Alex Doboli, Ph.D.

Professor
Department of Electrical and Computer Engineering
Stony Brook University, State University of New York
Stony Brook, NY, 11794-2350
Phone: ++1 631-632-1611
Fax: ++1 631-632-8494
Email: alex.doboli@stonybrook.edu

Alex Doboli received his engineering degree in Computer Science and Engineering (valedictorian (sef de promotie, Diploma of Merit)) from "Politehnica" University Timisoara, Romania in 1990. He was awarded the "Doctor" degree in Computers from "Politehnica" University Timisoara in 1997. In 2000, he received the Ph.D. degree in Computer Engineering from University of Cincinnati, Cincinnati, OH. He was a junior faculty (asistent universitar) at "Politehnica" University Timisoara, Department of Computer Science and Engineering between 1991-1997. In Fall 2000 he joined the Department of Electrical and Computer Engineering, where he is now a Professor. Dr. Doboli's research has been over the years, first in Electronic Design Automation (EDA) of analog and mixed-domain systems, and Cyber-Physical and embedded systems; and more recently on methodologies and tools for design innovation and data-intensive design, and Cyber-Social systems and Human-inspired Machine Learning. He has published over 160 papers in peer-reviewed journals and conference proceedings, and has advised 16 Ph.D. thesis (graduated). He co-authored with Dr. E. Currie the textbook ``Introduction to Mixed-Signal, Embeddd Design'', Springer, 2010. He received the IBM Partnership Award (2001) and the ``Traian Lalescu'' Award (for best student in mathematics) from ``Politehnica'' University Timisoara (1987). Dr. A. Doboli was an Associate Editor for Integration, the VLSI Journal (Elsevier). He is an ABET Program Evaluator. He is a Senior IEEE Member, a Member of SigmaXi, Upsilon Pi Epsilon and Tau Beta Pi. His h-index is 25 and i10-index is 57 (Oct. 2021). He was the Vice-Chair of the IEEE Long Island Circuits and Systems Society.


News

Research interests

Mixed-Domain Embedded Systems Laboratory

Recent publications

Publications

News

Teaching

Professional Service

Presentations and Talks

Recent readings

News

  • Accepted for publication: A. Doboli, S. Doboli, ``A Novel Learning and Response Generating Agent-based Model for Symbolic - Numeric Knowledge Modeling and Combination'', IEEE Symposium Series on Computational Intelligence, Oct. 2021.

  • Ryan Duke defended his PhD prelim with the thesis "diaLogic Interaction-Focused Speech & Emotion Detection". PhD committee: A. Doboli (SBU), S. Hong (SBU), W. Tang (SBU), P. Milder (SBU) and M. Lerner (SBU) (Sept 2021).

  • Published: A., Doboli, S., Doboli, ``A novel agent-based, evolutionary model for expressing the dynamics of creative open-problem solving in small groups'', Applied Intelligence, 51, 2094-2127, 2021.

  • Published: X. Liu, A. Doboli, S. Doboli, ``Bottom-Up Modeling of Design Knowledge Evolution: Application to Circuit Design Community Characterization'', IEEE Transactions on Computational Social Systems, vol. 8, no. 3, 689-703, June 2021.

  • Published: R. Duke and A. Doboli, ``diaLogic: Interaction-Focused Speaker Diarization'', IEEE International Systems Conference (SysCon), 2021, pp. 1-8.

  • A. Doboli, C. D'Agostino, ``Modern Algorithmic Trends in Analog Circuit Modeling'', invited book chapter, in G. Dundar (editor), ``Modelling Methodologies in Analogue Integrated Circuit Design'', Institution of Engineering & Technology (IET), 2020.


Research interests

His research interests include all aspects of CAD for mixed-domain systems and networks of systems, including specification, modeling, synthesis, and optimization of analog and mixed-signal (analog-digital) circuits, Cyber-Physical and embedded (hardware-software) systems, Systems-on-Chip (SoCs) and SoC networks. Recently, his work has been focusing on methodologies for innovation in electronic design.

  • Human-inspired Machine Learning: modeling of dialog, modeling of problem solving, modeling of cognitive activities, modeling of emotions, modeling of social interactions, and knowledge representations.

  • Innovation and creativity in electronic design: metrics to capture design innovation and creativity, innovation-oriented design methodologies, design taxonomies and automated design for innovation.

  • EDA for analog and mixed-signal systems: system sizing through optimization, automated topology synthesis, synthesis from VHDL-AMS specifications, circuit modeling and simulation, and methodologies for reconfigurable ADCs.

