Source: http://www.ee.uconn.edu/krishna-r-pattipati/
Timestamp: 2019-04-22 16:10:54+00:00

Document:
Dr. Krishna Pattipati received the B. Tech. degree in electrical engineering with highest honors from the Indian Institute of Technology, Kharagpur, in 1975, and the M.S. and Ph.D. degrees in systems engineering from UConn, Storrs, in 1977 and 1980, respectively. He was with ALPHATECH, Inc., Burlington, MA from 1980 to 1986. He has been with the department of Electrical and Computer Engineering at UConn, where he is currently the Board of Trustees Distinguished Professor and the UTC Chair Professor in Systems Engineering. Dr. Pattipati’s research activities are in the areas of proactive decision support, uncertainty quantification, smart manufacturing, autonomy, knowledge representation, and optimization-based learning and inference. A common theme among these applications is that they are characterized by a great deal of uncertainty, complexity, and computational intractability. He is a cofounder of Qualtech Systems, Inc., a firm specializing in advanced integrated diagnostics software tools (TEAMS, TEAMS-RT, TEAMS-RDS, TEAMATE), and serves on the board of Aptima, Inc.
Dr. Pattipati was selected by the IEEE Systems, Man, and Cybernetics (SMC) Society as the Outstanding Young Engineer of 1984, and received the Centennial Key to the Future award. He has served as the Editor-in-Chief of the IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS–PART B from 1998 to 2001. He was co-recipient of the Andrew P. Sage Award for the Best SMC Transactions Paper for 1999, the Barry Carlton Award for the Best AES Transactions Paper for 2000, the 2002 and 2008 NASA Space Act Awards for “A Comprehensive Toolset for Model-based Health Monitoring and Diagnosis,” and “Real-time Update of Fault-Test Dependencies of Dynamic Systems: A Comprehensive Toolset for Model-Based Health Monitoring and Diagnostics”, and the 2003 AAUP Research Excellence Award at UCONN. He is an elected Fellow of IEEE and of the Connecticut Academy of Science and Engineering.
Dr. Pattipati has developed multi-disciplinary and popular courses on advanced machine learning (ECE6141: Neural Networks for Classification and Optimization), linear programming and network flows (ECE6108: Linear Programming and Network Flows), nonlinear optimization (ECE6437: Computational Methods for Optimization), computational methods in control and communications (ECE6435:Advanced Numerical Methods in Scientific Computation), and stochastic models (ECE6433: Stochastic Models for the Analysis of Computer Systems and Communication Networks). As part of his leadership in the UTC Institute for Advanced Systems Engineering (UTC-IASE), Dr. Pattipati worked closely with other center leaders in the layout of seven new courses, and developed and taught SE 5202 (Foundations of Control for Thermal Fluid Systems) to UTC employees as part of the teaching mission of the UTC-IASE. Professor Pattipati regularly teaches ECE3111: Systems Analysis and ECE 4121/6095: “Digital Control of Mechatronic Systems”. He additionally developed an undergraduate systems Lab focused on cyber-physical systems. Major innovations in his teaching include widely acclaimed lecture notes for all courses (many students claim they are better than the assigned text books), extensive use of MATLAB in lectures, and the requirement to work in teams of three or fewer students on a project of their choice to amplify ideas in lectures. The latter is an enormous motivator for the creativity he sees in students.
Dr. Pattipati’s research has spanned the areas of agile planning, team decision-making, adaptive organizational design, modeling asymmetric threats, automated testing, model-based and data-driven diagnostics and prognostics, multi-target tracking, multi-user interference in wireless communications, computer system performance optimization, and scheduling of manufacturing systems. Dr. Pattipati’s research in complex system diagnostics and prognostics has been recognized by way of 8 Best Paper Awards at IEEE Autotest conferences, 2 Best Paper Awards in two different IEEE Transactions (AES & SMC), and 2 NASA Space Act Awards. His algorithms have been applied in a number of applications at NASA (e.g., Space station, Ares-1X, Launch complex), semi-conductor fabrication facilities (where downtime incurs significant economic cost), medical equipment (where patient safety and equipment availability are paramount), and ground tactical vehicles, to name a few. Dr. Pattipati’s work on fingerprinting of rare events was presented to JASON study group on rare events in June 2009. His work on command decision making and distributed dynamic resource allocation, weather-impacted ship routing and water space management has been transitioned to the US Navy. His algorithmic work on battery management systems has been patented and the algorithms are embedded in mobile devices by a leading semiconductor company.
