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#Hiring multiple positions (Technical architect, Senior AI scientist, Data scientist, PhD positions, interns and working students)
Dr. PANKAJ GUPTA, PhD
Dr. PANKAJ GUPTA, PhD
Leading AI-driven Industrial Innovation
Managing Director | Founder | Chief Technologist | Chief Scientist | Chief Product Officer at DRIMCo GmbH
OpenFLaaS Principal Investigator, funded by BMWk Federal Ministry Germany
Teaching "Deep Learning and Artificial Intelligence" at LMU, Munich
FORMER AFFILIATION
Chief Scientific Advisor at Insaas GmbH
Lead Research Scientist @Siemens AG
Research Intern at IBM Research
PhD Researcher at LMU Munich
Masters at TUM Munich
Senior Software Eng. at ALTRAN India
Software Eng. at Wipro India
EXPERIENCE
Professional Hands-on (13+ years)
Research (10+ years)
Research & Applications
NATURAL LANGUAGE PROCESSING
Information Extraction, Entity-Relation Extraction, Static and Dynamic Topic Modeling, Representation Learning, Semantic Textual Similarity, Document Layout Analysis, etc.
MACHINE LEARNING
Deep Learning, Recurrent Neural Networks, Probabilistic Graphical Models, Unsupervised Representation Learning, Semi-supervised Bootstrapping, Transfer and Domain learning, Lifelong Learning, Multi-tasking, Explainable AI, etc.
HOT TOPICS
Federated AI Learning, Edge Computing, Lifelong Continual Learning, Cross-client transfer learning with data privacy, Multi-modality (text + images) Document analysis, etc.
Dr. Pankaj Gupta is an accomplished technology leader, innovator, and AI researcher, serving as the Founder, CTO/CPO, and Chief Scientist at DRIMCo GmbH, headquartered in Munich, Germany. He is driving the development of innovative enterprise software solutions focused on industrial digitalization, business process optimization, and bridging AI innovation with industrial applications.
At DRIMCo, Dr. Gupta leads the vision, artificial intelligence research, and the technology stack behind DRIM — The Next-Generation Tender Assistant, a powerful tool designed for AI-driven requirement management in Product Lifecycle Management (PLM) workflows. Powered by state-of-the-art AI-NLP (Artificial Intelligence - Natural Language Processing) and GenAI technologies, DRIM enables smarter, faster, and more efficient tendering processes and requirement intelligence.
(#SmartTendering #RequirementIntelligence)
Dr. Gupta is also the lead for the innovation OpenFLaaS Project — a major national initiative funded by BMWk (Federal Ministry for Economic Affairs and Climate Action, Germany). OpenFLaaS is recognized as Germany’s answer to AI sovereignty, focusing on building open, sovereign AI frameworks for the future. Alongside his industrial contributions, Dr. Gupta is passionate about academia. He lectures on Deep Learning and Artificial Intelligence at Ludwig Maximilian University (LMU) Munich, providing guidance and supervision to PhD and Master's students specializing in advanced AI topics.
Previously, he worked as a Lead Research Scientist (AI-NLP) at Siemens AG, Munich, and the IBM Research Lab, Zurich, where he developed cutting-edge solutions in enterprise AI and natural language understanding.
With his unique blend of research excellence and real-world application, Dr. Gupta is at the forefront of AI-driven digital transformation in the industrial sector.
My mantra: "Science -> Technology -> Product led Growth" AND "Great Product makes Great Business"
Pankaj Gupta actively contributes in NLP, machine learning and AI conferences, and has peer-reviewed publications in the top tier conferences, such as ICML, ICLR, AAAI, NAACL, EMNLP, COLING, ICASSP, etc. He has served as an "expert reviewer" for ICML, Senior Program committee member at CoLLAs, program committee (PC) member for several conferences (e.g., NeurIPS, ICLR, ICML, ACL, AAAI, EMNLP, IJCNLP, AACL, CoLLA, CLAI, etc.), and journals (e.g., IEEE Transactions on Intelligent Transportation Systems, IEEE/ACM Transactions on Audio, Speech and Language Processing). He has won several shared tasks based on machine learning, information extraction and information retrieval. If interested, please checkout his talks and lectures here. Dr. Gupta also holds 15 patents on the topics at the intersection of applied artificial intelligence, natural language processing, deep learning and machine learning in industrial applications and usecases.
