning with basic understanding of computer communication networks and willingness to overcome a learning curve in wireless networks.

Terms

Our preferred starting date is Fabruary 2022, however, this can be negotiated. Offers will be made based on the applicants qualifications to carry out the research. Full tuition coverage and a competitive stipend will be guaranteed for one year and will be renewed based on research performance.

How to Apply

In order to apply for this position, you need to send the following materials over email to [email protected] with a subject line “SpectrumX PhD: YourFirstName YourLastName”

• Cover letter with a description of all relevant experience to the announced position
• CV
• Unofficial transcript and copies of all diplomas to date
• Two reference contacts
• Copies or proofs of significant results, if any (e.g. theses, published papers, technical reports, presentations, etc.. )

Admission

Admission to the PhD program in Computer Science at UAlbany is contingent upon completion of entry exams (GRE and TOEFL) as well as the submission of a full application package. Completion of the PhD program is contingent upon the candidate meeting all departmental academic requirements.

Contact

For more information about the position or any questions about the application process contact Mariya Zheleva at [email protected].

About the Univeristy

Located in the capital city of New York State, the University at Albany is a leading Research-1 institution in the State University of New York system. Faculty at the Department of Computer Science conduct ground-breaking and interdisciplinary research that prepares students at all levels: undergraduate, masters and PhD, for the future job market. Our graduates secure positions in academia, industry and research laboratories.

The City of Albany provides vibrant and diverse socio-cultural experience and is a great gateway to pristine nature, such as the Adirondacks, the Finger Lakes and the Catskills and some of the most vibrant urban centers in the world, including New York, Boston and Montreal.

Position Description

The UbiNET Lab at the University at Albany is looking to hire a full-time PhD student to carry out research on autonomous spectrum measurement and management. The position will provide full tuition coverage and a bi-weekly stipend to cover living expenses.

The research will focus on the design of machine learning algorithms for spectrum cognizance and transmitter fingerprinting, development of adaptive spectrum sensing techniques, co-design of sensing and cognizance algorithms, and testing of the developed solutions in lab-scale testbeds as well as in several real-world dynamic spectrum access deployments. The work will be conducted in a collaborative and interdisciplinary research setting with strong background in wireless networks design, measurement and deployment, machine learning and data mining.

Candidates will be expected to perform research through a combination of analytical modeling, simulation and system-based experimentation. Candidates should be able to work independently and overcome a steep and interdisciplinary learning curve at the intersection of wireless networks, signal processing, digital signal communications and machine learning. It is thus, required that the candidates have excellent programming and system administration skills as well as substantial expertise in at least one of the core areas of the project: wireless networks, digital communications or machine learning. Candidates should have excellent English communication skills and team work abilities. Collaboration with academic and industrial partners is expected.

Eligibility and required qualifications

Candidates for this position must have completed a BS or MS degree in computer science, electrical and computer engineering or a closely related field prior to applying to our program.

Expected candidate qualifications:
- Expert in wireless networks and systems with working knowledge in machine learning OR
- Expert in machine learning with basic understanding of computer communication networks and willingness to overcome a learning curve in wireless networks.

Terms

Our preferred starting date is no later than January 2020, however, this can be negotiated. Offers will be made based on the applicants qualifications to carry out the research. Full tuition coverage and a competitive stipend will be guaranteed for one year and will be renewed based on research performance.

How to Apply

In order to apply for this position, you need to send the following materials over email to [email protected] with a subject line “PhD in spectrum measurement: YourFirstName YourLastName”

• Cover letter with a description of all relevant experience to the announced position
• CV
• Unofficial transcript and copies of all diplomas to date
• Two reference contacts
• Copies or proofs of significant results, if any (e.g. theses, published papers, technical reports, presentations, etc.. )

Admission

Admission to the PhD program in Computer Science at UAlbany is contingent upon completion of entry exams (GRE and TOEFL) as well as the submission of a full application package. Completion of the PhD program is contingent upon the candidate meeting all departmental academic requirements.

Contact

For more information about the position or any questions about the application process contact Mariya Zheleva at [email protected].

About the Univeristy

Located in the capital city of New York State, the University at Albany is a leading Research-1 institution in the State University of New York system. Faculty at the Department of Computer Science conduct ground-breaking and interdisciplinary research that prepares students at all levels: undergraduate, masters and PhD, for the future job market. Our graduates secure positions in academia, industry and research laboratories.

The City of Albany provides vibrant and diverse socio-cultural experience and is a great gateway to pristine nature, such as the Adirondacks, the Finger Lakes and the Catskills and some of the most vibrant urban centers in the world, including New York, Boston and Montreal.

The UbiNET Lab is looking for self-motivated PhD, MS and undergraduate students to join the lab. To apply, send the following information to [email protected] with subject line “Research open rank: YourFirstName YourLastName”:

• Cover letter with a description of all relevant experience to the research conducted at UbiNET
• CV
• Unofficial transcript and copies of all diplomas to date
• Two reference contacts
• Copies or proofs of significant results, if any (e.g. theses, published papers, technical reports, presentations, etc.. )