PI/Co-PI on research grants/contracts from the Office of Naval Research, National Science Foundation, DARPA, the Air Force Office of Scientific Research, Naval Postgraduate School, Department of Economic Development of the State of Connecticut, General Motors (Warren, MI and India Science Lab, Bangalore), Toyota Technical Center (Ann Arbor, MI), National Aeronautics and Space Administration, Aptima, BAE Systems, Comcast, Fairchild Semiconductor, Hamilton Sundstrand, Harris Corporation, Pratt & Whitney, Sikorsky Aircraft, Pitney-Bowes and CALSPAN. Total funding value exceeded $15 M.
Google Scholar Citations: 10,783; h-index: 52; i-10 index: 201 (Accessed 2-23-2017).
B. Balasingam, P. Mannaru, D. Sidoti, K.R. Pattipati and P.K. Willett, “Online Anomaly Detection in Big Data: The First Line of Defense Against Intruders,” in Witold Pedrycz and Shy-Ming Chen (Eds.) Data Science and Big Data: An Environment of Computational Intelligence, Springer, 2017, pp. 1-25.
A. Abdollahi, K. R. Pattipati, P. B. Luh, A. Kodali, S. Singh, S. Zhang, and P.B. Luh, “Probabilistic Graphical Models for Fault Diagnosis in Complex Systems”, in Lance Fiondella and Antonio Puliafito (Eds. ) Book in honor of Prof. K.S. Trivedi’s 70th birthday, Springer, June 2016, pp. 109-139.
K. Choi, V. Asal, J. Wilkenfeld and K.R. Pattipati, “Forecasting the Use of Violence in Ethno‐political Organizations: Middle Eastern Minorities and the Choice of Violence,” in Handbook of Computational Approaches to Counterterrorism, Springer 2012.
R. A. Ammar, S.A. Demurjian, Sr., I.R. Greenshields, K.R. Pattipati and S. Rajasekaran, “Analysis of Heterogeneous Data in Ultrahigh Dimensions,” in R. Popp and J. Yen (eds.) Emergent Information Technologies and Enabling Policies for Counter Terrorism, Wiley-IEEE Press, May 2006, pp. 105-124.
J. B. Sharkey, D. Weishar, J. Lockwood, R. Loui, R. Rohwer and J. Byrnes, K. R. Pattipati, S. Eick, and D. Cousins “Signal Processing and Information Management Technologies for Counter-Terrorism,” in R. Popp and J. Yen (eds.) Emergent Information Technologies and Enabling Policies for Counter Terrorism, Wiley-IEEE Press, May 2006, pp. 75-104.
K. R. Pattipati, P.K. Willett, J. Allanach, H. Tu and S. Singh, “Hidden Markov Models and Bayesian Networks for Counter-terrorism,” in R. Popp and J. Yen (eds.) Emergent Information Technologies and Enabling Policies for Counter Terrorism, Wiley-IEEE Press, May 2006, pp. 27-50.
G. Levchuk, D. Serfaty and K.R. Pattipati, “Normative Design of Project-Based Adaptive Organizations,” Chapter 8 in S. Burke, L. G. Pierce and E. Salas (Eds.), Advances in Human Performance and Cognitive Engineering Research, Volume 6, Understanding Adaptability: A Prerequisite for Effective Performance within Complex Environments, Elsevier, 2005, pp. 249-287.
M. Mishra, D. Sidoti, G. Avvari, P. Mannaru, D.F.M. Ayala, K.R. Pattipati and D. L. Kleinman, “A Context-Driven Framework for Proactive Decision Support with Applications” submitted to IEEE Access, February 2017.