His research contributions span from information extraction, textual representation learning to document analysis, including lifelong learning of AI, federated learning, entity-relation extraction, neural topic modeling, representation learning, semantic textual similarity and interpretability of neural networks. Beyond research, he also builds cutting-edge enterprise product based on the state-of-the-art technologies. Towards Natural Language Processing (NLP) and AI core research, Dr. Gupta enjoys building state-of-the-art neural computational models, for instance, composite neural language models at the intersection of the probabilistic graphical models, deep learning, transfer learning, continuous lifelong learning, federated AI learning, topic and language modeling techniques, especially in unsupervised and self-supervised learning paradigms.
Pankaj Gupta earned his doctoral degree PhD (thesis title: Neural Information Extraction from Natural Language Text, 2019) in Computer Science/Computation Linguistics, advised by Prof. Hinrch Schütze (LMU, Germany) and focused on neural relation extraction and neural topic modeling for document semantic extraction and representation learning. During winter 2016, he did a PhD research internship at IBM Research Zurich with Dr. Angela Fahrni and Dr. Abdel Labbi. Dr. Gupta earned Masters (Computer Science) with Distinction from Technical University of Munich, Germany in Nov 2015. His Master thesis titled: "Deep Learning Methods for the Extraction of Relations in Natural Language Text " was supervised by Prof. Thomas Runkler, Dr. Heike Adel, Dr. Bernt Andrassy, Dr. Hans-Georg Zimmermann, and Prof. Hinrich Schütze. Before coming to Munich, he worked with Wipro and Aricent Technologies, India as a Senior Software Developer (C programmer) during 2010-2013. In 2010, he obtained Bachelor of Technology in Information Technology with Distinction from Amity University, Noida India. His Bachelor thesis is "Summarizing text by ranking text units according to shallow linguistic features".
Pankaj Gupta often looks for good master and PhD students in research and applications. If interested in working student, inter-disciplinary project, master thesis, intern or PhD position, please write him. Checkout his current/past students here.
News/Recent Activities (Beyond Regular Business)
News/Recent Activities (Beyond Regular Business)
[April 2024] Invited Speaker as Ministry AI Expert on "Mobile GenAI-Rooms for Requirement Engineering and Regulation Analysis in Manufacturing 4.0" at Workshop: Market Pathways for Cloud Edge IoT in the Manufacturing Sector
[Mar 2024] Speaking at The Future Days for SMEs on "Advantages of Edge Computing and Data Management for SMEs in Germany via OpenFLaaS"
[Mar 2024] Speaker TechTalk at AutomotiveMasterMinds conference Berlin
[Feb 2024] DRIMCO attending Bosch Connected World conference Berlin
[Nov 2023] Speaker at MLCon2023 Berlin on OpenFLaaS: Germany's answer to AI Sovereignty for Industrial Knowledge Digitalization
[Nov 2023] Speaker at MLCon2023 Berlin on Human-like Lifelong Learning in Every AI Machine?
[Nov 2023] Teaching/lecturing at LMU Munich, lecture on Deep Learning & AI series: Attention, Transformers, Large Language Models and the rise of Natural Language Processing
[Nov 2023] Teaching/lecturing at LMU Munich, lecture on Deep Learning & AI series: RNNs and Natural Language Processing
[2023] Program Committee Member / Reviewer for ICLR2024 conference
[2023] Program Committee Member / Reviewer for AAAI 2024 conference
[2023] Program Committee Member / Reviewer for Continual AI Un - Conference (CLAI) 2023
[2023] Conference Senior Reviewer / Program Committee Member for the Conference on Lifelong Learning Agents (CoLLAs) 2023
[Sept 2023] Speaker at 53rd annual conference of the German Informatics Society (Informatics 2023 Festival) Berlin in workshop "Shaping the future sustainably through digitized value-added processes (DigiWe)"
[Sept 2023] Keynote speaker at "International Conference on Data Science, AI and Analytics: Bridging the Gap Between Theory and Practices (ICDSAIA-2023)" Malaysia