  • Cyber-Physical and embedded systems: specification and optimization of massively distributed systems, data modeling for massively distributed systems, centralized and decentralized decision making in distributed systems, hardware/software co-design for resource constrained systems, stochastic and heuristic methods for on-line architecture adaptation, sensing design in massively distributed and dependable systems.


Mixed-Domain Embedded Systems Laboratory

  • Current student members: R. Duke (Ph.D. student).

  • Lab Alumni: C. Curiac (M.Sc. 2021, Technical University Munich), X. Liu (Ph.D. 2017, Linkedin), H. Li (Ph.D. 2017, Facebook), F. Jiao (Ph.D., Dec 2016, Marvell), A. Umbarkar (Ph.D., July 2014, IBM Austin), C. Ferent (Ph.D., Aug 2013, VJ Technologies), S. Kaghaz-Garan (M.S., Dec 2013) Y. Ji (M.S., Dec 2013, Google), A. Hussain (M.S., Dec 2012), V. Subramanian (Ph.D., Sept 2012, Carbon Design Inc.), M. Wang (Ph.D., Dec 2011, BNL), S. Kodasara (M.S., Dec 2010), M. Gilberti (Ph.D., Dec 2009, Motorolla), P. Sun (Ph.D., Dec 2009, IBM), Y. Zhao (Ph.D., May 2008, Techexcell), S. Kallakuri (Ph.D., Jun 2007), Y. Weng (M.S., 2008, PDF Solutions), Y. Wei (Ph.D., Feb 2007, Synopsys), J. Zhou (MS, Dec. 2006, DDC), H. Zhang (Ph.D., Dec 2005, Cadence), J. Gao (MS, Dec 2005, Marvell), H. Tang (Ph.D., July 2005, U Minnesota), N. Thepayasuwan (Ph.D., Nov 2004, Eastern Digital), V. Damle (MS, Dec 2003, Springer), R. Pai (MS, Dec 2003, Goldman Sachs).


 
Some Recent publications:
  • A., Doboli, S., Doboli, ``A novel agent-based, evolutionary model for expressing the dynamics of creative open-problem solving in small groups'', Applied Intelligence, 51, 2094-2127, 2021.

  • X. Liu, A. Doboli, S. Doboli, ``Bottom-Up Modeling of Design Knowledge Evolution: Application to Circuit Design Community Characterization'', IEEE Transactions on Computational Social Systems, vol. 8, no. 3, 689-703, June 2021.

  • A. Doboli, C. D'Agostino, ``Modern Algorithmic Trends in Analog Circuit Modeling'', invited book chapter, in G. Dundar (editor), ``Modelling Methodologies in Analogue Integrated Circuit Design'', Institution of Engineering & Technology (IET), 2020.

  • X. Liu, H. Li, A. Doboli, S. Doboli, ``Modeling and Extraction of Insight Information on the Evolution of Community-Level, Creative Problem Solving'', in P. Paulus and B. A. Nijstad (editors), In ``The Oxford Handbook of Group Creativity and Innovation'', The Oxford University Press, May 2019.

  • H, Li, X. Liu, F. Jiao, A, Doboli, S. Doboli, ``InnovA: A Cognitive Architecture for Computational Innovation through Robust Divergence and Its Application for Analog Circuit Design'', IEEE Transactions on CADICS, 37(10), 1943-1956, 2018.

Selected publications


Teaching

Undergrad: ESE 124: Programming Techniques for EE/CE (Summer)
Undergrad: ESE 366: Design using Mixed-Signal Programmable Systems-on-Chip (Spring)
Undergrad: ESE 355: VLSI System Design (Spring)
Undergrad: ESE 440/ESE 441: Senior Design Project
Grad: ESE 556: VLSI Physical and Logic Level Design Automation (Spring)
Grad: ESE 566: Hardware-Software Co-Design of Embedded Systems (Fall)
Grad: ESE 588: Pattern Recognition (Spring)
Grad: ESE 670: Research Topics in EE/CE (Fall)

ESE 566, ESE 588 and ESE 670 form a course sequence that discusses model-based decision making using networks of embedded systems. ESE 566 presents the fundamentals of embedded architectures (hardware and software), networking and design methods for performance optimization. ESE 588 focuses on model development using pattern recognition and data mining. ESE 670 discusses decision making techniques, including centralized and decentralized optimization, constraint satisfaction and game theory.


Professional Service


Presentations and Talks

My recent readings

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