Y. Yan, P.B. Luh and K.R. Pattipati, “Fault Diagnosis of HVAC: Air Delivery and Terminal Systems,” submitted to IEEE Transactions on Robotics-Letters, February 2017.
D. McMenemy, D. Sidoti, F. Palmieri and K.R. Pattipati, “A Fast and Efﬁcient Conﬂict Detection Method for Ellipsoidal Safety Regions,” submitted to IEEE Trans. On AES, February 2017.
M. Mishra, W. An, X. Han, D.F.M. Ayala, D. Sidoti, K.R. Pattipati and D. L. Kleinman, “Context-Aware Decision Support for ASW Mission Planning in a Dynamic Environment,” submitted to IEEE Transactions on Systems, Man and Cybernetics, revised January 2017.
Q. Lu, K. Domrese, P. Willett, Y. Bar-Shalom and K.R. Pattipati,”A Bootstrapped PMHT with Feature Measurements,” submitted to IEEE Trans. AES, Jan. 2017.
D.F.M. Ayala, B. Balasingam, S. McComb, and K.R. Pattipati, “Markov Modeling and Analysis of Team Communication,” revision submitted to IEEE Transactions on Human and Machine Systems, February 2017.
R. Ghimire, C. Zhang and K.R. Pattipati, “A Rough Sets Theory-based Fault Diagnosis Method for Electric Power Steering System”, submitted to IEEE Transactions on Systems, Man and Cybernetics, 2016.
L. Zhang, D. Sidoti, K.R. Pattipati and D. Castanon, “Approaches to Obtain a Large Number of Ranked Solutions to 3-Dimensional Assignment Problems,” submitted to Journal of Advances in Information Fusion, 2016.
D. Sidoti, X. Han, D.F.M. Ayala, M. Mishra, S. Sankavaram, W. An and K.R. Pattipati, “Context-Aware Dynamic Asset Allocation for Maritime Interdiction Operations – Part II: Application and Sensitivity Analysis,” submitted to IEEE Transactions on Systems, Man and Cybernetics: Systems, 2016.
D. Sidoti, X. Han, D.F.M. Ayala, M. Mishra, S. Sankavaram, W. An and K.R. Pattipati, “Context-Aware Dynamic Asset Allocation for Maritime Interdiction Operations – Part I: Approximate Dynamic Programming Approaches,” submitted to IEEE Transactions on Systems, Man and Cybernetics: Systems, 2016.
Y. Yan, P.B. Luh and K.R. Pattipati, “Fault diagnosis of HVAC air handling systems considering fault propagation impacts among components,” to appear in IEEE Transactions on Automation Science and Engineering, 2017.
A. Abdollahi, X. Han, N. Raghunathan, B. Pattipati, B. Balasingam, K. R. Pattipati and Y. Bar-Shalom, B. Card “Optimal Charging for General Equivalent Electrical Battery Model, and Battery Life Management,” Journal of Energy Storage, Vol. 9, pp. 47-58, February 2017.
D. Pasupuleti, P. Mannaru, B. Balasingam, M. Baum, K. R. Pattipati, P. Willett, C. Lintz, G. Commeau, F. Dorigo, and J. Fahrny, “Cognitive Video Streaming,” Journal of Advancements in Information Fusion, In press, July 2016.
D. Belfadel, Osborne III, Y. Bar-Shalom, and K. Pattipati, “Space Based Sensor Bias Estimation in the Presence of Data Association Uncertainty,” Journal of Advancements in Information Fusion, in press, May 2016.
D. Sidoti, G. V. Avvari, M. Mishra, L. Zhang, B. Nadella, J. A. Hansen, and K. R. Pattipati, “A Multi-Objective Path Planning Algorithm with Time Windows for Asset Routing in a Dynamic Weather-Impacted Environment,” IEEE Transactions on Systems, Man and Cybernetics: Systems, June 2016, DOI: 10.1109/TSMC.2016.2573271.
C. Sankavaram, K. Pattipati, S. Singh, Y. Zhang, and M. Salman, “An Inference-based Prognostic Framework for Health Management of Automotive Systems,” International Journal of Prognostics and Health Management, Vol. 7, June 2016, pp.1-16.