[Sept 2023]
[Jun 2023] Speaker at MLCON2023 Munich on "Human-like Lifelong Learning in AI Machines for Tender-Requirement Analysis and Business Intelligence"
[May 2023] Keynote speaker at The Munich Product Conference 2023 Product Network Europe in panel of Chief Product Officers and Senior Product Leaders
[May 2023] Leading and Moderating the OpenFLaaS project kickoff meeting with consortium, funding parties and Federal Ministry for Economic Affairs and Climate Action
[Mar 2023] Speaking at Digital Technology Forum at the kick-off of OpenFLaaS research project funded by Federal Ministry for Economic Affairs and Climate Action
[Mar 2023] Senior Program committee member at Conference on Lifelong Learning Agents CoLLAs 2023
[Nov 2022] Speaking at Digital Technology Forum at the closing of PLASS research project funded by Federal Ministry for Economic Affairs and Climate Action
[Nov 2022] Teaching Deep Learning and AI for Master Course in Data Science at LMU, Germany
[Oct 2022] PC member for #ICLR2023: Paper review 5x for #ICLR2023 in areas of AI / ML / NLP/ Federated Learning / Continual Learning
[Oct 2022] PC member for #AAAI2023: Paper review 6x for #AAAI2023 in areas of AI / ML / NLP
[Oct 2022] Paper accepted at EMNLP 2022 (findings) on Federated Continual Learning #title: "Federated Continual Learning for Text Classification via Selective Inter-client Transfer"
[Aug 2022] DRIMCo (lead by Dr. Pankaj Gupta) wins a joint research project- OpenFLaaS in a funding competition by the Federal Ministry for Economic Affairs and Climate Action (BMWK)
[Mar 2022] Nominated Senior Program committee member at Conference on Lifelong Learning Agents CoLLAs 2022
[Jul2021] Paper reviewing for #NeurIPS2021 in areas of AI/ML/NLP/Probabilistic Modeling
[Mar2021] 4x paper reviewing in Lifelong Continual Learning and Federated Learning areas
[Mar2021] A paper accepted in NAACL2020 conference proceedings (title: "Multi-source Neural Topic Modeling in Multi-view Embedding Spaces")
[Mar2021] Nominated as "Expert Reviewer" for #ICML2021 (the topmost AI Conference)
[Oct 2020] Awarded the top 10% High-scoring reviewers by #NeurIPS2020 (the topmost AI Conference)
[Sept 2020] Our paper ("TopicBERT for Energy Efficient Document Classification") accepted at EMNLP2020 (findings)
[30 July 2020] Reviewing 6x papers for EMNLP 2020 conference
[24 July 2020] Reviewing 3x papers for NeurIPS 2020 conference
[16-17 July 2020] Giving talks at ICML2020 for our two papers: ("Neural Topic Modeling with Continual Lifelong Learning " and "Explainable and Discourse Topic-aware Neural Language Understanding ")
[25 June 2020] Started Entrepreneurship (Co-founder, CTO and Chief Scientist) at DRIMCo GmbH, Munich Germany
[22 June 2020] Left Job at Siemens AG
[01 Jun, 2019] Accepted #2 ICML papers ("Neural Topic Modeling with Continual Lifelong Learning " and "Explainable and Discourse Topic-aware Neural Language Understanding ")
[06 Dec, 2019] Giving an invited talk about "Neural Representation Learning Beyond Sentence Boundaries (for Information Extraction and Topic Modeling)" at NLPMeetup Zurich Switzerland. Recorded Talk
[04 Dec, 2019] Offering a 3-hour Honorary Lecture about "Representation and Distributional Learning" at LMU, Germany
[20 Nov, 2019] Offering a 3-hour Honorary Lecture about "Recurrent Neural Networks" at LMU, Germany
[04 Nov, 2019] Presenting (Poster/Talks) @EMNLP2019 our solutions of Shared Tasks about NER, Relation Extraction, Information Retrieval and Propaganda Detection
[08 Oct, 2019] Giving an invited talk about "Neural Representation Learning Beyond Sentence Boundaries" at NLPMeetup Munich Germany
[26 Sept, 2019] Defended my PhD thesis (title: Neural Information Extraction from Natural Language Text), Examination Committee: Dr. Ivan Titov and Dr. William Yang Wang. [Awesome pics]
[05 Sept, 2019] Our submissions (Team: MIC-CIS) rank 3rd (out of 12 participants) in fragment level and 4th (out of 25 participants) in sentence level propaganda detection shared tasks at NLP4IF workshop (EMNLP2019). solution -paper
