Faculty Research

Software Analytics, Wireless Networks, Accountability and Privacy, Modeling and Simulation

Data, models, and tools for robust systems and software

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Modeling and Analysis of Software and Networked Systems: The ongoing research is a multi-pronged approach for engineering large software and networked systems. Analyzing how developers interact with IDEs allows us to investigate how to predict development activities and how to improve these productivity tools. Observing software changes in software projects provides us opportunity not only to discover software architecture and common bugs, but also to suggest coding solutions. Examining system and network logs is an important means to understanding large and complex software and network systems, which in turn leads to solutions to improving these systems, such as removing  performance bugs. Last, but not least, security is a cross-cutting concern in software and system design and implementation. For this, the interest lies in accountability and privacy—while preventive measures such as access control are critical to protect systems, software, and data, they do prevent misuse of these in the face of prevalent data collection and information flow. Students are welcome to contact the faculty for opportunities to take part in the research that provides ample experience in deepening learning and applying skills and knowledge in programming, data structure and algorithms, systems and networks, security and privacy, probability and statics, and machine learning.

Algorithms, Complexity, Constraint Solving, Search in A.I., Natural Language Processing

CT of a patient obtained from Christiana Hospital in Delaware. We colored some portions to show automatic segmentation. We later automatically segmented the liver tumor on the upper right.

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My research focuses on areas of computer science with a significant mathematical content. In the past I have worked on applications to robotics, medical imaging, constraint programming, and complexity theory. The medical imaging research resulted in a U.S. Patent. Our system allows the semi-automatic segmentation of CT and MRI, for example, in isolating soft tissue tumors. In the last several years I have been working in several areas. In Artificial Intelligence we have been working on two threads. The first thread involves developing search heuristics for difficult (NP-complete) constraint problems, an application that is of great importance in many areas, particularly in operations research problems for industry. We have developed new search heuristics that outperform state of the art software on difficult instances of a class of NP-complete problems. In the second thread we have been developing techniques in natural language processing to help classify text documents, of particular importance in the world of Big Data. In the second area we have worked on randomized graph search and developed a tool to measure the time such a search will likely take, with applications to Monte Carlo methods, an important technique in scientific computing. Our analysis also has applications to complexity theory, which characterizes the inherent difficulty of classes of computational problems. Finally, we continued work on pure complexity theory.

Algorithms, Boolean Functions, Serious Games

Code Control (game to teach introductory programming, in development)

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We pursue two independent areas of research. In one, we are interested in devising algorithms for problems related to problems in machine learning; for example, algorithms for minimizing the test-time budget when learning in the presence of attribute costs. In this line of research, we have devised approximation algorithms and structural results for a broad range of Boolean function classes and continue to investigate this topic through a combination of theoretical analysis and experiments.

In a completely separate line of research, we are investigating the use of serious educational games to help teach topics in computer science education (e.g., introductory programming and cybersecurity). We aim to create games that are fun and engaging, and help students learn.

Spoken Language Processing, Natural Language Processing, Speaker States and Traits, Deep Learning, Dialogue

Figure: Silhouette scores for k-means clustering for 2 ≤ k ≤ 40 (a) and 3D projection based on first three principal components (b) of 2433 SBC sessions in 18D space by entrainment measures.

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Our lab is working on various research projects associated with automatic speaker state and trait recognition from speech and language, such as deception detection, personality recognition, prosodic modeling for sarcasm detection, nativeness detection, and influence detection. We are interested in answering questions about how multiple modalities and multiple tasks can be implemented together to improve recognition.

We are also working on learning robust and integrated models of entrainment in multiple modalities, to improve conversation analysis and to create more natural and trust-invoking virtual conversational agents.

Logic, Game Theory, Social Software

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I am currently working on several projects.

• Logic without language (talk given at Rutgers in October and  given in absentia, by Dr. Ramanujam, at IIT in New Delhi). Parikh, Rohit. “Logic Without Language.” Indian Conference on Logic and Its Applications. Springer, Berlin, Heidelberg, 2019.
• Why do we speak? An inquiry into the game theoretic aspects of communication (A talk given at MOL: Mathematics of Language, in London, in 2017).
• When are groups individuals? A talk given at Tufts University, Social Ontology Conference August 2018. Work is continuing.

Relational Databases, Intelligent Agents, Scientific Applications, Information Technology

Agent at work

My research spans two realms—science and business. One area involves the design and development of relational databases to support scientific applications, such as studies in neuroscience, to link external meta-data garnered from human and animal experiments into a relational database to enhance research. A second area relates to my past experience in the business world where I seek to employ techniques of information technology, particularly intelligent agents, to enhance business functionality.

Algorithms, Pattern Matching, Compression

Strand of DNA

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We develop algorithms (and software) for searching for regularities in texts. We search for tandem repeats in DNA sequences, where a tandem repeat is defined as some pattern repeated contiguously. Tandem repeats in DNA sequences have been shown to be related to numerous hereditary diseases, yet their origin and function are still not well-understood. We also search for patterns and repetitions in two-dimensional texts, such as satellite images, as well as in compressed texts. We examine palindromes, which are a form of a repetition, where the second occurrence appears in reverse. Searching for an identical match is often not practical, hence, we develop algorithms that admit a certain level of fuzziness in the match. We study both the Hamming distance and edit distance with regards to repetitions and palindromes in strings as well as matrices. The goal is to optimize the time and space complexity of the algorithms.

Category Theory; Theoretical Computer Science

Published and forthcoming textbooks

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My research centers around three interconnected areas:

• Category Theory. This formalism easily describes relationships and processes between structures. Category Theory works for many different types of relationships, processes, and structures. The generality of Category Theory is used to make connections between various seemingly disparate areas. I am currently writing a textbook for Category Theory that stresses the connections between different areas. The book is tentatively titled Monoidal Categories: A Unifying Concept in Mathematics, Physics, and Computing.
• Theoretical Computer Science. In particular, I work with
  • Complexity Theory, which measures the complexity of procedures;
  • Shannon’s Information Theory, which measures how structures are described; and
  • Kolmogorov Complexity Theory, which measures how structures are described through processes.

  I am currently trying to understand categorical structures using these various measures of complexity and information.

• Foundations of Quantum Mechanics. I study the relationship of Quantum Mechanics with information and information processing (Quantum Computing.) I am currently trying to understand quantum randomness and how it relates to these various measures of complexity and information.

Programming Languages, Constraint Programming, Logic Programming, Combinatorial Search, Machine Learning, Probabilistic Reasoning

Picat website

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My research group is interested in programming languages, algorithms, and implementation techniques for combinatorial search and optimization problems. Recent projects include:

• Investigating algorithms for translating simple declarative planning models into efficient models
• Studying efficient encoding algorithms and optimization techniques for compiling high-level constraints into SAT
• Integrating machine learning and reasoning algorithms for AI applications.

Many algorithms and implementation techniques have been incorporated into the Picat system, and many more need to be explored.