C. Zhao, K.R. Pattipati, G. Liu, J. Qiu, K. Lv and T. Li, “A Markov Chain-Based Testability Growth Model with a Cost-Benefit Function,” IEEE Trans. On Systems, Man, and Cybernetics: Systems, Vol. 46, No. 4, pp. 512-523, April 2016.
G. Avvari, B. Pattipati, B. Balasingam, K. Pattipati and Y. Bar-Shalom, “Battery fuel gauge validation on portable li-ion battery cells,” Applied Energy, December 2015.
B. Balasingam, G. Avvari, K. Pattipati and Y. Bar-Shalom, “Performance analysis results of a BFG algorithm at multiple temperatures,” Journal of Power Sources, vol. 273, pp. 742–753, January, 2015.
G. Avvari, B. Balasingam, K. Pattipati and Y. Bar-Shalom, “ A battery chemistry-adaptive fuel gauge using probabilistic data association,” Journal of Power Sources, vol. 273, pp. 185–195, December, 2014.
B. Balasingam, B. Pattipati, G. Avvari, K. Pattipati and Y. Bar-Shalom, “A robust approach to battery fuel gauging, Part I: Real time model identification,” Journal of Power Sources, vol. 272, pp. 1142–1153, December, 2014.
B. Balasingam, B. Pattipati, G. Avvari, K. Pattipati and Y. Bar-Shalom, “A robust approach to battery fuel gauging, Part II: Real time capacity estimation,” Journal of Power Sources, vol. 269, pp. 949–961, December, 2014.
B. Pattipati, B. Balasingam, G. Avvari, K. Pattipati and Y. Bar-Shalom, “Open circuit voltage characterization of Lithium-ion batteries,” Journal of Power Sources, vol. 269, pp. 317–333, December, 2014.
C. Sankavaram, B. Pattipati, K. Pattipati, Y. Zhang, and M. Howell, “Fault Diagnosis in Hybrid Electric Vehicle Regenerative Braking System,” IEEE Access, vol. 2, pp. 1225-1239, October, 2014.
X. Han, M. Mishra, S. Mandal, H. Bui, D. F. M. Ayala, D. Sidoti, K.R. Pattipati and D.L. Kleinman, “Optimization-based Decision Support Software for Team-in-the-Loop Experiment: Multi-level Asset Allocation,” IEEE Transactions on SMC: Systems, vol. 44, no. 8, pp. 1098-1112, August, 2014.
X. Han, S. Mandal, K. R. Pattipati, D. L. Kleinman, and M. Mishra, “An Optimization-based Multi-Agent Distributed Planning Algorithm: A Blackboard-Based Collaborative Framework,” IEEE Trans. On SMC: Part A – Systems, Vol. 44, No. 6, pp. 673-686, June 2014.
Y. Song, B. Wang, Z. Shi, K. R. Pattipati and S. Gupta, “Distributed Algorithms for Energy-Efficient Even Self-Deployment in Mobile Sensor Networks”, IEEE Transactions on Mobile Computing, Early Access Articles, April 2013.
S. Zhang, K.R. Pattipati, Z. Hu, X. Wen, “Optimal Selection of Imperfect Tests for Fault Detection and Isolation,” IEEE Transactions on Systems, Man and Cybernetics, part A – Systems, Vol. 43, No. 6, pp. 1424-1439, Nov. 2013.
S. Zhang, K.R. Pattipati, Z. Hu, X.Wen, and C. Sankavaram, “Dynamic Coupled Fault Diagnosis with Propagation and Observation Delays,” IEEE Transactions on Systems, Man and Cybernetics, part A – Systems, Vol. 43, No. 6, pp. 1370-1384, Nov. 2013.
D. F. Crouse, R.W. Osborne III, K.R. Pattipati, P.K. Willett, and Y. Bar-Shalom, “Efficient 2D Sensor Location Estimation Using Targets of Opportunity,” Journal of Advances in Information Fusion, Vol. 8, No., 1, June 2013.