[05 Aug, 2019] Winning (1st ranked, Team: MIC-CIS) the Bacteria Biotope Benchmark: Entity Extraction + Normalization task at BioNLP-OST workshop (EMNLP2019)
[23 July, 2019] Winning (1st ranked, Team: MIC-CIS) the SeeDev benchmark: Relation/Event Extraction shared task at BioNLP-OST workshop (EMNLP2019)
[28 June, 2019] Winning (1st ranked) the RDoC-IR (task-1) shared task at BioNLP workshop (EMNLP2019) on Information Retrieval and Extraction on Mental Health
[28 June, 2019] Winning (1st ranked) the RDoC-IE (task-2) shared task at BioNLP workshop (EMNLP2019) on Information Retrieval and Extraction on Mental Health
[05 June, 2019] Giving a talk: "Improved Neural Topic Modeling with Language Structures and Transfer Learning" at 3rd German-French Summer School on Transfer learning, Passau, Germany
[May, 2019] Submitting Doctoral Dissertation (~PhD thesis: Neural Information Extraction from Natural Language Text) at Faculty of Mathematics, Informatics and Statistics LMU Munich
[09 May, 2019] Presenting poster of our paper ("textTOvec") at ICLR-2019 conference proceedings at New Orleans, USA
[25 Mar, 2019] Giving an invited Talk: "Neural NLP Models of Information Extraction" at Google AI, New York City
[Mar-April, 2019] TWO awesome candidates (Usama Yaseen and Yatin Chaudhary) starting their PhD @Siemens, advised by me
[Jan 30, 2019] TWO oral talks ("iDocNADEe" and "iDepNN") and TWO posters ("iDocNADEe" and "iDepNN") presented at AAAI-2019 at Honolulu, Hawaii USA
[Jan, 2019] 2nd Patent published. Title: "Method and system for automatic discovery of topics and trends over time " (No: EP 3432155)
[Nov 29, 2018] Offering guest lecture about "Representation and Distributional Learning" at LMU, Germany
[Nov 24, 2018] One long paper ("textTOvec") accepted in ICLR-2019 conference. Acceptance rate: 31.4% (500/1591)
[Nov 14, 2018] Offering guest lecture about "Recurrent Neural Networks" at LMU, Germany
[Oct 31, 2018] TWO long papers ("iDocNADEe" and "iDepNN") accepted in AAAI-2019 conference. Acceptance rate: 16.2% (1150/7095)
[Oct 31, 2018] Poster presentation for our paper ("LISA") at EMNLP-2018 BlackBoxNLP workshop at Brussels, Belgium
[Aug 19, 2018] Oral talk for our paper ("Replicated Siamese LSTM") delivered at COLING-2018 at New Mexico, USA
[Jun 07, 2018] 1st Patent published. Title: "Device and Method for Natural Language Processing" (No: US 15/498517)
[Jun 01, 2018] TWO oral talks ("RNN-RSM" and "JBM") delivered at NAACL-HLT-2018 at New Orleans, USA. Talk1 Talk2
[Feb 14, 2018] TWO long papers ("RNN-RSM" and "JBM") accepted in NAACL HLT-2018 conference. Acceptance rate: 32.0% (207/647)
[Mar-Oct, 2017] Paper rejections. Working on scientific writings, advised by Prof. Hinrich Schütze and Dr. Florian Büttner
[Sep 25-27, 2017] Attending Google's 2nd Natural Language Processing Summit at Google Zurich, Switzerland
[May, 2017] Reviewing papers for EMNLP-2017
[May, 2017] Pitching/Invited Talk at Young Research Forum at Siemens AG
[Dec 11-16, 2016] Oral talk for our paper ("TF-MTRNN") delivered at COLING-2016 at New Mexico, USA
[Oct 2016-Jan 2017] PhD research internship at IBM Research Zurich
[Sept 20, 2016] One long paper ("TF-MTRNN") accepted in COLING-2016 conference. Acceptance rate: 32.4% (337/1039)
[March, 2016] One short paper ("Ranking-RNN") accepted in ICASSP-2016 conference. Acceptance rate: 47.0% (1265/2682)
[March, 2016] One short paper accepted in NAACL HLT-2016 conference. Acceptance Rate: 28.9% (82/284)
[Dec 2015] Starting PhD, advised by Prof. Hinrich Schütze at University of Munich (LMU) and Research Group Machine Intelligence at Siemens AG
[Nov 2015] Submitting Master Thesis titled: "Deep Learning Methods for the Extraction of Relations in Natural Language Text " supervised by Prof. Thomas Runkler, Dr. Heike Adel, Dr. Bernt Andrassy, Dr. Hans-Georg Zimmermann, and Prof. Hinrich Schütze
Invited Scientific Talks / Key-notes
Invited Scientific Talks / Key-notes
Google Sites
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