B. Pattipati, C. Sankavaram, K.R. Pattipati, Y. Zhng, M. Howell and M. Salman, “Multiple Model Moving Horizon Estimation Approach to Prognostics in Coupled Systems,” IEEE Aerospace and Electronic Systems Magazine, Vol. 28, No. 3, pp. 4-12, March 2013.
A. Kodali, Y. Zhang, C. Sankavaram, K.R. Pattipati and M. Salman, “Fault Diagnosis in Automotive Electric Power Generation and Storage System (EPGS),” IEEE/ASME Trans. On Mechatronic Systems, Vol. 18, No. 6, pp. 1809-1818, December 2013.
A. Kodali, K. Pattipati and S. Singh, “A Coupled Factorial Hidden Markov Model (CFHMM) for Diagnosing Coupled Faults” IEEE Trans. on SMC: Part A, Vol.43, No. 3, pp. 522-534, May 2013.
A. Kodali, S. Singh, K. Pattipati, “Dynamic set-covering for real-time multiple fault diagnosis with delayed test outcomes,” IEEE Trans. on SMC: Part A, Vol. 43, No.3, pp. 547-562, May 2013.
X. Han, H. Bui, S. Mandal, K.R. Pattipati and D.L. Kleinman, “Optimization-based Decision Support Software for Team-in-the-loop Experiment – MOC-1: Asset Package Selection and Planning,” IEEE Trans. on SMC: Part A – , Vol. 43, No. 2, pp. 237-251, March 2013.
Z. Wang, S. Zhou, J. C. Presig, K. R. Pattipati, and P. K. Willett, “Clustered Adaptation for Estimation of Time-Varying Underwater Acoustic Channels,“ IEEE Trans. on Signal Processing, Accepted for publication, Vol. 60, No. 6, June 2012, pp. 3065-3078.
X. Han, F. Yu, G. Levchuk, F. Tu and K.R. Pattipati, “A Probabilistic Computational Model for Identifying Organizational Structures from Uncertain Message Data,” Journal of Advances in Information Fusion, Vol. 7, No. 1, June 2012, pp. 78-96.
B. Wang, W. Wei, H. Dinh, W. Zeng and K.R. Pattipati, “Fault Localization using Passive End-to-End Measurements and Sequential Testing for Wireless Networks”, IEEE Trans. On Mobile Computing, Vol. 11, No. 3, March 2012, pp. 439-452.
C. Park, K. R. Pattipati, W. An, and D. L. Kleinman, “Quantifying the impact of information and organizational structures via distributed auction algorithm: Point-to-point communication structure”, IEEE Transactions on Systems, Man and Cybernetics: Part A., Vol. 42, No. 1, January 2012, pp. 68-86.
Y. Yan, P.B. Luh and K.R. Pattipati, “Fault Diagnosis of HVAC: Air Delivery and Terminal Systems,” 2017 IEEE Conference on Automation Science and Engineering, X’ian, China, August 20-23, 2017.
P. Mannaru, B. Balasingam, K.R. Pattipati, C. Sibley and J. Coyne, “Heterogeneous Hidden Markov Models for Context Modeling Through Eye Gaze Observations,” AAAI Spring 2017 Symposium Series, Palo Alto, CA, March 27-29, 2017.
M. Mishra, D. Sidoti, G.V. Avvari, P. Mannaru, D.F.M.Ayala, and K.R. Pattipati, “Context-Driven Proactive Decision Support: Challenges and Applications,” invited paper AAAI Spring 2017 Symposium Series, Palo Alto, CA, March 27-29, 2017.
Y. Qin, et al., “A Control Theoretic Approach to Rate Adaptation for ABR Video Streaming over Cellular: A Fresh Look at PID-based Control,” IEEE INFOCOM 2017, Atlanta, GA, May 1-4, 2017.
H. Ravichandar, A, Kumar, A. Dani and K.R. Pattipati, “Learning and Predicting Sequential Tasks using Recurrent Neural Networks and Multiple Model Filtering,” AAAI-FSS 2016, Shared Autonomy in Research and Practice, Washington, DC, 2016.
R. Ghimire, K. R. Pattipati and P. B. Luh, “Fault diagnosis and augmented reality (AR)-based guided troubleshooting of HVAC systems”, IEEE Autotestcon, Anaheim, California, 2016.
P. Mannaru, B. Balasingam, K. Pattipati, C. Sibley and J. Coyne, “Human-machine system improvement through cognitive context detection,” Annual Meeting of the Human Factors and Ergonomics Society, Oct. 2016.
P. Mannaru, B. Balasingam, K. Pattipati, C. Sibley and J. Coyne, “Cognitive context detection in UAS operators using pupillary measurements,” SPIE Conferences on Defense, Security, and Sensing, April 2016.
P. Mannaru, B. Balasingam, K. Pattipati, C. Sibley and J. Coyne, “Cognitive context detection in UAS operators using gaze patterns,” SPIE Conferences on Defense, Security, and Sensing, April 2016.
P. Mannaru, B. Balasingam, K. Pattipati, C. Sibley and J. Coyne, “On the use of hidden Markov models for eye-gaze pattern modeling and classification,” SPIE Conferences on Defense, Security, and Sensing, April 2016.
L. Zhang, D. Sidoti, K. R. Pattipati, and D. Castanon, “Approaches for Solving m-best 3-Dimensional Dynamic Scheduling Problems for Large m,” International Conference on Information Fusion, July, 2016.
B. Balasingam, M. Baum, D. Pasupuleti, P. Mannaru, K. R. Pattipati, P. Willett, C. Lintz, G. Commeau adn F. Dorigo, and J. Fahrny, “Playtime prediction of video streams using nonlinear regression and feature selection,” IEEE International Conference on Information Fusion, July, 2015.
B. Balasingam, K. Pattipati, and Y. Bar-Shalom, “Algorithms for Advanced Battery Management System Design”, 47th Power Sources Conference, June 2016.
B. Nadella, G. V. Avvari, A. Kumar, M. Mishra, D. Sidoti, C. Sibley and K. R. Pattipati, “Dynamic Routing of Unmanned Aerial Vehicles in Uncertain Mission Environment”, in IEEE Aerospace Conference, March 2016.
A. Abdollahi, N. Raghunathan, X. Han, B. Pattipati, B. Balasingam, K. R. Pattipati, Y. Bar-Shalom, and B. Card. “Battery health degradation and optimal life management.” in IEEE Autotestcon, pp. 146-151, 2015.
Y. Yan, P. B. Luh and K. R. Pattipati, “A Fault Diagnosis Method for HVAC Air Handling Units Considering Fault Propagation,” IEEE Conference on Automation Science and Engineering, August, 2015.
A. A. Farhan, K. R. Pattipati, B. Wang, and P. B. Luh, “Predicting Individual Thermal Comfort using Machine Learning Algorithms,” IEEE Conference on Automation Science and Engineering, August 2015.
A. Abdollahi, N. Raghunathan, X. Han, G. V. Avvari, B. Balasingam, K. R. Pattipati and Y. Bar-Shalom, “Battery Charging Optimization for OCV-Resistance Equivalent Circuit Model,” American Control Conference, pp. 3467-3472, 2015.
D. Pasupuleti, P. Mannaru, B. Balasingam, M. Baum, K. R. Pattipati, and P. Willett, “Cognitive Video Streaming,” IEEE International Conference EEECOS, March 2015.
D. Pasupuleti, P. Mannaru, B. Balasingam, M. Baum, K. R. Pattipati, P. Willett, C. Lintz, G. Commeau, F. Dorigo, and J. Fahrny, “Online Playtime Prediction for Cognitive Video Streaming,” Fusion 2015, July 2015.
M. Mishra, D. Sidoti, D. F. M. Ayala, G. V. Avvari, X. Han, W. An, L. Zhang, K. R. Pattipati and J. Hansen, “Dynamic Resource Management and Information Integration for Proactive Decision Support and Planning,” Fusion 2015, July, 2015.
G. V. Avvari, D. Sidoti, M. Mishra, L. Zhang, B. K. Nadella and K. R. Pattipati. “Dynamic Asset Allocation for Counter Smuggling Operations Under Disconnected, Intermittent and Low-Bandwidth Environment,” IEEE Symposium on Computational Intelligence for Security and Defense Applications (IEEE CISDA 2015), Verona, NY, May 2015.
B. Balasingam, K. R. Pattipati, G. Levchuck and J. C. Romano, “Robust collaborative learning by multi-agents,” IEEE Symposium on Computational Intelligence for Security and Defense Applications (IEEE CISDA 2015), Verona, NY, May 2015.
D. M. F. Ayala, D. Sidoti, M. Mishra, X. Han, and K. R. Pattipati, “Context-based Models to Overcome Operational Challenges in Maritime Security,” IEEE Symposium on Technologies for Homeland Security, April, 2015.
D. Sidoti, D. F. M. Ayala, S. Sankavaram, X. Han, M. Mishra, W. An, D. Kellmeyer, J. Hansen, and K. R. Pattipati, “Decision support information integration platform for context-driven interdiction operations in counter-smuggling missions,” 2014 IEEE/SICE International Symposium on System Integration, pp. 659–664, Tokyo, Japan, December, 2014.
M. Mishra, W. An, X. Han, D. Sidoti, D. F. M. Ayala and K. R. Pattipati, “Decision Support System for ASW Mission Planning within a Dynamic and Uncertain Mission Environment,” IEEE International Conference on Systems, Man and Cybernetics, pp. 3390-3393, San Diego, CA, October, 2014.
B. Pattipati, B. Balasingam, G. V. Avvari, K. Pattipati and Y. Bar-Shalom, “Robust battery fuel gauge algorithm development, Part 0: Normalized OCV modeling approach,” International Conference on Renewable Energy Research and Applications, pp. 116 – 121, October, 2014.
B. Balasingam, B. Pattipati, G. V. Avvari, K. Pattipati and Y. Bar-Shalom, “Robust battery fuel gauge algorithm development, Part 1: Online parameter estimation,” International Conference on Renewable Energy Research and Applications, pp. 98- 103, October, 2014.
B. Balasingam, B. Pattipati, G. V. Avvari, K. Pattipati and Y. Bar-Shalom, “Robust battery fuel gauge algorithm development, Part 2: Online battery-capacity estimation,” International Conference on Renewable Energy Research and Applications, pp. 104- 109, October, 2014.
B. Balasingam, B. Pattipati, G. V. Avvari, K. Pattipati and Y. Bar-Shalom, “Robust battery fuel gauge algorithm development, Part 3: State of charge tracking,” International Conference on Renewable Energy Research and Applications, pp. 110- 115, October, 2014.
B. Pattipati, B. Balasingam, A. Abdollahi, G. V. Avvari, K. R. Pattipati and Y. Bar-Shalom “Integrated battery fuel gauge and optimal charger,” IEEE Autotest Conference, pp. 260- 269, September, 2014.
C. X. Zhao, K. R. Pattipati, J. Qiu, G. J. Liu and K. H. Lv, “A testability growth model and its application,” IEEE Autotest Conference, pp. 121- 128, September, 2014.
Y. Yan, P. B. Luh and K. R. Pattipati, “Fault Diagnosis Framework for Air Handling Units based on Integration of Dependency Models and PCA,” IEEE Conference on Automation Science and Engineering, pp. 1103-1108, September, 2014.
Balasingam, S. Sankavaram, K. Choi, D. F. M. Ayala, D. Sidoti, K. R. Pattipati, P. Willett, C. Lintz, G. Commeau, F. Dorigo and J. Fahrny, “Online anomaly detection in big data,” 15th International Conference on Information Fusion, pp. 1- 8, July 2014.
U.S. Patent Number US 2014/0244193 A1, Battery State of Charge Tracking, Equivalent Circuit Selection and Benchmarking, August 28th, 2014.
U.S. Patent Number US 2014/0244225 A1, Battery State of Charge Tracking, Equivalent Circuit Selection and Benchmarking, August 28th, 2014.

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